SPSA Based Feature Relevance Estimation For Video Retrieval

With the availability of a huge amount of video data on various sources, efficient video retrieval tools are increasingly in demand. Video being a multi-modal data, the perceptions of ``relevance'' between the user provided query video (in case of Query-By-Example type of video search) and retrieved video clips are subjective in nature. We present an efficient video retrieval method that takes user's feedback on the relevance of retrieved videos and iteratively reformulates the input query feature vectors (QFV) for improved video retrieval. The QFV reformulation is done by a simple, but powerful feature weight optimization method based on Simultaneous Perturbation Stochastic Approximation (SPSA) technique. A video retrieval system with video indexing, searching and relevance feedback (RF) phases is built for demonstrating the performance of the proposed method. The query and database videos are indexed using the conventional video features like color, texture, etc. However, we use the comprehensive and novel methods of feature representations, and a spatio-temporal distance measure to retrieve the top M videos that are similar to the query. In feedback phase, the user activated iterative on the previously retrieved videos is used to reformulate the QFV weights (measure of importance) that reflect the user's preference, automatically. It is our observation that a few iterations of such feedback are generally sufficient for retrieving the desired video clips. The novel application of SPSA based RF for user-oriented feature weights optimization makes the proposed method to be distinct from the existing ones. The experimental results show that the proposed RF based video retrieval exhibit good performance.

Learning Optimal Discriminant Functions through a Cooperative Game of Automata

The problem of learning correct decision rules to minimize the probability of misclassification is a long-standing problem of supervised learning in pattern recognition. The problem of learning such optimal discriminant functions is considered for the class of problems where the statistical properties of the pattern classes are completely unknown. The problem is posed as a game with common payoff played by a team of mutually cooperating learning automata. This essentially results in a probabilistic search through the space of classifiers. The approach is inherently capable of learning discriminant functions that are nonlinear in their parameters also. A learning algorithm is presented for the team and convergence is established. It is proved that the team can obtain the optimal classifier to an arbitrary approximation. Simulation results with a few examples are presented where the team learns the optimal classifier.

A cooperative game of a pair of learning automata

A cooperative game played in a sequential manner by a pair of learning automata is investigated in this paper. The automata operate in an unknown random environment which gives a common pay-off to the automata. Necessary and sufficient conditions on the functions in the reinforcement scheme are given for absolute monotonicity which enables the expected pay-off to be monotonically increasing in any arbitrary environment. As each participating automaton operates with no information regarding the other partner, the results of the paper are relevant to decentralized control.

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.

Surface treatments for pistons and their effect on engine performance

Surface treatment alters the frictional behaviour of pistons in I.C. engines and can be used to improve engine performance. Surface treatments applied to aluminium alloy pistons of a high speed diesel engine and their effect on the engine performance are described. Certain piston surface treatments improve engine performance and also reduce the run-in period.

Analysis and computation of the oil film thickness between the piston ring and cylinder liner of an internal combustion engine

A study of the essential features of piston rings in the cylinder liner of an internal combustion engine reveals that the lubrication problem posed by it is basically that of a slider bearing. According to steady-flow-hydrodynamics, viz. Image the oil film thickness becomes zero at the dead centre positions as the velocity, U = 0. In practice, however, such a phenomenon cannot be supported by consideration of the wear rates of pistion rings and cylinder liners. This can be explained by including the “squeeze” action term in the

Engine wear and used oil analysis - comparative study in high speed diesel engines

The operational life and reliability of I.C. engines are limited to a certain extent by the break down of the engine components due to wear. It is advantageous to know the condition of an engine and its components without disassembling for detailed measurements. This paper describes the possibility of employing chemical analysis of the used crank case oil to predict the wear of engine components. It is concluded that the acidity and carbon contents of the crank case oil play a significant role in assessing the wear of copper-lead bearings used for the big end of the connecting rod.

Engine wear and used oil analysis-A comparative study in high speed diesel engines

The operational life and reliability of I.C. engines are limited to a certain extent by the break down of the engine components due to wear. It is advantageous to know the condition of an engine and its components without disassembling for detailed measurements. This paper describes the possibility of employing chemical analysis of the used crank case oil to predict the wear of engine components. It is concluded that the acidity and carbon contents of the crank case oil play a significant role in assessing the wear of copper-lead bearings used for the big end of the connecting rod.

A method for the experimental evaluation of the acoustic characteristics of an engine exhaust system in the presence of mean flow

The paper deals with an exact analysis of standing waves in an impedance tube with mean flow. A method is offered for the experimental evaluation of the various wave parameters. Navier–Stokes equations have been solved for evaluating the volume velocity taking into account mean flow, viscosity, etc. The engine exhaust system has been characterized as an acoustic source with an acoustic pressure and internal impedance. A method is suggested for the evaluation of these hypothetical parameters using the exhaust pipe as an impedance tube.Subject Classification: [43]85.20; [43]20.40.

