Naval Engineering and Labor Specialization during the Industrial Revolution

This paper explores the roles of capital- and technology-skill complementarities in labor allocation decisions within the U.S. Navy. During the latter 19th century the ocer corps was highly specialized, and was split between groups of line and sta ocers. This was also a time of dramatic technological changes which aected nearly every facet of naval opera- tions. Specically, naval technological developments tended to be \engineering-biased," in that they raised the relative importance of engineer-oriented skills. This created a dilemma for the Navy, as it navigated the balance between the benets of a specialized workforce implementing increasingly complex technologies with rising communication and coordina- tion costs. We rst document the extent of capital- and technology-skill complementarities within the navy which fostered greater labor specialization. We then show how the Navy vitiated the specialized human capital of ocers by blending the corps. The study oers in- sights into how an industry undergoing wrenching technological changes managed its labor and human capital allocation to help the U.S. become a world class naval power.

Small Satellite Industrial Base Study: Foundational Findings

This report documents findings from a Small Satellite (SmallSat) Industrial Base Study conducted by The Aerospace Corporation between November 2018 and September 2019. The primary objectives of this study were a) to gain a better understanding of the SmallSat communitys technical practices, engineering approaches, requirements flow-downs, and common processes and b) identify insights and recommendations for how the government can further capitalize on the strengths and capabilities of SmallSat offerings. In the context of this study, SmallSats are understood to weigh no more than 500 kg, as described in State of the Art Small Spacecraft Technology, NASA/TP-2018- 220027, December 2018. CubeSats were excluded from this study to avoid overlap and duplication of recently completed work or other studies already under way. The team also touched on differences between traditional space-grade and the emerging mid-grade and other non-space, alternate-grade EEEE (electrical, electronic, electromechanical, electro-optical) piece part categories. Finally, the participants sought to understand the potential effects of increased use of alternate-grade parts on the traditional space-grade industrial base. The study team was keenly aware that there are missions for which non-space grade parts currently are infeasible for the foreseeable future. National security, long-duration and high-reliability missions intolerant of risk are a few examples. The team sought to identify benefits of alternative parts and approaches that can be harnessed by the government to achieve greater efficiencies and capabilities without impacting mission success

Is there a trade-off between academic research and faculty entrepreneurship? Evidence from U.S. NIH supported biomedical researchers

Is there a trade-off of scholarly research productivity when faculty members found or join for-profit firms? This paper offers an empirical examination of this question for a subpopulation of biomedical academic scientists who received research funding from the U.S. National Institutes of Health (NIH). In this study, we are able to distinguish between permanent versus temporary employment transitions by entrepreneurial faculty members and examine how their journal article publication rates change using individual-level panel data. We find that the biomedical scientists who eventually choose to found or join a for-profit firm were more productive during their careers in academe than a randomly selected control group of their NIH peers. When they pursue entrepreneurship in the private sector, however, their scholarly productivity falls. Those entrepreneurial faculty members who return to academe are not as productive as they were before their entrepreneurial experience in terms of journal publications. --academic entrepreneurship,SBIR,NIH,biomedical research,life scientist productivity

Design considerations for space flight hardware

The environmental and design constraints are reviewed along with some insight into the established design and quality assurance practices that apply to low earth orbit (LEO) space flight hardware. It is intended as an introduction for people unfamiliar with space flight considerations. Some basic data and a bibliography are included

Pricing Derivatives Securities with Prior Information on Long- Memory Volatility

This paper investigates the existence of long memory in the volatility of the Mexican stock market. We use a stochastic volatility (SV) model to derive statistical test for changes in volatility. In this case, estimation is carried out through the Kalman filter (KF) and the improved quasi-maximum likelihood (IQML). We also test for both persistence and long memory by using a long-memory stochastic volatility (LMSV) model, constructed by including an autoregressive fractionally integrated moving average (ARFIMA) process in a stochastic volatility scheme. Under this framework, we work up maximum likelihood spectral estimators and bootstraped confidence intervals. In the light of the empirical findings, we develop a Bayesian model for pricing derivative securities with prior information on long-memory volatility.contingent pricing, econometric modeling

Optimisation of an acoustic resonator for particle manipulation in air

An acoustic resonator system has been investigated for the manipulation and entrapment of micron-sized particles in air. Careful consideration of the effect of the thickness and properties of the materials used in the design of the resonator was needed to ensure an optimised resonator. This was achieved using both analytical and finite-element modelling, as well as predictions of acoustic attenuation in air as a function of frequency over the 0.8 to 2.0 MHz frequency range. This resulted in a prediction of the likely operational frequency range to obtain particle manipulation. Experimental results are presented to demonstrate good capture of particles as small as 15 µm in diameter

Is there a trade-off between academic research and faculty entrepreneurship? : evidence from U.S. NIH supported biomedical researchers

Is there a trade-off of scholarly research productivity when faculty members found or join for-profit firms? This paper offers an empirical examination of this question for a subpopulation of biomedical academic scientists who received research funding from the U.S. National Institutes of Health (NIH). In this study, we are able to distinguish between permanent versus temporary employment transitions by entrepreneurial faculty members and examine how their journal article publication rates change using individual-level panel data. We find that the biomedical scientists who eventually choose to found or join a for-profit firm were more productive during their careers in academe than a randomly selected control group of their NIH peers. When they pursue entrepreneurship in the private sector, however, their scholarly productivity falls. Those entrepreneurial faculty members who return to academe are not as productive as they were before their entrepreneurial experience in terms of journal publications

