A Benchmark for Image Retrieval using Distributed Systems over the Internet: BIRDS-I

The performance of CBIR algorithms is usually measured on an isolated workstation. In a real-world environment the algorithms would only constitute a minor component among the many interacting components. The Internet dramati-cally changes many of the usual assumptions about measuring CBIR performance. Any CBIR benchmark should be designed from a networked systems standpoint. These benchmarks typically introduce communication overhead because the real systems they model are distributed applications. We present our implementation of a client/server benchmark called BIRDS-I to measure image retrieval performance over the Internet. It has been designed with the trend toward the use of small personalized wireless systems in mind. Web-based CBIR implies the use of heteroge-neous image sets, imposing certain constraints on how the images are organized and the type of performance metrics applicable. BIRDS-I only requires controlled human intervention for the compilation of the image collection and none for the generation of ground truth in the measurement of retrieval accuracy. Benchmark image collections need to be evolved incrementally toward the storage of millions of images and that scaleup can only be achieved through the use of computer-aided compilation. Finally, our scoring metric introduces a tightly optimized image-ranking window.Comment: 24 pages, To appear in the Proc. SPIE Internet Imaging Conference 200

Thermodynamic analysis of turbulent combustion in a spark ignition engine. Experimental evidence

A method independent of physical modeling assumptions is presented to analyze high speed flame photography and cylinder pressure measurements from a transparent piston spark ignition research engine. The method involves defining characteristic quantities of the phenomena of flame propagation and combustion, and estimating their values from the experimental information. Using only the pressure information, the mass fraction curves are examined. An empirical burning law is presented which simulates such curves. Statistical data for the characteristics delay and burning angles which show that cycle to cycle fractional variations are of the same order of magnitude for both angles are discussed. The enflamed and burnt mass fractions are compared as are the rates of entrainment and burning

Combustion and operating characteristics of spark-ignition engines

The spark-ignition engine turbulent flame propagation process was investigated. Then, using a spark-ignition engine cycle simulation and combustion model, the impact of turbocharging and heat transfer variations or engine power, efficiency, and NO sub x emissions was examined

Turbulent flame propagation and combustion in spark ignition engines

Pressure measurements synchronized with high-speed motion picture records of flame propagation have been made in a transparent piston engine. The data show that the initial expansion speed of the flame front is close to that of a laminar flame. As the flame expands, its speed rapidly accelerates to a quasi-steady value comparable with that of the turbulent velocity fluctuations in the unburned gas. During the quasi-steady propagation phase, a significant fraction of the gas behind the visible front is unburned. Final burnout of the charge may be approximated by an exponential decay in time. The data have been analyzed in a model independent way to obtain a set of empirical equations for calculating mass burning rates in spark ignition engines. The burning equations contain three parameters: the laminar burning speed s l, a characteristic speed u T, and a characteristic length l T. The laminar burning speed is known from laboratory measurements. Tentative correlations relating u T and l T to engine geometry and operating variables have been derived from the engine data. © 1983

The Invisible Power of Fairness. How Machine Learning Shapes Democracy

Many machine learning systems make extensive use of large amounts of data regarding human behaviors. Several researchers have found various discriminatory practices related to the use of human-related machine learning systems, for example in the field of criminal justice, credit scoring and advertising. Fair machine learning is therefore emerging as a new field of study to mitigate biases that are inadvertently incorporated into algorithms. Data scientists and computer engineers are making various efforts to provide definitions of fairness. In this paper, we provide an overview of the most widespread definitions of fairness in the field of machine learning, arguing that the ideas highlighting each formalization are closely related to different ideas of justice and to different interpretations of democracy embedded in our culture. This work intends to analyze the definitions of fairness that have been proposed to date to interpret the underlying criteria and to relate them to different ideas of democracy

Wehrl information entropy and phase distributions of Schrodinger cat and cat-like states

The Wehrl information entropy and its phase density, the so-called Wehrl phase distribution, are applied to describe Schr\"odinger cat and cat-like (kitten) states. The advantages of the Wehrl phase distribution over the Wehrl entropy in a description of the superposition principle are presented. The entropic measures are compared with a conventional phase distribution from the Husimi Q-function. Compact-form formulae for the entropic measures are found for superpositions of well-separated states. Examples of Schr\"odinger cats (including even, odd and Yurke-Stoler coherent states), as well as the cat-like states generated in Kerr medium are analyzed in detail. It is shown that, in contrast to the Wehrl entropy, the Wehrl phase distribution properly distinguishes between different superpositions of unequally-weighted states in respect to their number and phase-space configuration.Comment: 10 pages, 4 figure

The smallest refrigerators can reach maximal efficiency

We investigate whether size imposes a fundamental constraint on the efficiency of small thermal machines. We analyse in detail a model of a small self-contained refrigerator consisting of three qubits. We show analytically that this system can reach the Carnot efficiency, thus demonstrating that there exists no complementarity between size and efficiency.Comment: 9 pages, 1 figure. v2: published versio