Strategies for collecting screen-less oscillation data

Screen-less oscillation photography is the method of choice for recording three-dimensional X-ray diffraction data for crystals of biological macromolecules. The geometry of an oscillation camera is extremely simple. However, the manner in which the reciprocal lattice is recorded in any experiment is fairly complex. This depends on the Laue symmetry of the reciprocal lattice, the lattice type, the orientation of the crystal on the camera and to a lesser extent on the unit-cell dimensions. Exploring the relative efficiency of collecting X-ray diffraction data for different crystal orientations prior to data collection might reduce the number of films required to record most of the unique data and the consequent amount of time required for processing these films. Here algorithms are presented suitable for this purpose and results are reported for the 11 Laue groups, different lattice types and crystal orientations often employed in data collection.

Apparent shortening of the Csp(3)-Csp(3) bond analysed via a variable-temperature X-ray diffraction study in racemic 1,1 '-binaphthalene-2,2 '-diyl diethyl bis(carbonate)

Crystal structure determination at room temperature [292 (2) K] of racemic 1,1'-binaphthalene-2,2'-diyl diethyl bis(carbonate), C26H22O6, showed that one of the terminal carbon-carbon bond lengths is very short [Csp(3)-Csp(3) = 1.327 (6) angstrom]. The reason for such a short bond length has been analysed by collecting data sets on the same crystal at 393, 150 and 90 K. The values of the corrected bond lengths clearly suggest that the shortening is mainly due to positional disorder at two sites, with minor perturbations arising as a result of thermal vibrations. The positional disorder has been resolved in the analysis of the 90 K data following the changes in the unit-cell parameters for the data sets at 150 and 90 K, which appear to be an artifact of a near centre of symmetry relationship between the two independent molecules in the space group P (1) over bar at these temperatures. Indeed, the unit cell at low temperature (150 and 90 K) is a supercell of the room-temperature unit cell.

A Convex Optimization Framework for Almost Budget Balanced Allocation of a Divisible Good

We address the problem of allocating a single divisible good to a number of agents. The agents have concave valuation functions parameterized by a scalar type. The agents report only the type. The goal is to find allocatively efficient, strategy proof, nearly budget balanced mechanisms within the Groves class. Near budget balance is attained by returning as much of the received payments as rebates to agents. Two performance criteria are of interest: the maximum ratio of budget surplus to efficient surplus, and the expected budget surplus, within the class of linear rebate functions. The goal is to minimize them. Assuming that the valuation functions are known, we show that both problems reduce to convex optimization problems, where the convex constraint sets are characterized by a continuum of half-plane constraints parameterized by the vector of reported types. We then propose a randomized relaxation of these problems by sampling constraints. The relaxed problem is a linear programming problem (LP). We then identify the number of samples needed for ``near-feasibility'' of the relaxed constraint set. Under some conditions on the valuation function, we show that value of the approximate LP is close to the optimal value. Simulation results show significant improvements of our proposed method over the Vickrey-Clarke-Groves (VCG) mechanism without rebates. In the special case of indivisible goods, the mechanisms in this paper fall back to those proposed by Moulin, by Guo and Conitzer, and by Gujar and Narahari, without any need for randomization. Extension of the proposed mechanisms to situations when the valuation functions are not known to the central planner are also discussed. Note to Practitioners-Our results will be useful in all resource allocation problems that involve gathering of information privately held by strategic users, where the utilities are any concave function of the allocations, and where the resource planner is not interested in maximizing revenue, but in efficient sharing of the resource. Such situations arise quite often in fair sharing of internet resources, fair sharing of funds across departments within the same parent organization, auctioning of public goods, etc. We study methods to achieve near budget balance by first collecting payments according to the celebrated VCG mechanism, and then returning as much of the collected money as rebates. Our focus on linear rebate functions allows for easy implementation. The resulting convex optimization problem is solved via relaxation to a randomized linear programming problem, for which several efficient solvers exist. This relaxation is enabled by constraint sampling. Keeping practitioners in mind, we identify the number of samples that assures a desired level of ``near-feasibility'' with the desired confidence level. Our methodology will occasionally require subsidy from outside the system. We however demonstrate via simulation that, if the mechanism is repeated several times over independent instances, then past surplus can support the subsidy requirements. We also extend our results to situations where the strategic users' utility functions are not known to the allocating entity, a common situation in the context of internet users and other problems.