Evaluating Drivers’ Understanding of Automotive Symbols Related to Powertrain and Advanced Driver Assistant Systems

The purpose of this research was to evaluate drivers’ understanding of automotive symbols meaning and what action to take in response to a symbol. With the dramatic increase in vehicle technology, the availability of a wide range of powertrain options, and the development of advanced driver assistant systems (ADAS), instrument cluster interfaces have become more complex, increasing the demand on drivers. Understanding the needs and preferences of a diverse group of drivers is essential for the development of digital instrument cluster interfaces that improve driver’s understanding of critical information about the vehicle. This research was divided in three studies. Study I evaluated teen drivers’, between 15 to 17 years of age, understanding of symbols from vehicles featuring advanced driving assistant systems and multiple powertrain configurations. The teenage driver population was selected for this study because in the U.S., the teenage driving population is at the highest risk of being involved in a crash. Teens often demonstrate poor vehicle control skills and poor ability to identify hazards, thus proper understanding of automotive indicators and warnings may be even more critical for this population. In addition, teen drivers are usually not represented in automotive symbol comprehension studies. In this research, teen drivers’ (N=72) understanding of automotive symbols was compared to three other groups with specialized driving experience and technical knowledge: automotive engineering graduate students (N=48), driver rehabilitation specialists (N=16), and performance driving instructors (N=15). Participants matched 42 symbols to their descriptions and then selected the five symbols they considered most important. Teen drivers demonstrated lower performance (Mean=29%) identifying symbols than the other three groups (Mean=60%). For all groups, responses on symbols related to basic vehicle functions and common to all powertrain types had significantly higher scores than symbols related to advanced driving assistant system (ADAS) functions or those that are powertrain specific. Overall, the five symbols selected by the participants as most important were related to powertrain and safety warnings. Study II investigated drivers’ understanding, and preferences related to powertrain and ADAS symbols presented on instrument clusters. Participants answered questions that evaluated nine symbol’s comprehension, familiarity, and helpfulness. Then, participants were presented with information from the owner’s manual for each symbol and responded if the information changed their understanding of the symbol. Lastly, participants rated their need for more information to understand the symbols and shared their preferences about how the automotive interface could help them better understand the symbols. Teen drivers (N=30), normal drivers (N=20), driving rehabilitation specialists (N=20), and automotive engineering students (N=48) participated in this study. When comparing the groups’ performance on the comprehension testing, driving rehabilitation specialists had the best performance. Teen drivers had the poorest performance. Symbols with an implied or arbitrary icon-function relationship demonstrated poorer comprehension for all participant groups. Symbols with a direct icon-function relationship received higher comprehension scores and helpfulness ratings independent of previous exposure. Symbols considered less helpful received higher ratings on the need for additional information, suggesting that drivers need additional information to understand the symbol when the symbol meaning is not clear. Automotive engineering students and normal drivers reported being considerably less satisfied with the information presented on the dashboard of their vehicles. Study III investigated drivers’ understanding of six automotive symbols presented on the instrument cluster or infotainment screen on a driving simulator study. Teens drivers between 15 to 17 years of age (N=24), adult drivers between 30 to 54 years (N=24), and senior drivers between 65 to 80 years of age participated in this study. The results of this driving simulator study suggest that presenting automotive symbols on in-vehicle displays with text description improved driver’s understanding of symbols meaning and what action to take in response to a symbol. Symbol type and previous experience with the symbol were contributing factors on symbol comprehension. Participants reported having higher previous experience with the powertrain symbols than the ADAS symbols and in general demonstrated significantly better understanding of symbols meaning and what action to take in response to powertrain symbols than ADAS symbols. Driving experience was not observed to be a contributing factor to correctly identifying a symbols’ meaning nor what action to take in response to the symbol in this study. Mixed evidence was observed on the negative impact of text descriptions on driving performance. Performance on the driving simulator and cognitive workload measures of mean and maximum index of cognitive activity (ICA) suggest that text descriptions did not negatively impact driving performance. On the other hand, eye glance off the road time, symbol reaction times, and the self-reported cognitive workload measures suggest that text descriptions negatively impact driving performance. Further research is needed to evaluate the impact of text descriptions on driving performance. In the end, participants demonstrated to prefer having more information about the symbols presented at the in-vehicle displays both when driving and while stopped. The inclusion of the teenage driver population under 18 years in future symbol comprehension testing studies and the exploration of alternative methods to communicate vehicle information to the driver should be considered by vehicle manufacturers. The results of this study may help automotive professionals when developing new vehicle interfaces to aid inexperienced and experienced drivers. The results of this study may help when developing new vehicle interfaces, ensuring that indicators and warnings are presented in a way that aid both inexperienced and experienced drivers. Overall, this study demonstrates that the evaluation of symbol’s comprehension and the comparison of alternative methods to communicate information on the in-vehicle displays greatly benefit from testing on a dynamic setting using a driving simulator versus a paper and pen survey. The dynamic setting allowed a comprehensive analysis of the effects of powertrain and ADAS warning symbols on driver’s understanding of the symbol, driving performance, and preference