Sixteen new IR laser dyes

Sixteen new IR laser dyes are reported. All lased successfully under excitation from a simple linear flashlamp of about 700-ns rise time. Untuned lasing wavelengths ranged from 810 to 972 nm. Laser output pulse energies from the four best of these dyes were 5-15 times greater than from diethylthiatricarbocyanine iodide (DTTC), with peak output of about 50 mJ obtained from 128-J excitation. Solvent effects with four selected laser dyes are also discussed.     

Personality differences between fee-paying and non-fee paying patients seen for psychological testing.

Administered the MMPI to 17 21-62 yr old male patients who did not pay their clinic bills and 17 patients who did pay their bills. MMPI and clinical data suggest greater reality disturbance and distortion for the non-fee paying group than for the fee-paying group, and that fee-payment behavior is situationally determined and not a generalized characteristic. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

New neural circuits for robot phonotaxis

W. Grey Walter built robotic systems to improve understanding of biological systems. In that tradition, this paper reports ongoing work on a robot model of cricket sound localization. The main advances are the inclusion of a much larger range of neuroethological detail, and the investigation of multimodal influences on the behaviour. The former allows exploration of the functionality of identified neurons in the insect, including the possible roles of multiple sensory fibres, mutually inhibitory connections, and brain neurons with pattern-filtering properties. The latter focuses on the inclusion of an optomotor stabilization response, and how this might improve tracking, particularly under conditions of random disturbance.     

High-precision fringe tracking invariant to systematic model errors

We present a new approach to processing of interferometric data, which dramatically improves operation on the smallest fraction of the fringe (approximately 1/1,000 of a wavelength and beyond). In particular, this approach, dubbed the variation-invariant subspace tracking approach (VISTA), makes it possible to operate a Michelson interferometer in a highly stable mode in which the estimation of optical path delay becomes invariant (insensitive) to a large class of systematic model errors. This previously unknown invariance property of interferometry follows from the fundamental odd-even symmetry of the channeled spectrum and its derivatives. VISTA offers a powerful algorithmic alternative for alleviating technological challenges in the design of high-precision long-baseline spaceborne interferometers.     

To Select or To Weigh: A Comparative Study of Linear Combination Schemes for SuperParent-One-Dependence Estimators

We conduct a large-scale comparative study on linearly combining superparent-one-dependence estimators (SPODEs), a popular family of seminaive Bayesian classifiers. Altogether, 16 model selection and weighing schemes, 58 benchmark data sets, and various statistical tests are employed. This paper's main contributions are threefold. First, it formally presents each scheme's definition, rationale, and time complexity and hence can serve as a comprehensive reference for researchers interested in ensemble learning. Second, it offers bias-variance analysis for each scheme's classification error performance. Third, it identifies effective schemes that meet various needs in practice. This leads to accurate and fast classification algorithms which have an immediate and significant impact on real-world applications. Another important feature of our study is using a variety of statistical tests to evaluate multiple learning methods across multiple data sets.     

设计：三星变革的催化剂

当设计团队从市场与工程部门完全独立,有了独立的话语权之后,三星公司才渐渐从市场上找到自己的定位。设计是成功的基石,对于中国企业而言,这或许是值得借鉴的方法。品牌知名度低,市场竞争激烈,或许是很多中国企业现在面临的发展困局。10年前,如今名满天下的三星也面临过同样的     

Surface Temperature Test Methods Per IEEE 1349

The fine print note (FPN) No. 1 in 2005 National Electrical Code (NEC) Article 501.8 (B) [ANSI/NFPA 70, National Electrical Code, 2005 (NEC)] cautions users to "consider the temperature of internal and external surfaces that may be exposed to the flammable atmosphere" when putting a motor into service in a Class I, Division 2 environment. Thus, it is critical that manufacturers and users of industrial electric motors understand that internal peak temperatures exceed the external peak temperatures. This paper presents three common IEEE 1349 [IEEE 1349-2001, IEEE Guide for the Application of Electric Motors in Class I, Division 2 Hazardous (Classified) Locations] test methods used by manufacturers to determine these internal peak temperatures. Potential test method error and the test results from the three test methods are also presented. IEEE 1349 provides only guidance when performing these test methods so this paper intends to provide additional clarification. The test motors presented in this paper are low voltage, ac induction, severe-duty, energy-efficient, totally enclosed fan-cooled motors commonly used in the "Petrochemical Industry."     

A stochastic approach to quantifying the blur with uncertainty estimation for high-energy X-ray imaging systems

One of the primary causes of blur in a high-energy X-ray imaging system is the shape and extent of the radiation source, or ‘spot’. It is important to be able to quantify the size of the spot as it provides a lower bound on the recoverable resolution for a radiograph, and penumbral imaging methods – which involve the analysis of blur caused by a structured aperture – can be used to obtain the spot’s spatial profile. We present a Bayesian approach for estimating the spot shape that, unlike variational methods, is robust to the initial choice of parameters. The posterior is obtained from a normal likelihood, which was constructed from a weighted least squares approximation to a Poisson noise model, and prior assumptions that enforce both smoothness and non-negativity constraints. A Markov chain Monte Carlo algorithm is used to obtain samples from the target posterior, and the reconstruction and uncertainty estimates are the computed mean and variance of the samples, respectively. Synthetic data-sets are used to demonstrate accurate reconstruction, while real data taken with high-energy X-ray imaging systems are used to demonstrate applicability and feasibility.     

A POPULATION MONTE CARLO METHOD FOR GENERATING RANDOM MATRICES WITH KNOWN CHARACTERISTICS

An algorithm which provides approximate solutions to a certain matrix inverse problem is presented. In this inverse problem, we usually assume that the distribution of a functional of a random matrix is known. For example, we may know the distribution of the determinant or trace of the matrix. The algorithm attempts to find the mean and covariance structure of a random Gaussian matrix which yields the correct distribution for the functional. The algorithm is based on population Monte Carlo (PMC). Density estimation and importance sampling are used to converge toward a Gaussian matrix solution space described by the means and covariances. We also apply the algorithm to a machine learning problem without a known distribution and show the algorithm can find solutions maximizing an objective function. Results of the algorithm can give insights into the nature of random matrices with certain properties and allow statistical machine learning to create hypotheses about matrix structures from limited measurements. Furthermore, there are applications in testing and communications theory.