Study of temperature distribution along an artificially polluted insulator string

Insulator becomes wet partially or completely, and the pollution layer on it becomes conductive, when collecting pollutants for an extended period during dew, light rain, mist, fog or snow melting. Heavy rain is a complicated factor that it may wash away the pollution layer without initiating other stages of breakdown or it may bridge the gaps between sheds to promote flashover. The insulator with a conducting pollution layer being energized, can cause a surface leakage current to flow (also temperature-rise). As the surface conductivity is non-uniform, the conducting pollution layer becomes broken by dry bands (at spots of high current density), interrupting the flow of leakage current. Voltage across insulator gets concentrated across dry bands, and causes high electric stress and breakdown (dry band arcing). If the resistance of the insulator surface is sufficiently low, the dry band arcs can be propagated to bridge the terminals causing flashover. The present paper concerns the evaluation of the temperature distribution along the surface of an energized artificially polluted insulator string.

Representation of evidence: An approach to uncertainty handling in knowledge-based systems

Many knowledge based systems (KBS) transform a situation information into an appropriate decision using an in built knowledge base. As the knowledge in real world situation is often uncertain, the degree of truth of a proposition provides a measure of uncertainty in the underlying knowledge. This uncertainty can be evaluated by collecting `evidence' about the truth or falsehood of the proposition from multiple sources. In this paper we propose a simple framework for representing uncertainty in using the notion of an evidence space.

Mining sentiments from songs using latent dirichlet allocation

Song-selection and mood are interdependent. If we capture a song’s sentiment, we can determine the mood of the listener, which can serve as a basis for recommendation systems. Songs are generally classified according to genres, which don’t entirely reflect sentiments. Thus, we require an unsupervised scheme to mine them. Sentiments are classified into either two (positive/negative) or multiple (happy/angry/sad/...) classes, depending on the application. We are interested in analyzing the feelings invoked by a song, involving multi-class sentiments. To mine the hidden sentimental structure behind a song, in terms of “topics”, we consider its lyrics and use Latent Dirichlet Allocation (LDA). Each song is a mixture of moods. Topics mined by LDA can represent moods. Thus we get a scheme of collecting similar-mood songs. For validation, we use a dataset of songs containing 6 moods annotated by users of a particular website.

Effects of two-wheelers on saturation flow at signalized intersections in developing countries

Two-wheelers (TW) constitute a major proportion of urban traffic in developing countries and therefore their effect on the saturation flow at signalized intersections could be substantial. This paper attempts to study and analyze the effect of two-wheelers on the saturation flow of signalized intersections by collecting data at a few signalized intersections in Bangalore, India. A strong correlation is observed between the measured saturation flow and the proportion of two-wheeler traffic, which suggest that two-wheelers have significant impact and should be considered in the capacity analysis of signalized intersections. In this paper, the effect of two-wheelers on saturation flow rate is incorporated in a previous model by calibrating and introducing a new adjustment factor for two-wheelers. Results show that saturation flow measured using the modified HCM equation is closer to observed saturation flow values.

