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Data from multifactor HCI experiments often violates the normality assumption of parametric tests (i.e., nonconforming data). The Aligned Rank Transform (ART) is a popular nonparametric analysis technique that can find main and interaction effects in nonconforming data, but leads to incorrect results when used to conduct contrast tests. We created a new algorithm called ART-C for conducting contrasts within the ART paradigm and validated it on 72,000 data sets. Our results indicate that ART-C does not inflate Type I error rates, unlike contrasts based on ART, and that ART-C has more statistical power than a t-test, Mann-Whitney U test, Wilcoxon signed-rank test, and ART. We also extended a tool called ARTool with our ART-C algorithm for both Windows and R. Our validation had some limitations (e.g., only six distribution types, no mixed factorial designs, no random slopes), and data drawn from Cauchy distributions should not be analyzed with ART-C.

Among plausible causes for replicability failure, one that has not received sufficient attention is the environment in which the research is conducted. Consisting of the population, equipment, personnel, and various conditions such as location, time, and weather, the research environment can affect treatments and outcomes, and changes in the research environment that occur when an experiment is redone can affect replicability. We examine the extent to which such changes contribute to replicability failure. Our framework is that of an initial experiment that generates the data and a follow-up experiment that is done the same way except for a change in the research environment. We assume that the initial experiment satisfies the assumptions of the two-sample t-statistic and that the follow-up experiment is described by a mixed model which includes environmental parameters. We derive expressions for the effect that the research environment has on power, sample size selection, p-values, and confidence levels. We measure the size of the environmental effect with the environmental effect ratio EER which is the ratio of the standard deviations of environment by treatment interaction and error. By varying EER, it is possible to determine conditions that favor replicability and those that do not.

This article expands on research that has been done to develop a recurrent neural network (RNN) capable of predicting aircraft engine vibrations using long short-term memory (LSTM) neurons. LSTM RNNs can provide a more generalizable and robust method for prediction over analytical calculations of engine vibration, as analytical calculations must be solved iteratively based on specific empirical engine parameters, making this approach ungeneralizable across multiple engines. In initial work, multiple LSTM RNN architectures were proposed, evaluated and compared. This research improves the performance of the most effective LSTM network design proposed in the previous work by using a promising neuroevolution method based on ant colony optimization (ACO) to develop and enhance the LSTM cell structure of the network. A parallelized version of the ACO neuroevolution algorithm has been developed and the evolved LSTM RNNs were compared to the previously used fixed topology. The evolved networks were trained on a large database of flight data records obtained from an airline containing flights that suffered from excessive vibration. Results were obtained using MPI (Message Passing Interface) on a high performance computing (HPC) cluster, evolving 1000 different LSTM cell structures using 168 cores over 4 days. The new evolved LSTM cells showed an improvement of 1.35%, reducing prediction error from 5.51% to 4.17% when predicting excessive engine vibrations 10 seconds in the future, while at the same time dramatically reducing the number of weights from 21,170 to 11,810.

This document is a preliminary design of a High Speed Civil Transport (HSCT) named the RTJ-303. It is a 300 passenger, Mach 1.6 transport with a range of 5000 nautical miles. It features four mixed-flow turbofan engines, variable geometry oblique wing, with conventional tail-aft control surfaces. The preliminary cost analysis for a production of 300 aircraft shows that flyaway cost would be 183 million dollars (1992) per aircraft. The aircraft uses standard jet fuel and requires no special materials to handle aerodynamic heating in flight because the stagnation temperatures are approximately 130 degrees Fahrenheit in the supersonic cruise condition. It should be stressed that this aircraft could be built with today's technology and does not rely on vague and uncertain assumptions of technology advances. Included in this report are sections discussing the details of the preliminary design sequence including the mission to be performed, operational and performance constraints, the aircraft configuration and the tradeoffs of the final choice, wing design, a detailed fuselage design, empennage design, sizing of tail geometry, and selection of control surfaces, a discussion on propulsion system/inlet choice and their position on the aircraft, landing gear design including a look at tire selection, tip-over criterion, pavement loading, and retraction kinematics, structures design including load determination, and materials selection, aircraft performance, a look at stability and handling qualities, systems layout including location of key components, operations requirements maintenance characteristics, a preliminary cost analysis, and conclusions made regarding the design, and recommendations for further study.

This report discussed the following questions in regard to testing, measurement and evaluation in the Indiana public schools: (1) Where are we? (2) Is "where we are" different from where we perceive we should be? (3) Do teachers feel competent in testing? (4) How are teachers' skills viewed by their "superiors," the central office administrators? and (5) Where would educational assistance staff time and energy be best served? It is felt that the results of this data collection can be used to develop additional inservice thrusts, and also to identify preservice needs that can and should be met by faculty members in the various teacher-training colleges and universities within the state. Opinionnaires were mailed to approximately 1200 teachers, 900 principals, and 300 superintendents--with a return rate of 348, 418, and 164 respectively. Specific analyses of selected data are addressed in the following chapters of this monograph: (1) classroom testing, (2) standardized testing, (3) pupil test-taking skills and the testing environment, (4) the computer in testing, and (5) an administrator's self-appraisal. (PN)