Surprises in a Growing Market Niche - An Evaluation of the German Private Annuities Market

High replacement rates from public old age insurance might lead to the belief that little room is left for private sector annuities in Germany. Taking a closer look, we find a small market with a surprisingly large variety of products. Due to the recent pension reform and future ones to come the market is projected to grow substantially in the upcoming years. This paper describes the available annuity contracts and determines their money’s worth for different subgroups of the population.

On the Stability of Community Detection Algorithms on Longitudinal Citation Data

There are fundamental differences between citation networks and other classes of graphs. In particular, given that citation networks are directed and acyclic, methods developed primarily for use with undirected social network data may face obstacles. This is particularly true for the dynamic development of community structure in citation networks. Namely, it is neither clear when it is appropriate to employ existing community detection approaches nor is it clear how to choose among existing approaches. Using simulated data, we attempt to clarify the conditions under which one should use existing methods and which of these algorithms is appropriate in a given context. We hope this paper will serve as both a useful guidepost and an encouragement to those interested in the development of more targeted approaches for use with longitudinal citation data.Comment: 17 pages, 7 figures, presenting at Applications of Social Network Analysis 2009, ETH Zurich Edit, August 17, 2009: updated abstract, figures, text clarification

A General Approach for Predicting the Behavior of the Supreme Court of the United States

Building on developments in machine learning and prior work in the science of judicial prediction, we construct a model designed to predict the behavior of the Supreme Court of the United States in a generalized, out-of-sample context. To do so, we develop a time evolving random forest classifier which leverages some unique feature engineering to predict more than 240,000 justice votes and 28,000 cases outcomes over nearly two centuries (1816-2015). Using only data available prior to decision, our model outperforms null (baseline) models at both the justice and case level under both parametric and non-parametric tests. Over nearly two centuries, we achieve 70.2% accuracy at the case outcome level and 71.9% at the justice vote level. More recently, over the past century, we outperform an in-sample optimized null model by nearly 5%. Our performance is consistent with, and improves on the general level of prediction demonstrated by prior work; however, our model is distinctive because it can be applied out-of-sample to the entire past and future of the Court, not a single term. Our results represent an important advance for the science of quantitative legal prediction and portend a range of other potential applications.Comment: version 2.02; 18 pages, 5 figures. This paper is related to but distinct from arXiv:1407.6333, and the results herein supersede arXiv:1407.6333. Source code available at https://github.com/mjbommar/scotus-predict-v

Computational Design of Upperstage Chamber, Aerospike, & Cooling Jacket for Dual-Expander Rocket Engine

To increase the performance of the current US satellite launch capability, new rocket designs must be undertaken. One concept that has been around since the 50s but yet to be utilized on a launch platform is the aerospike, or plug nozzle. The aerospike nozzle concept demonstrates globally better performance compared to a conventional bell nozzle, since the expansion of the jet is not bounded by a wall and therefore can adjust to the environment by changing the outer jet boundary. A dual-expander aerospike nozzle (DEAN) rocket concept would exceed the Integrated High Payoff Rocket Propulsion Technology initiative (IHPRPT) phase three goals. This document covers the design of the chamber and nozzle of the DEAN. The validation of the design of the DEAN are based on the model in Numerical Propulsion System Simulation (NPSS TM), added with the nozzle design from Two-Dimensional Kinematics (TDK 04TM). The result is a rocket engine that produces 57,231 lbf (254.5 kN) of thrust at an Isp of 472 s. Additionally, the oxygen wall is made of silicon carbide, with a melting point of 5580 R (3100 K), and has a maximum temperature at the throat of 1625 R (902 K). The hydrogen side is made of copper, with a melting point of 2444 R (1358 K), and has a maximum wall temperature of 1224 R (680 K) at the throat. Based on these result, future investigation into this design is merited since it has the potential to save $19 million in the cost to launch a satellite. NPSS proved to be a powerful tool in the development of rocket engines. TDK, however, was left wanting in the area of aerospike design

The role of task-appropriate processing, context, and attention allocation in prospective memory: a multinomial modeling approach

This study investigated the influences of attention and retrospective memory processes on prospective memory. In Experiment 1, participants who processed prospective memory cues under conditions that did not coincide with the processes required for making judgments in an ongoing task showed greater levels of performance at the expense of the attentional resources needed to complete the ongoing task. This differed compared to participants who processed cues under conditions that required the same processes needed to performance the ongoing task. In Experiment 2, the reinstatement of contextual features associated with prospective memory cues from the time of intention formation, or encoding, to the opportunity for retrieval resulted in greater levels of performance compared to a lack of contextual reinstatement of the cues. This difference in performance did not affect the attentional resources needed to perform the ongoing task between the two conditions. The data from both experiments were fit to a formal model as a means to address the contributions of attention and memory processes in performance, as well as to address the validity of the model in investigations of prospective memory. Finally, participants were administered a questionnaire meant to assess overall task impressions, and to address participants’ attention allocation policies given the requirements of the experiment

OPTIMIZATION OF LIGHT EXTRACTION FROM HIGH-VOLTAGE SIC PIN DIODE VIA PACKAGE DESIGN

This work demonstrates improved light extraction from a silicon carbide (SiC) PiN diode via package optimization. Previous research has shown that SiC power devices have low on-state voltage drop while maintaining a large breakdown voltage, making them desirable for high-power systems. SiC produces insufficient amounts of electroluminescence due to being an indirect bandgap semiconductor. Device packaging utilizing ray optics can maximize electroluminescent output. A packaging model is developed using computer aided design (CAD) software that supports light production and high-power operation with associated heat and electric potential constraints. The packaged SiC PiN diode is shown to have a light extraction improvement of 1740%. Methods of device production and follow-on testing are also discussed.Office of Naval Research, Arlington VA 22203Lieutenant, United States NavyApproved for public release. Distribution is unlimited