An adaptable fuzzy-based model for predicting link quality in robot networks.

It is often essential for robots to maintain wireless connectivity with other systems so that commands, sensor data, and other situational information can be exchanged. Unfortunately, maintaining sufficient connection quality between these systems can be problematic. Robot mobility, combined with the attenuation and rapid dynamics associated with radio wave propagation, can cause frequent link quality (LQ) issues such as degraded throughput, temporary disconnects, or even link failure. In order to proactively mitigate such problems, robots must possess the capability, at the application layer, to gauge the quality of their wireless connections. However, many of the existing approaches lack adaptability or the framework necessary to rapidly build and sustain an accurate LQ prediction model. The primary contribution of this dissertation is the introduction of a novel way of blending machine learning with fuzzy logic so that an adaptable, yet intuitive LQ prediction model can be formed. Another significant contribution includes the evaluation of a unique active and incremental learning framework for quickly constructing and maintaining prediction models in robot networks with minimal sampling overhead

Effects of YouTube Video as Pre-Lecture Preparation

Classroom lectures convey course concepts more effectively when students have prepared in advance. Traditionally, students prepare for lectures by reading the course textbook. Textbooks are the default study material for most educational courses; however, some technical subjects are better conveyed in video format. Therefore, in this study, we encouraged students to supplement their learning resources with web-based video tutorials that provide detailed demonstrations with the respect to technical network configuration and management. YouTube is a video sharing website that can provide free educational tutorials and instructions on technical subject matter, where students can observe practical human-machine interaction to prepare for lectures and increase overall course performance on exams, assignments, and laboratory projects. Our goal was to compare the overall performance as well as the level of active class participation between two groups of the same computer networking course. We found that the group that used YouTube videos for pre-lecture preparation scored approximately 3% higher on exams but 5% lower on homework assignments than the control group (textbook only). There was no statistical significance between the two groups with respect to overall course grades. Study habits and degree of class participation of each student correlated more strongly with overall course performance than whether the student viewed the videos

Trusting AI: Integrating Artificial Intelligence into the Army’s Professional Expert Knowledge

Integrating artificially intelligent technologies for military purposes poses a special challenge. In previous arms races, such as the race to atomic bomb technology during World War II, expertise resided within the Department of Defense. But in the artificial intelligence (AI) arms race, expertise dwells mostly within industry and academia. Also, unlike the development of the bomb, effective employment of AI technology cannot be relegated to a few specialists; almost everyone will have to develop some level of AI and data literacy. Complicating matters is AI-driven systems can be a “black box” in that humans may not be able to explain some output, much less be held accountable for its consequences. This inability to explain coupled with the cession to a machine of some functions normally performed by humans risks the relinquishment of some jurisdiction and, consequently, autonomy to those outside the profession. Ceding jurisdiction could impact the American people’s trust in their military and, thus, its professional standing. To avoid these outcomes, creating and maintaining trust requires integrating knowledge of AI and data science into the military’s professional expertise. This knowledge covers both AI technology and how its use impacts command responsibility; talent management; governance; and the military’s relationship with the US government, the private sector, and society.https://press.armywarcollege.edu/monographs/1955/thumbnail.jp

Discovery of a Very Young Field L Dwarf, 2MASS J01415823-4633574

While following up L dwarf candidates selected photometrically from the Two Micron All Sky Survey, we uncovered an unusual object designated 2MASS J01415823-4633574. Its optical spectrum exhibits very strong bands of vanadium oxide but abnormally weak absorptions by titanium oxide, potassium, and sodium. Morphologically such spectroscopic characteristics fall intermediate between old, field early-L dwarfs (log(g)~5) and very late M giants (log(g)~0), leading us to favor low gravity as the explanation for the unique spectral signatures of this L dwarf. Such a low gravity can be explained only if this L dwarf is much lower in mass than a typical old field L dwarf of similar temperature and is still contracting to its final radius. These conditions imply a very young age. Further evidence of youth is found in the near-infrared spectrum, including a triangular-shaped H-band continuum reminiscent of young brown dwarf candidates discovered in the Orion Nebula Cluster. Using the above information along with comparisons to brown dwarf atmospheric and interior models, our current best estimate is that this L dwarf has an age of 1-50 Myr and a mass of 6-25 M_Jupiter. The location of 2MASS 0141-4633 on the sky coupled with a distance estimate of ~35 pc and the above age estimate suggests that this object may be a brown dwarf member of either the 30-Myr-old Tucana/Horologium Association or the ~12-Myr-old beta Pic Moving Group.Comment: Accepted for publication in the 10 March 2006 issue (volume 639) of the Astrophysical Journa

A Study of the Diverse T Dwarf Population Revealed by WISE

We report the discovery of 87 new T dwarfs uncovered with the Wide-field Infrared Survey Explorer (WISE) and 3 brown dwarfs with extremely red near-infrared colors that exhibit characteristics of both L and T dwarfs. Two of the new T dwarfs are likely binaries with L7 ± 1 primaries and mid-type T secondaries. In addition, our follow-up program has confirmed 10 previously identified T dwarfs and 4 photometrically selected L and T dwarf candidates in the literature. This sample, along with the previous WISE discoveries, triples the number of known brown dwarfs with spectral types later than T5. Using the WISE All-Sky Source Catalog we present updated color-color and color-type diagrams for all the WISE-discovered T and Y dwarfs. Near-infrared spectra of the new discoveries are presented along with spectral classifications. To accommodate later T dwarfs we have modified the integrated flux method of determining spectral indices to instead use the median flux. Furthermore, a newly defined J-narrow index differentiates the early-type Y dwarfs from late-type T dwarfs based on the J-band continuum slope. The K/J indices for this expanded sample show that 32% of late-type T dwarfs have suppressed K-band flux and are blue relative to the spectral standards, while only 11% are redder than the standards. Comparison of the Y/J and K/J index to models suggests diverse atmospheric conditions and supports the possible re-emergence of clouds after the L/T transition. We also discuss peculiar brown dwarfs and candidates that were found not to be substellar, including two young stellar objects and two active galactic nuclei. The substantial increase in the number of known late-type T dwarfs provides a population that will be used to test models of cold atmospheres and star formation. The coolest WISE-discovered brown dwarfs are the closest of their type and will remain the only sample of their kind for many years to come