Nonlinear Control Design for an Air-breathing Engine with State Estimation

A nonlinear control design approach is presented in this paper for a challenging application problem of ensuring robust performance of an air-breathing engine operating at supersonic speed. The primary objective of control design is to ensure that the engine produces the required thrust that tracks the commanded thrust as closely as possible by appropriate regulation of the fuel flow rate. However, since the engine operates in the supersonic range, an important secondary objective is to ensure an optimal location of the shock in the intake for maximum pressure recovery with a sufficient margin. This is manipulated by varying the throat area of the nozzle. The nonlinear dynamic inversion technique has been successfully used to achieve both of the above objectives. In this problem, since the process is faster than the actuators, independent control designs have also been carried out for the actuators as well to assure the satisfactory performance of the system. Moreover, an extended Kalman Filter based state estimation design has been carried out both to filter out the process and sensor noises as well as to make the control design operate based on output feedback. Promising simulation results indicate that the proposed control design approach is quite successful in obtaining robust performance of the air-breathing system.

Running-in wear of a compression ignition engine: Factors influencing the conformance between cylinder liner and piston rings

The conformance between the liner and rings of an internal combustion engine depends mainly on their linear wear (dimensional loss) during running-in. Running-in wear studies, using the factorial design of experiments, on a compression ignition engine show that at certain dead centre locations of piston rings the linear wear of the cylinder liner increases with increase in the initial surface roughness of the liner. Rough surfaces wear rapidly without seizure during running-in to promote quick conformance, so an initial surface finish of the liner of 0.8 μm c.l.a. is recommended. The linear wear of the cast iron liner and rings decreases with increasing load but the mass wear increases with increasing load. This discrepancy is due to phase changes in the cast iron accompanied by dimensional growth at higher thermal loads. During running-in the growth of cast iron should be minimised by running the engine at an initial load for which the exhaust gas temperature is approximately 180 °C.

Location of Pathogenic Bacteria during Persistent Infections: Insights from an Analysis Using Game Theory

Bacterial persistent infections are responsible for a significant amount of the human morbidity and mortality. Unlike acute bacterial infections, it is very difficult to treat persistent bacterial infections (e.g. tuberculosis). Knowledge about the location of pathogenic bacteria during persistent infection will help to treat such conditions by designing novel drugs which can reach such locations. In this study, events of bacterial persistent infections were analyzed using game theory. A game was defined where the pathogen and the host are the two players with a conflict of interest. Criteria for the establishment of Nash equilibrium were calculated for this game. This theoretical model, which is very simple and heuristic, predicts that during persistent infections pathogenic bacteria stay in both intracellular and extracellular compartments of the host. The result of this study implies that a bacterium should be able to survive in both intracellular and extracellular compartments of the host in order to cause persistent infections. This explains why persistent infections are more often caused by intracellular pathogens like Mycobacterium and Salmonella. Moreover, this prediction is in consistence with the results of previous experimental studies.

Jet Engine Health Signal Denoising Using Optimally Weighted Recursive Median Filters

The removal of noise and outliers from health signals is an important problem in jet engine health monitoring. Typically, health signals are time series of damage indicators, which can be sensor measurements or features derived from such measurements. Sharp or sudden changes in health signals can represent abrupt faults and long term deterioration in the system is typical of gradual faults. Simple linear filters tend to smooth out the sharp trend shifts in jet engine signals and are also not good for outlier removal. We propose new optimally designed nonlinear weighted recursive median filters for noise removal from typical health signals of jet engines. Signals for abrupt and gradual faults and with transient data are considered. Numerical results are obtained for a jet engine and show that preprocessing of health signals using the proposed filter significantly removes Gaussian noise and outliers and could therefore greatly improve the accuracy of diagnostic systems. [DOI: 10.1115/1.3200907].

An adaptive decomposition method for video

Scalable video coding (SVC) is an emerging standard built on the success of advanced video coding standard (H.264/AVC) by the Joint video team (JVT). Motion compensated temporal filtering (MCTF) and Closed loop hierarchical B pictures (CHBP) are two important coding methods proposed during initial stages of standardization. Either of the coding methods, MCTF/CHBP performs better depending upon noise content and characteristics of the sequence. This work identifies other characteristics of the sequences for which performance of MCTF is superior to that of CHBP and presents a method to adaptively select either of MCTF and CHBP coding methods at the GOP level. This method, referred as "Adaptive Decomposition" is shown to provide better R-D performance than of that by using MCTF or CRBP only. Further this method is extended to non-scalable coders.

A cooperative game theoretic approach to prototype selection

In this paper we consider the task of prototype selection whose primary goal is to reduce the storage and computational requirements of the Nearest Neighbor classifier while achieving better classification accuracies. We propose a solution to the prototype selection problem using techniques from cooperative game theory and show its efficacy experimentally.