Improved Algorithms for Reservoir Capacity Calculation Incorporating Storage-Dependent Losses and Reliability Norm

Two algorithms that improve upon the sequent-peak procedure for reservoir capacity calculation are presented. The first incorporates storage-dependent losses (like evaporation losses) exactly as the standard linear programming formulation does. The second extends the first so as to enable designing with less than maximum reliability even when allowable shortfall in any failure year is also specified. Together, the algorithms provide a more accurate, flexible and yet fast method of calculating the storage capacity requirement in preliminary screening and optimization models.

Cooking in the ungra area: Fuel efficiency, energy losses, and opportunities for reducing firewood consumption

Cooking efficiency and related fuel economy issues have been studied in a particular rural area of India. Following a description of the cooking practices and conditions in this locale, cooking efficiency is examined. A cooking efficiency of only 6% was found. The use of aluminium rather than clay pots results in an increased efficiency. In addition, cooking efficiency correlates very well with specific fuel consumption. The latter parameter is much simpler to analyse than cooking efficiency. The energy losses during cooking are examined in the second part of this case study. The major energy losses are heating of excess air, heat carried away by the combustion products, heat transmitted to the stove body and floor, and the chemical energy in charcoal residue. The energy loss due to the evaporation of cooking water is also significant because it represents about one-third of the heat reaching the pots.

Evaluation of Charges for Power Transmission and Losses in Bilateral Power Contracts

The paper presents a method for transmission loss charge allocation in deregulated power systems based on Relative Electrical Distance (RED) concept. Based on RED between the generator and load nodes and the predefined bilateral power contracts, charge evaluation is carried out. Generally through some power exchange mechanism a set of bilateral contracts are determined that facilitate bilateral agreements between the generation and distribution entities. In this paper the possible charges incurred in meeting loads like generation charge, transmission charge and charge due to losses are evaluated. Case studies have been carried out on a few practical equivalent systems. Due to space limitation results for a sample 5 bus system are presented considering ideal load/generation power contracts and deviated load/generation power contracts. Extensive numerical testing indicates that the proposed allocation scheme produces loss allocations that are appropriate and that behave in a physically reasonable manner.

Performance of an Al-Si-graphite particle composite piston in a diesel engine

Al-Si-graphite particle composite alloy pistons containing different percentages of about 80 μm uncoated graphite particles were successfully cast by foundry techniques. Tests with a 5 hp single-cylinder diesel engine show that Al-Si-graphite particle composite pistons can withstand an endurance test of 500 h without any apparent deterioration and do not seize during the running-in period. The use of the Al-Si-3% graphite particle composite piston also results in (a) up to 3% reduction in the specific fuel consumption, (b) considerable reduction in the wear of all four piston rings, (c) a reduction in piston wear, (d) a 9% reduction in the frictional horsepower losses of the engine as determined by the motoring test and (e) a slight increase in the exhaust gas temperature. These reductions (a)–(d) appear to be due to increased lubrication from the graphite particles which are smeared on the bearing surface, the higher damping capacity of the composite pistons and the reduced coefficient of thermal expansion of the composite pistons. Preliminary results indicate that aluminum-graphite particle composite alloy is a promising material for automotive pistons.

Energy losses at pipe trifurcations

In the case of pipe trifurcation, previous observations report negative energy losses in the centre branch. This causes an anomaly, because there should not be any negative energy loss due to conservation of energy principle. Earlier investigators have suggested that this may be due to the non-inclusion of kinetic energy coefficient (a) in the computations of energy losses without any experimental evidence. In the present work, through experimentally determined velocity profiles, energy loss coefficients have been evaluated. It has been found that with the inclusion of a in the computations of energy loss, there is no negative energy loss in the centre branch.

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.

Surface resistance and residual losses of Ag?doped YBa2Cu3O7?? thin films on sapphire

High?quality Ag?doped YBa2Cu3O7?? thin films have been grown by laser ablation on R?plane ?1102? sapphire without any buffer layer. Thin films have been found to be highly c?axis oriented with Tc=90 K, transition width ?T?1 K, and transport Jc=1.2×106 A?cm?2 at 77 K in self?field conditions. The microwave surface resistance of these films measured on patterned microstrip resonators has been found to be 530 ?? at 10 GHz at 77 K which is the lowest reported on unbuffered sapphire. Improved in?plane epitaxy and reduced reaction rate between the substrate and the film caused due to Ag in the film are believed to be responsible for this greatly improved microwave surface resistance. © 1995 American Institute of Physics.

Structured Learning for Non-Smooth Ranking losses

Learning to rank from relevance judgment is an active research area. Itemwise score regression, pairwise preference satisfaction, and listwise structured learning are the major techniques in use. Listwise structured learning has been applied recently to optimize important non-decomposable ranking criteria like AUC (area under ROC curve) and MAP(mean average precision). We propose new, almost-lineartime algorithms to optimize for two other criteria widely used to evaluate search systems: MRR (mean reciprocal rank) and NDCG (normalized discounted cumulative gain)in the max-margin structured learning framework. We also demonstrate that, for different ranking criteria, one may need to use different feature maps. Search applications should not be optimized in favor of a single criterion, because they need to cater to a variety of queries. E.g., MRR is best for navigational queries, while NDCG is best for informational queries. A key contribution of this paper is to fold multiple ranking loss functions into a multi-criteria max-margin optimization.The result is a single, robust ranking model that is close to the best accuracy of learners trained on individual criteria. In fact, experiments over the popular LETOR and TREC data sets show that, contrary to conventional wisdom, a test criterion is often not best served by training with the same individual criterion.