A Sample of Very Young Field L Dwarfs and Implications for the Brown Dwarf "Lithium Test" at Early Ages

Using a large sample of optical spectra of late-type dwarfs, we identify a subset of late-M through L field dwarfs that, because of the presence of low-gravity features in their spectra, are believed to be unusually young. From a combined sample of 303 field L dwarfs, we find observationally that 7.6+/-1.6% are younger than 100 Myr. This percentage is in agreement with theoretical predictions once observing biases are taken into account. We find that these young L dwarfs tend to fall in the southern hemisphere (Dec < 0 deg) and may be previously unrecognized, low-mass members of nearby, young associations like Tucana-Horologium, TW Hydrae, beta Pictoris, and AB Doradus. We use a homogeneously observed sample of roughly one hundred and fifty 6300-10000 Angstrom spectra of L and T dwarfs taken with the Low-Resolution Imaging Spectrometer at the W. M. Keck Observatory to examine the strength of the 6708-A Li I line as a function of spectral type and further corroborate the trends noted by Kirkpatrick et al. (2000). We use our low-gravity spectra to investigate the strength of the Li I line as a function of age. The data weakly suggest that for early- to mid-L dwarfs the line strength reaches a maximum for a few 100 Myr, whereas for much older (few Gyr) and much younger (<100 Myr) L dwarfs the line is weaker or undetectable. We show that a weakening of lithium at lower gravities is predicted by model atmosphere calculations, an effect partially corroborated by existing observational data. Larger samples containing L dwarfs of well determined ages are needed to further test this empirically. If verified, this result would reinforce the caveat first cited in Kirkpatrick et al. (2006) that the lithium test should be used with caution when attempting to confirm the substellar nature of the youngest brown dwarfs.Comment: 73 pages with 22 figures; to appear in ApJ (Dec 20, 2008, v689n2 issue

A Study of the Diverse T Dwarf Population Revealed by WISE

We report the discovery of 87 new T dwarfs uncovered with the Wide-field Infrared Survey Explorer (WISE) and three brown dwarfs with extremely red near-infrared colors that exhibit characteristics of both L and T dwarfs. Two of the new T dwarfs are likely binaries with L7+/-1 primaries and mid-type T secondaries. In addition, our follow-up program has confirmed 10 previously identified T dwarfs and four photometrically-selected L and T dwarf candidates in the literature. This sample, along with the previous WISE discoveries, triples the number of known brown dwarfs with spectral types later than T5. Using the WISE All-Sky Source Catalog we present updated color-color and color-type diagrams for all the WISE-discovered T and Y dwarfs. Near-infrared spectra of the new discoveries are presented, along with spectral classifications. To accommodate later T dwarfs we have modified the integrated flux method of determining spectral indices to instead use the median flux. Furthermore, a newly defined J-narrow index differentiates the early-type Y dwarfs from late-type T dwarfs based on the J-band continuum slope. The K/J indices for this expanded sample show that 32% of late-type T dwarfs have suppressed K-band flux and are blue relative to the spectral standards, while only 11% are redder than the standards. Comparison of the Y/J and K/J index to models suggests diverse atmospheric conditions and supports the possible re-emergence of clouds after the L/T transition. We also discuss peculiar brown dwarfs and candidates that were found not to be substellar, including two Young Stellar Objects and two Active Galactic Nuclei. The coolest WISE-discovered brown dwarfs are the closest of their type and will remain the only sample of their kind for many years to come.Comment: Accepted to ApJS on 15 January 2013; 99 pages in preprint format, 30 figures, 12 table

Preliminary Trigonometric Parallaxes of 184 Late-T and Y Dwarfs and an Analysis of the Field Substellar Mass Function into the "Planetary" Mass Regime

We present preliminary trigonometric parallaxes of 184 late-T and Y dwarfs using observations from Spitzer (143), USNO (18), NTT (14), and UKIRT (9). To complete the 20-pc census of $\ge$T6 dwarfs, we combine these measurements with previously published trigonometric parallaxes for an additional 44 objects and spectrophotometric distance estimates for another 7. For these 235 objects, we estimate temperatures, sift into five 150K-wide $T_{\rm eff}$ bins covering the range 300-1050K, determine the completeness limit for each, and compute space densities. To anchor the high-mass end of the brown dwarf mass spectrum, we compile a list of early- to mid-L dwarfs within 20 pc. We run simulations using various functional forms of the mass function passed through two different sets of evolutionary code to compute predicted distributions in $T_{\rm eff}$. The best fit of these predictions to our L, T, and Y observations is a simple power-law model with $\alpha \approx 0.6$ (where $dN/dM \propto M^{-\alpha}$), meaning that the slope of the field substellar mass function is in rough agreement with that found for brown dwarfs in nearby star forming regions and young clusters. Furthermore, we find that published versions of the log-normal form do not predict the steady rise seen in the space densities from 1050K to 350K. We also find that the low-mass cutoff to formation, if one exists, is lower than $\sim$5 $M_{Jup}$, which corroborates findings in young, nearby moving groups and implies that extremely low-mass objects have been forming over the lifetime of the Milky Way.Comment: 86 pages with 19 figures. Accepted for publication in The Astrophysical Journal Supplement Series on 2018 Dec 0