Weather Information Communication Technologies for Increased Safety and Mobility in the National Airspace System

The purpose of the NASA Glenn Research Center Weather Information Communications (WINCOMM) project was to develop advanced communications and information technologies to enable the high-quality and timely dissemination of strategic weather information between the flight deck and ground users as well as tactical turbulence hazard information between relevant aircraft and to the ground. This report will document and reference accomplishments on the dissemination of weather information during the en route phase of flight from ground-based weather information providers to the flight deck (ground-to-air), from airborne meteorological sensors to ground users (air-to-ground), and weather turbulence and icing hazard information between relevant aircraft (air-to-air). In addition, references in this report will demonstrate the architecture necessary to implement and perform successful transmission and reception of weather information to the cockpit, show that weather information flow does not impact "normal" traffic, demonstrate the feasibility of operational implementation, and lay foundation for future data link development

Locating previously unknown patterns in data-mining results: a dual data- and knowledge-mining method

BACKGROUND: Data mining can be utilized to automate analysis of substantial amounts of data produced in many organizations. However, data mining produces large numbers of rules and patterns, many of which are not useful. Existing methods for pruning uninteresting patterns have only begun to automate the knowledge acquisition step (which is required for subjective measures of interestingness), hence leaving a serious bottleneck. In this paper we propose a method for automatically acquiring knowledge to shorten the pattern list by locating the novel and interesting ones. METHODS: The dual-mining method is based on automatically comparing the strength of patterns mined from a database with the strength of equivalent patterns mined from a relevant knowledgebase. When these two estimates of pattern strength do not match, a high "surprise score" is assigned to the pattern, identifying the pattern as potentially interesting. The surprise score captures the degree of novelty or interestingness of the mined pattern. In addition, we show how to compute p values for each surprise score, thus filtering out noise and attaching statistical significance. RESULTS: We have implemented the dual-mining method using scripts written in Perl and R. We applied the method to a large patient database and a biomedical literature citation knowledgebase. The system estimated association scores for 50,000 patterns, composed of disease entities and lab results, by querying the database and the knowledgebase. It then computed the surprise scores by comparing the pairs of association scores. Finally, the system estimated statistical significance of the scores. CONCLUSION: The dual-mining method eliminates more than 90% of patterns with strong associations, thus identifying them as uninteresting. We found that the pruning of patterns using the surprise score matched the biomedical evidence in the 100 cases that were examined by hand. The method automates the acquisition of knowledge, thus reducing dependence on the knowledge elicited from human expert, which is usually a rate-limiting step

Structure–activity relationships of dinucleotides: Potent and selective agonists of P2Y receptors

Dinucleoside polyphosphates act as agonists on purinergic P2Y receptors to mediate a variety of cellular processes. Symmetrical, naturally occurring purine dinucleotides are found in most living cells and their actions are generally known. Unsymmetrical purine dinucleotides and all pyrimidine containing dinucleotides, however, are not as common and therefore their actions are not well understood. To carry out a thorough examination of the activities and specificities of these dinucleotides, a robust method of synthesis was developed to allow manipulation of either nucleoside of the dinucleotide as well as the phosphate chain lengths. Adenosine containing dinucleotides exhibit some level of activity on P2Y1 while uridine containing dinucleotides have some level of agonist response on P2Y2 and P2Y6. The length of the linking phosphate chain determines a different specificity; diphosphates are most accurately mimicked by dinucleoside triphosphates and triphosphates most resemble dinucleoside tetraphosphates. The pharmacological activities and relative metabolic stabilities of these dinucleotides are reported with their potential therapeutic applications being discussed

ACTS Battery and Solar Array Assembly On-Orbit Measured Performance

The Advanced Communications Technology Satellite (ACTS) is a NASA experimental communications satellite system designed to demonstrate on-orbit Ka-band communications and switching technologies that will be used by NASA and the commercial sector in the 21st century. The ACTS was launched on September 12, 1993, and has performed over 10 years of successful experimental operations. The purpose of this report is to describe the ACTS power subsystem and the ACTS solar array and battery assemblies located within the power subsystem and then to document on-orbit measured performance from launch to mission end on April 28, 2004. Solar array and battery performance data is presented, and respective conclusions are drawn. The total solar array power available to the spacecraft was measured each year at the same time, and battery voltage performance was measured twice per year at the same times during peak solar eclipse. At the highest spacecraft power demand, the ACTS uses approximately 1113 W of electrical power during the low-burstrate experiment to operate all six satellite subsystems. After 10 years of on-orbit operation, solar array available output power normal to the Sun measured 1508 W, which represents 395 W of excess margin. The ACTS batteries have successfully supported the ACTS experiment program for over 10 years and operated in excess of 900 charge and discharge cycles through 21 eclipse seasons

Predicting Itemset Sales Profiles with Share Measures and Repeat-Buying Theory

Given a random sample of sales transaction records (i.e., scanner panels) for a particular period (such as a week, month, quarter, etc.), we analyze the scanner panels to determine approximations for the penetration and purchase frequency distribution of frequently purchased items and itemsets. If the purchase frequency distribution for an item or itemset in the current period can be modeled by the negative binomial distribution, then the parameters of the model are used to predict sales profiles for the next period. We present representative experimental results based upon synthetic data