Evaluation of mechanical losses in a linear motor pressure wave generator

A moving magnet linear motor compressor or pressure wave generator (PWG) of 2 cc swept volume with dual opposed piston configuration has been developed to operate miniature pulse tube coolers. Prelimnary experiments yielded only a no-load cold end temperature of 180 K. Auxiliary tests and the interpretation of detailed modeling of a PWG suggest that much of the PV power has been lost in the form of blow-by at piston seals due to large and non-optimum clearance seal gap between piston and cylinder. The results of experimental parameters simulated using Sage provide the optimum seal gap value for maximizing the delivered PV power.

Sustainability of apparent slip in micro-channel flows

In the present work, we experimentally study the flow of water over textured hydrophobic surfaces in a micro-channel. Shear stress measurements are done along with direct visualization of trapped air pockets on the hydrophobic surface. The trapped air pockets on such surfaces are known to be responsible for apparent slip at these surfaces and hence in significant drag reduction. In typical circumstances, the apparent slip reduces over time as seen, for example, from our shear stress measurements. This implies that the drag reduction will not be sustained. We have performed extensive visualizations of the trapped air pockets while varying flow parameters like the flow rate and the pressure. We present here direct visualizations that show that under some conditions, the air pockets can grow with time. The variation of the air pocket size with time is found to change qualitatively and quantitatively as the flow rate is varied. These measured changes in the air pocket size with time have a direct bearing on the sustainability of apparent slip in micro-channel flows.

Classification calibration dimension for general multiclass losses

We study consistency properties of surrogate loss functions for general multiclass classification problems, defined by a general loss matrix. We extend the notion of classification calibration, which has been studied for binary and multiclass 0-1 classification problems (and for certain other specific learning problems), to the general multiclass setting, and derive necessary and sufficient conditions for a surrogate loss to be classification calibrated with respect to a loss matrix in this setting. We then introduce the notion of \emph{classification calibration dimension} of a multiclass loss matrix, which measures the smallest `size' of a prediction space for which it is possible to design a convex surrogate that is classification calibrated with respect to the loss matrix. We derive both upper and lower bounds on this quantity, and use these results to analyze various loss matrices. In particular, as one application, we provide a different route from the recent result of Duchi et al.\ (2010) for analyzing the difficulty of designing `low-dimensional' convex surrogates that are consistent with respect to pairwise subset ranking losses. We anticipate the classification calibration dimension may prove to be a useful tool in the study and design of surrogate losses for general multiclass learning problems.

Extension of TSVM to multi-class and hierarchical text classification problems With general losses

Transductive SVM (TSVM) is a well known semi-supervised large margin learning method for binary text classification. In this paper we extend this method to multi-class and hierarchical classification problems. We point out that the determination of labels of unlabeled examples with fixed classifier weights is a linear programming problem. We devise an efficient technique for solving it. The method is applicable to general loss functions. We demonstrate the value of the new method using large margin loss on a number of multi-class and hierarchical classification datasets. For maxent loss we show empirically that our method is better than expectation regularization/constraint and posterior regularization methods, and competitive with the version of entropy regularization method which uses label constraints.

Surrogate Regret Bounds for Bipartite Ranking via Strongly Proper Losses

The problem of bipartite ranking, where instances are labeled positive or negative and the goal is to learn a scoring function that minimizes the probability of mis-ranking a pair of positive and negative instances (or equivalently, that maximizes the area under the ROC curve), has been widely studied in recent years. A dominant theoretical and algorithmic framework for the problem has been to reduce bipartite ranking to pairwise classification; in particular, it is well known that the bipartite ranking regret can be formulated as a pairwise classification regret, which in turn can be upper bounded using usual regret bounds for classification problems. Recently, Kotlowski et al. (2011) showed regret bounds for bipartite ranking in terms of the regret associated with balanced versions of the standard (non-pairwise) logistic and exponential losses. In this paper, we show that such (non-pairwise) surrogate regret bounds for bipartite ranking can be obtained in terms of a broad class of proper (composite) losses that we term as strongly proper. Our proof technique is much simpler than that of Kotlowski et al. (2011), and relies on properties of proper (composite) losses as elucidated recently by Reid and Williamson (2010, 2011) and others. Our result yields explicit surrogate bounds (with no hidden balancing terms) in terms of a variety of strongly proper losses, including for example logistic, exponential, squared and squared hinge losses as special cases. An important consequence is that standard algorithms minimizing a (non-pairwise) strongly proper loss, such as logistic regression and boosting algorithms (assuming a universal function class and appropriate regularization), are in fact consistent for bipartite ranking; moreover, our results allow us to quantify the bipartite ranking regret in terms of the corresponding surrogate regret. We also obtain tighter surrogate bounds under certain low-noise conditions via a recent result of Clemencon and Robbiano (2011).