Secure ADS-B authentication system and method

A secure system for authenticating the identity of ADS-B systems, including: an authenticator, including a unique id generator and a transmitter transmitting the unique id to one or more ADS-B transmitters; one or more ADS-B transmitters, including a receiver receiving the unique id, one or more secure processing stages merging the unique id with the ADS-B transmitter's identification, data and secret key and generating a secure code identification and a transmitter transmitting a response containing the secure code and ADSB transmitter's data to the authenticator; the authenticator including means for independently determining each ADS-B transmitter's secret key, a receiver receiving each ADS-B transmitter's response, one or more secure processing stages merging the unique id, ADS-B transmitter's identification and data and generating a secure code, and comparison processing comparing the authenticator-generated secure code and the ADS-B transmitter-generated secure code and providing an authentication signal based on the comparison result

WARNING: Physics Envy May Be Hazardous To Your Wealth!

The quantitative aspirations of economists and financial analysts have for many years been based on the belief that it should be possible to build models of economic systems - and financial markets in particular - that are as predictive as those in physics. While this perspective has led to a number of important breakthroughs in economics, "physics envy" has also created a false sense of mathematical precision in some cases. We speculate on the origins of physics envy, and then describe an alternate perspective of economic behavior based on a new taxonomy of uncertainty. We illustrate the relevance of this taxonomy with two concrete examples: the classical harmonic oscillator with some new twists that make physics look more like economics, and a quantitative equity market-neutral strategy. We conclude by offering a new interpretation of tail events, proposing an "uncertainty checklist" with which our taxonomy can be implemented, and considering the role that quants played in the current financial crisis.Comment: v3 adds 2 reference

Effect of training-sample size and classification difficulty on the accuracy of genomic predictors

Introduction: As part of the MicroArray Quality Control (MAQC)-II project, this analysis examines how the choice of univariate feature-selection methods and classification algorithms may influence the performance of genomic predictors under varying degrees of prediction difficulty represented by three clinically relevant endpoints. Methods: We used gene-expression data from 230 breast cancers (grouped into training and independent validation sets), and we examined 40 predictors (five univariate feature-selection methods combined with eight different classifiers) for each of the three endpoints. Their classification performance was estimated on the training set by using two different resampling methods and compared with the accuracy observed in the independent validation set. Results: A ranking of the three classification problems was obtained, and the performance of 120 models was estimated and assessed on an independent validation set. The bootstrapping estimates were closer to the validation performance than were the cross-validation estimates. The required sample size for each endpoint was estimated, and both gene-level and pathway-level analyses were performed on the obtained models. Conclusions: We showed that genomic predictor accuracy is determined largely by an interplay between sample size and classification difficulty. Variations on univariate feature-selection methods and choice of classification algorithm have only a modest impact on predictor performance, and several statistically equally good predictors can be developed for any given classification problem

Integrated Economic and Climate Modeling

This survey examines the history and current practice in integrated assessment models (IAMs) of the economics of climate change. It begins with a review of the emerging problem of climate change. The next section provides a brief sketch of the rise of IAMs in the 1970s and beyond. The subsequent section is an extended exposition of one IAM, the DICE/RICE family of models. The purpose of this description is to provide readers an example of how such a model is developed and what the major components are. The final section discusses major important open questions that continue to occupy IAM modelers. These involve issues such as the discount rate, uncertainty, the social cost of carbon, the potential for catastrophic climate change, algorithms, and fat-tailed distributions. These issues are ones that pose both deep intellectual challenges as well as important policy implications for climate change and climate-change policy

Economic Analysis of Knowledge: The History of Thought and the Central Themes

Following the development of knowledge economies, there has been a rapid expansion of economic analysis of knowledge, both in the context of technological knowledge in particular and the decision theory in general. This paper surveys this literature by identifying the main themes and contributions and outlines the future prospects of the discipline. The wide scope of knowledge related questions in terms of applicability and alternative approaches has led to the fragmentation of research. Nevertheless, one can identify a continuing tradition which analyses various aspects of the generation, dissemination and use of knowledge in the economy

The James Webb Space Telescope Mission

Twenty-six years ago a small committee report, building on earlier studies, expounded a compelling and poetic vision for the future of astronomy, calling for an infrared-optimized space telescope with an aperture of at least $4m$. With the support of their governments in the US, Europe, and Canada, 20,000 people realized that vision as the $6.5m$ James Webb Space Telescope. A generation of astronomers will celebrate their accomplishments for the life of the mission, potentially as long as 20 years, and beyond. This report and the scientific discoveries that follow are extended thank-you notes to the 20,000 team members. The telescope is working perfectly, with much better image quality than expected. In this and accompanying papers, we give a brief history, describe the observatory, outline its objectives and current observing program, and discuss the inventions and people who made it possible. We cite detailed reports on the design and the measured performance on orbit.Comment: Accepted by PASP for the special issue on The James Webb Space Telescope Overview, 29 pages, 4 figure

The Science Performance of JWST as Characterized in Commissioning

This paper characterizes the actual science performance of the James Webb Space Telescope (JWST), as determined from the six month commissioning period. We summarize the performance of the spacecraft, telescope, science instruments, and ground system, with an emphasis on differences from pre-launch expectations. Commissioning has made clear that JWST is fully capable of achieving the discoveries for which it was built. Moreover, almost across the board, the science performance of JWST is better than expected; in most cases, JWST will go deeper faster than expected. The telescope and instrument suite have demonstrated the sensitivity, stability, image quality, and spectral range that are necessary to transform our understanding of the cosmos through observations spanning from near-earth asteroids to the most distant galaxies.Comment: 5th version as accepted to PASP; 31 pages, 18 figures; https://iopscience.iop.org/article/10.1088/1538-3873/acb29

The Impact of Market Size and Users' Sophistication on Innovation: The Patterns of Demand and the Technology Life Cycle

The aim of this paper is an investigation on the role of demand in industrial dynamics. Despite the decades-long debate on demand and innovation, theory still lacks a comprehensive analytical formulation. This paper proposes a model where demand is conceived as a peculiar blend of two conditions, market size, and users sophistication. These conditions drive firms incentives to innovate. As main outcome, the paper proposes both a theoretical taxonomy of sectors and an original explanation of technological life cycle