Formation and evolution of disk galaxies

Global star formation is the key to understanding galaxy disk formation. This in turn depends on gravitational instability of disks and continuing gas accretion as well as minor merging. A key component is feedback from supernovae. Primary observational constraints on disk galaxy formation and evolution include the Schmidt-Kennicutt law, the Tully-Fisher relation and the galaxy luminosity function. I will review how theory confronts phenomenology, and discuss future prospects for refining our understanding of disk formation.Comment: to appear in The Galaxy Disk in Cosmological Context Proceedings IAU Symposium No. 254, 2008, J. Andersen, J. Bland-Hawthorn & B. Nordstrm, ed

Machine Prognosis with Full Utilization of Truncated Lifetime Data

Intelligent machine fault prognostics estimates how soon and likely a failure will occur with little human expert judgement. It minimizes production downtime, spares inventory and maintenance labour costs. Prognostic models, especially probabilistic methods, require numerous historical failure instances. In practice however, industrial and military communities would rarely allow their engineering assets to run to failure. It is only known that the machine component survived up to the time of repair or replacement but there is no information as to when the component would have failed if left undisturbed. Data of this sort are called truncated data. This paper proposes a novel model, the Intelligent Product Limit Estimator (iPLE), which utilizes truncated data to perform adaptive long-range prediction of a machine component's remaining lifetime. It takes advantage of statistical models' ability to provide useful representation of survival probabilities, and of neural networks ability to recognise nonlinear relationships between a machine component's future survival condition and a given series of prognostic data features. Progressive bearing degradation data were simulated and used to train and validate the proposed model. The results support our hypothesis that the iPLE can perform better than similar prognostics models that neglect truncated data

Adversarial Semantic Scene Completion from a Single Depth Image

We propose a method to reconstruct, complete and semantically label a 3D scene from a single input depth image. We improve the accuracy of the regressed semantic 3D maps by a novel architecture based on adversarial learning. In particular, we suggest using multiple adversarial loss terms that not only enforce realistic outputs with respect to the ground truth, but also an effective embedding of the internal features. This is done by correlating the latent features of the encoder working on partial 2.5D data with the latent features extracted from a variational 3D auto-encoder trained to reconstruct the complete semantic scene. In addition, differently from other approaches that operate entirely through 3D convolutions, at test time we retain the original 2.5D structure of the input during downsampling to improve the effectiveness of the internal representation of our model. We test our approach on the main benchmark datasets for semantic scene completion to qualitatively and quantitatively assess the effectiveness of our proposal.Comment: 2018 International Conference on 3D Vision (3DV

BCAS: A Web-enabled and GIS-based Decision Support System for the Diagnosis and Treatment of Breast Cancer

For decades, geographical variations in cancer rates have been observed but the precise determinants of such geographic differences in breast cancer development are unclear. Various statistical models have been proposed. Applications of these models, however, require that the data be assembled from a variety of sources, converted into the statistical models’ parameters and delivered effectively to researchers and policy makers. A web-enabled and GIS-based system can be developed to provide the needed functionality. This article overviews the conceptual web-enabled and GIS-based system (BCAS), illustrates the system’s use in diagnosing and treating breast cancer and examines the potential benefits and implications for breast cancer research and practice

A Balancing-Process Approach to Firm Internationalization

Drawing on the resource-based view of the firm, this paper develops a balancing-process approach to explain the motivations and location choices of foreign direct investment (FDI). In this approach, FDI is viewed as a means to balance a firm's portfolio of resources and capabilities through utilizing foreign strategic factor markets with the ultimate goal of achieving growth and sustainable competitive advantage. This approach joins exploitative and explorative FDI in a single framework and helps explain why a firm can conduct both types of FDI simultaneously.

Inertia in the North American Electricity Industry: Can the Kyoto Protocol Objectives Be Realistically Met?

If they are to be attained, the objectives set in the Kyoto Protocol will impose fundamental changes on the structure of North America's economy. This text highlights the extent of the Kyoto challenge by clearly describing the historical inertia in terms of total market shares for different production technologies of the North American electricity industry. It also compares two potential scenarios of the industry changes needed to attain the Kyoto objectives. The results obtained suggest that it will be virtually impossible to reach the Kyoto objectives within the electricity industry.Kyoto Protocol, Electricity Industry, Technological Change