A Shot boundary Detection Technique based on Visual Colour Information

The paper proposes a novel video segmentation system with maiden application of CIEDE2000 colour-difference and mean luminace pattern. CIEDE2000 colour-difference uses Lab colour space which is a stable and efficient colour space. The main advantage of Lab colour space model is that it can approximate all the available colours perceived by our human eye. CIEDE2000 colour difference is used for detecting abrupt transitions in the video. The novel contribution of the paper is the maiden use of the mean luminance pattern, increasing and decreasing patterns of the mean value of frame luminance, for detecting the gradual transition. The approach is validated on standard databases TRECVid 2001 and 2007 test video database. The performance of the proposed technique is compared with recently reported techniques and found to be superior as compared to other techniques. The accuracy achieved with the proposed method on the standard databases is 95.9% for cut transition, 78.6% for gradual transition and 92.1% overall.

     

Generalizing Multi-agent Graph Exploration Techniques

International Journal of Control, Automation and Systems - The system of multiple agents working in coordination for a given task has several advantages on faster completion, fault-tolerance, etc....     

Evolutionary programming techniques for economic load dispatch

Evolutionary programming has emerged as a useful optimization tool for handling nonlinear programming problems. Various modifications to the basic method have been proposed with a view to enhance speed and robustness and these have been applied successfully on some benchmark mathematical problems. But few applications have been reported on real-world problems such as economic load dispatch (ELD). The performance of evolutionary programs on ELD problems is examined and presented in this paper in two parts. In Part I, modifications to the basic technique are proposed, where adaptation is based on scaled cost. In Part II, evolutionary programs are developed with adaptation based on an empirical learning rate. Absolute, as well as relative, performance of the algorithms are investigated on ELD problems of different size and complexity having nonconvex cost curves where conventional gradient-based methods are inapplicable.     

Towards finding the best-fit distribution for OSN data

The Journal of Supercomputing - Currently, all online social networks (OSNs) are considered to follow a power-law distribution. In this paper, the degree distribution for multiple OSNs has been...     

Reliability-based multiobjective optimization for automotive crashworthiness and occupant safety

This paper presents a methodology for reliability-based multiobjective optimization of large-scale engineering systems. This methodology is applied to the vehicle crashworthiness design optimization for side impact, considering both structural crashworthiness and occupant safety, with structural weight and front door velocity under side impact as objectives. Uncertainty quantification is performed using two first order reliability method-based techniques: approximate moment approach and reliability index approach. Genetic algorithm-based multiobjective optimization software GDOT, developed in-house, is used to come up with an optimal pareto front in all cases. The technique employed in this study treats multiple objective functions separately without combining them in any form. It shows that the vehicle weight can be reduced significantly from the baseline design and at the same time reduce the door velocity. The obtained pareto front brings out useful inferences about optimal design regions. A decision-making criterion is subsequently invoked to select the “best” subset of solutions from the obtained nondominated pareto optimal solutions. The reliability, thus computed, is also checked with Monte Carlo simulations. The optimal solution indicated by knee point on the optimal pareto front is verified with LS-DYNA simulation results.     

Genetic neural-based modeling of AC resistance of heating coil used for high-frequency inverter-fed induction cooker

The present paper deals with modeling of AC resistance of twisted litz wires used for high-frequency inverter-fed induction cooker. Several traditional approaches are available, most of which have concentrated in deriving the analytical relationships between the AC resistances with the parameters of the wire. However, it is very difficult to get the exact relationship, due to several reasons. An attempt is made in this paper to model the AC resistance using a three-layered feed-forward Neural Network. For this purpose, four inputs (wire type, number of strand, number of spiral turn and operating frequency) and one output as AC resistance have been considered. Since the performance of Neural Network alone might not be optimal; it is optimized using a binary-coded Genetic Algorithm. Performances of the proposed approach were compared with the method of AC resistance computation proposed by Ferreira. Genetic-neural system has given a very close accuracy, and the computational complexity was found to be very low. Thus, it is suitable for online implementations.     

Assessment of relative impacts of various geo-mining factors on methane dispersion for safety in gassy underground coal mines: an artificial neural networks approach

Neural Computing and Applications - Dispersing methane to a safer level is crucial for mines safety as methane has been the greatest contributor of explosion hazard in underground coal mines...     

Robust stability of discrete-time systems

A new approach is proposed for determining the robust stability of discrete-time systems where each coefficient of the characteristic polynomial can take any value between specified lower and upper bounds. It is based on the use of Rouche's theorem in the theory of complex variables.     

The synthesis of pixelated metamaterial cross polarizer using binary wind driven optimization algorithm

Microsystem Technologies - In this paper synthesis of two wideband Metamaterial Cross Polarizer (MCPs) is proposed. The synthesis of proposed MCPs is done by using Binary Wind Driven Optimization...