Learning to Generate Images with Perceptual Similarity Metrics

Deep networks are increasingly being applied to problems involving image synthesis, e.g., generating images from textual descriptions and reconstructing an input image from a compact representation. Supervised training of image-synthesis networks typically uses a pixel-wise loss (PL) to indicate the mismatch between a generated image and its corresponding target image. We propose instead to use a loss function that is better calibrated to human perceptual judgments of image quality: the multiscale structural-similarity score (MS-SSIM). Because MS-SSIM is differentiable, it is easily incorporated into gradient-descent learning. We compare the consequences of using MS-SSIM versus PL loss on training deterministic and stochastic autoencoders. For three different architectures, we collected human judgments of the quality of image reconstructions. Observers reliably prefer images synthesized by MS-SSIM-optimized models over those synthesized by PL-optimized models, for two distinct PL measures ($\ell_1$ and $\ell_2$ distances). We also explore the effect of training objective on image encoding and analyze conditions under which perceptually-optimized representations yield better performance on image classification. Finally, we demonstrate the superiority of perceptually-optimized networks for super-resolution imaging. Just as computer vision has advanced through the use of convolutional architectures that mimic the structure of the mammalian visual system, we argue that significant additional advances can be made in modeling images through the use of training objectives that are well aligned to characteristics of human perception

Об изучении иностранными студентами-медиками лексической синонимии в процессе усвоения языка специальности

This paper considers design issues for microvalves for large gas flow control. It introduces out-of-plane knife-gate microvalves as a novel design concept and a proportional microvalve concept for pressure control applications. The design of three different actuator-gate configurations and first prototypes are presented. The first valve prototypes feature thermal silicon-aluminum bimorph actuators and the pressure-flow performance per chip area of the demonstrator valve presented is greatly increased using out-of-plane actuation and an out-of-plane orifice. The characterization of the actuators and of the pressure-flow performance is presented. The prototype valve allows for a flow change of Delta Q = 3.4 standard liters per minute (SLPM) at a pressure change of Delta P = 95 kPa (P-in = 196.3 kPa, P-out = 101.3 kPa) on an active chip area of only 2.3 x 3.7 mm(2).QC20100727</p

HST Observations of the Host Galaxies of BL Lacertae Objects

Six BL Lac objects from the complete 1 Jy radio-selected sample of 34 objects were observed in Cycle 5 with the HST WFPC2 camera to an equivalent limiting flux of mu_I~26 mag/arcsec^2. Here we report results for the second half of this sample, as well as new results for the first three objects, discussed previously by Falomo et al. (1997). In addition, we have analyzed in the same way HST images of three X-ray-selected BL Lacs observed by Jannuzi et al. (1997). The ensemble of 9 BL Lac objects spans the redshift range from z=0.19 to ~1. Host galaxies are clearly detected in seven cases, while the other two, at z~0.258 (redshift highly uncertain) and z=0.997, are not resolved. The HST images constitute a homogeneous data set with unprecedented morphological information between a few tenths of an arcsecond and several arcseconds from the nucleus, allowing us in 6 of the 7 detected host galaxies to rule out definitively a pure disk light profile. The host galaxies are luminous ellipticals with an average absolute magnitude of M_I~-24.6 mag (with dispersion 0.7 mag), more than a magnitude brighter than L* and comparable to brightest cluster galaxies. The morphologies are generally smooth and have small ellipticities (epsilon<0.2). Given such roundness, there is no obvious alignment with the more linear radio structures. In the six cases for which we have HST WFPC2 images in two filters, the derived color profiles show no strong spatial gradients and are as expected for K-corrected passively evolving elliptical galaxies. The host galaxies of the radio-selected and X-ray-selected BL Lacs for this very limited sample are comparable in both morphology and luminosity.Comment: 23 pages, including 6 postscript figures and 3 tables (embedded). Latex requires aaspp4.sty and psfig.sty (not included). Accepted for publication in the Astrophysical Journa

Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment

Automated data-driven decision making systems are increasingly being used to assist, or even replace humans in many settings. These systems function by learning from historical decisions, often taken by humans. In order to maximize the utility of these systems (or, classifiers), their training involves minimizing the errors (or, misclassifications) over the given historical data. However, it is quite possible that the optimally trained classifier makes decisions for people belonging to different social groups with different misclassification rates (e.g., misclassification rates for females are higher than for males), thereby placing these groups at an unfair disadvantage. To account for and avoid such unfairness, in this paper, we introduce a new notion of unfairness, disparate mistreatment, which is defined in terms of misclassification rates. We then propose intuitive measures of disparate mistreatment for decision boundary-based classifiers, which can be easily incorporated into their formulation as convex-concave constraints. Experiments on synthetic as well as real world datasets show that our methodology is effective at avoiding disparate mistreatment, often at a small cost in terms of accuracy.Comment: To appear in Proceedings of the 26th International World Wide Web Conference (WWW), 2017. Code available at: https://github.com/mbilalzafar/fair-classificatio