Experimentally validated Raman Monte Carlo simulation for a cuboid object to obtain Raman spectroscopic signatures for hidden material

In conventional Raman spectroscopic measurements of liquids or surfaces the preferred geometry for detection of the Raman signal is the backscattering (or reflection) mode. For non-transparent layered materials, sub-surface Raman signals have been retrieved using spatially offset Raman spectroscopy (SORS), usually with light collection in the same plane as the point of excitation. However, as a result of multiple scattering in a turbid medium, Raman photons will be emitted in all directions. In this study, Monte Carlo simulations for a three-dimensional layered sample with finite geometry have been performed to confirm the detectability of Raman signals at all angles and at all sides of the object. We considered a non-transparent cuboid container (high density polyethylene) with explosive material (ammonium nitrate) inside. The simulation results were validated with experimental Raman intensities. Monte Carlo simulation results reveal that the ratio of sub-surface to surface signals improves at geometries other than backscattering. In addition, we demonstrate through simulations the effects of the absorption and scattering coefficients of the layers, and that of the diameter of the excitation beam. The advantage of collecting light from all possible 4 angles, over other collection modes, is that this technique is not geometry specific and molecular identification of layers underneath non-transparent surfaces can be obtained with minimal interference from the surface layer. To what extent all sides of the object will contribute to the total signal will depend on the absorption and scattering coefficients and the physical dimensions. Copyright (c) 2015 John Wiley & Sons, Ltd.

Optimum Parameter Selection in Sparse Reconstruction of Frequency-Domain Optical-Coherence Tomography Signals

For a multilayered specimen, the back-scattered signal in frequency-domain optical-coherence tomography (FDOCT) is expressible as a sum of cosines, each corresponding to a change of refractive index in the specimen. Each of the cosines represent a peak in the reconstructed tomogram. We consider a truncated cosine series representation of the signal, with the constraint that the coefficients in the basis expansion be sparse. An l(2) (sum of squared errors) data error is considered with an l(1) (summation of absolute values) constraint on the coefficients. The optimization problem is solved using Weiszfeld's iteratively reweighted least squares (IRLS) algorithm. On real FDOCT data, improved results are obtained over the standard reconstruction technique with lower levels of background measurement noise and artifacts due to a strong l(1) penalty. The previous sparse tomogram reconstruction techniques in the literature proposed collecting sparse samples, necessitating a change in the data capturing process conventionally used in FDOCT. The IRLS-based method proposed in this paper does not suffer from this drawback.

Activity Recognition in Egocentric Life-Logging Videos

With the increasing availability of wearable cameras, research on first-person view videos (egocentric videos) has received much attention recently. While some effort has been devoted to collecting various egocentric video datasets, there has not been a focused effort in assembling one that could capture the diversity and complexity of activities related to life-logging, which is expected to be an important application for egocentric videos. In this work, we first conduct a comprehensive survey of existing egocentric video datasets. We observe that existing datasets do not emphasize activities relevant to the life-logging scenario. We build an egocentric video dataset dubbed LENA (Life-logging EgoceNtric Activities) (http://people.sutd.edu.sg/similar to 1000892/dataset) which includes egocentric videos of 13 fine-grained activity categories, recorded under diverse situations and environments using the Google Glass. Activities in LENA can also be grouped into 5 top-level categories to meet various needs and multiple demands for activities analysis research. We evaluate state-of-the-art activity recognition using LENA in detail and also analyze the performance of popular descriptors in egocentric activity recognition.

Design and administration of activity-travel diaries: a case study from Bengaluru city in India

Studies on travel survey instrument design and administration in the context of Indian cities are limited despite the fact that these aspects of travel survey face unique challenges here when compared to the cities in the developed world. Here we report results of a pilot survey conducted for evaluating the performances, alternative diary formats and survey administration techniques in Bengaluru city, India. The study proposes two diary formats. `Diary-1' is in day-planner format and is a variant of the one reported earlier in the literature. `Diary-2' is derived as a combination of `Diary-1' and the trip-based diaries widely applied in Indian cities. `Face-to-face', and `drop-off and pick-up' methods of survey administration are considered for retrieving the activity-travel information of individuals. Evidence appears to be strong that diary-2 is preferable to diary-1 for collecting the travel details of individuals. The comparison of the retrieval methods suggests that the face-to-face method of instrument administration is superior to the drop-off and pick-up method in terms of higher response rates and minimum recording errors.