Forecasting Player Behavioral Data and Simulating in-Game Events

Understanding player behavior is fundamental in game data science. Video games evolve as players interact with the game, so being able to foresee player experience would help to ensure a successful game development. In particular, game developers need to evaluate beforehand the impact of in-game events. Simulation optimization of these events is crucial to increase player engagement and maximize monetization. We present an experimental analysis of several methods to forecast game-related variables, with two main aims: to obtain accurate predictions of in-app purchases and playtime in an operational production environment, and to perform simulations of in-game events in order to maximize sales and playtime. Our ultimate purpose is to take a step towards the data-driven development of games. The results suggest that, even though the performance of traditional approaches such as ARIMA is still better, the outcomes of state-of-the-art techniques like deep learning are promising. Deep learning comes up as a well-suited general model that could be used to forecast a variety of time series with different dynamic behaviors

Лекарственное обеспечение медицинских учреждений и населения Россонского района Витебской области в период национализации аптек и новой экономической политики (1918-1929 гг.)

АПТЕКИИСТОРИЯ МЕДИЦИНЫЛЕКАРСТВЕННОГО ОБЕСПЕЧЕНИЯ СИСТЕМЫФАРМАЦИ

A Phenomenological Study of Perceptions of Self-Efficacy and Belongingness in Transfer Students with Disabilities after an Individualized Orientation at a Public University

This research explored the self-efficacy and sense of belonging in transfer students with disabilities after an individualized, one-on-one orientation with the Port City University’s Office of Student Disability Services. This study employed a qualitative approach, specifically phenomenology, to collect data. The researcher obtained data through semi-structured interviews using a purposeful sample of transfer students with disabilities registered with the Office of Student Disability Services. Seven participants submitted responses concerning their experience with the individualized orientation as related to their perception of self-efficacy and belongingness. Moreover, data underwent an interpretative phenomenological analysis. The study investigator reduced interview transcripts into themes, highlighting the individualized orientation essence. The findings from the research show that the factors related to the individualized orientation with the most influence on participants’ self-efficacy and belongingness were preparation for success, support of accommodations, virtual meeting options, tailored approaches, and knowledgeable and engaging disability services providers. The findings, considerations for future research, and limitations were discussed

A 180 Kpc Tidal Tail in the Luminous Infrared Merger Arp 299

We present VLA HI observations and UH88 deep optical B- and R-band observations of the IR luminous merger Arp 299 (= NGC 3690 + IC 694). These data reveal a gas-rich, optically faint tidal tail with a length of over 180 kpc. The size of this tidal feature necessitates an old interaction age for the merger (~750 Myr since first periapse), which is currently experiencing a very young star burst (~20 Myr). The observations reveal a most remarkable structure within the tidal tail: it appears to be composed of two parallel filaments separated by ~20 kpc. One of the filaments is gas rich with little if any starlight, while the other is gas poor. We believe that this bifurcation results from a warped disk in one of the progenitors. The quantities and kinematics of the tidal HI suggest that Arp 299 results from the collision of a retrograde Sab-Sb galaxy (IC 694) and a prograde Sbc-Sc galaxy (NGC 3690) that occurred 750 Myr ago and which will merge into a single object in ~60 Myr. We suggest that the present IR luminous phase in this system is due in part to the retrograde spin of IC 694. Finally, we discuss the apparent lack of tidal dwarf galaxies within the tail.Comment: LaTex, 14 pages, 11 figures, 4 tables, uses emulateapj.sty. Accepted to AJ for July 1999. For version with full-resolution images see http://www.cv.nrao.edu/~jhibbard/a299/HIpaper/a299HI.htm

Motivational engagement in first-time hearing aid users: a feasibility study

Objective: To assess (1) the feasibility of incorporating the Ida Institute’s Motivation Tools into a UK audiology service, (2) the potential benefits of motivational engagement in first-time hearing aid users, and (3) predictors of hearing aid and general health outcome measures. Design: A feasibility study using a single-centre, prospective, quasi-randomized controlled design with two arms. The Ida Institute’s Motivation Tools formed the basis for motivational engagement. Study sample: First-time hearing aid users were recruited at the initial hearing assessment appointment. The intervention arm underwent motivational engagement (M+, n = 32), and a control arm (M-, n = 36) received standard care only. Results: The M+ group showed greater self-efficacy, reduced anxiety, and greater engagement with the audiologist at assessment and fitting appointments. However, there were no significant between-group differences 10-weeks post-fitting. Hearing-related communication scores predicted anxiety, and social isolation scores predicted depression for the M+ group. Readiness to address hearing difficulties predicted hearing aid outcomes for the M- group. Hearing sensitivity was not a predictor of outcomes. Conclusions: There were some positive results from motivational engagement early in the patient journey. Future research should consider using qualitative methods to explore whether there are longer-term benefits of motivational engagement in hearing aid users