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Invasive weed optimization (IWO) has been found to be a simple but powerful algorithm for function optimization over continuous spaces. It has reportedly outperformed many types of evolutionary algorithms and other search heuristics when tested over both benchmark and real-world problems. However the performance of most search heuristics deteriorates severely when applied to the task of optimization...
Segmentation, or partitioning images into internally homogeneous regions, is an important first step in many computer vision tasks. In this paper, we attack the segmentation problem using an ensemble of low cost image segmentations. These segmentations are reconciled by applying recent techniques from the consensus clustering literature which exploit a non-negative matrix factorization (NMF) framework...
Electrical systems throughout the world are experiencing problems with aging insulation. One of the major components, which degrade under stresses, is the paper insulation of a power transformer. In this research work, analysis of acoustic emission (AE) signal patterns due to the occurrence of partial discharge (PD) has been carried out. In order to characterize the different types of PD sources,...
Image registration is considered one of the most fundamental and crucial pre-processing tasks in digital imaging. This paper describes a fast multimodal automatic image registration algorithm that handles the alignment of IR and visible images. A multiresolution approach based on dual tree-complex wavelet transform is employed to speed up the process. At the coarsest level, an accurate registration...
This paper presents a bottom-up tracking algorithm for surveillance applications where speed and reliability in the case of multiple matches and occlusions are major concerns. The algorithm is divided into four steps. First, moving objects are detected using an accurate hybrid scheme with selective Gaussian modeling. Simple object features balancing speed, reliability, and complexity are then extracted...
We report synthesis of luminescent, spherical Si quantum dots by dry and wet etching of Si/SiO2 core/shell structures fabricated by oxidation of ball milled Si. The possible mechanism of photoluminescence is briefly discussed.
Identification of multiple simultaneously recorded neural spike train recordings is an important task in understanding neuronal dependency, functional connectivity, and temporal causality in neural systems. An assessment of the functional connectivity in a group of ensemble cells was performed using a regularized point process generalized linear model (GLM) that incorporates temporal smoothness or...
The scale and complexity of distributed systems have steadily grown in the recent years. Management of this complexity has drawn attention towards systems that can automatically maintain themselves throughout different scenarios. These systems have been described with many terms, such as self-healing, self-stabilizing, self-organizing, self-adaptive, self-optimizing, self-protecting, and self-managing...
Particle Swarm Optimization (PSO) is arguably one of the most popular nature- inspired algorithms for real parameter optimization at present. The existing theoretical research on PSO is mostly based on the gbest (global best) particle topology, which usually is susceptible to false or premature convergence over multi-modal fitness landscapes. The present standard PSO (SPSO 2007) uses an lbest (local...
Designing and building software that is free of defects that can be exploited by malicious adversaries is a difficult task. Despite extensive efforts via the application of formal methods, use of automated software engineering tools, and performing extensive pre-deployment testing, exploitable errors still appear in software. The problem of cyber resilience is further compounded by the growing sophistication...
Multiplication is at the core of many data processing tasks and saving power at the multiplication level can significantly impact the lifetime of a wireless sensor network. This paper introduces a novel light-weight low-power multiplication algorithm which is tailored for sensor nodes featuring low-end microcontrollers. These microcontrollers might have no hardware multiplier, or feature a fixed-point...
We suggest a unique and efficient system model for sensor networks to create sensor-smart highways. Our approach first considers various cell geometries encountered with two-dimensional roads, which are then extended to three- dimensional roads. The mathematical relations describing each type of cell are derived, and the analysis indicates the numbers and positions of sensor nodes needed in each cell...
The strategy of using an effective scheme to screen out a large number of stable contingencies and to apply detailed simulation programs only to potentially unstable contingencies is well recognized. This strategy is implemented in on-line voltage security assessment (VSA). This paper presents a hybrid of linear, quadratic and nonlinear methods for on-line VSA. Linear methods are fast but may not...
This paper discusses the CAISO experience of implementing automated Remedial Action Schemes in Energy Management Systems. Some details of the script language used for coding the algorithms are also discussed. These algorithms fall into the general class of condition-detection and action-initiation set of sequences. Remedial Action Schemes are typically applied to solve single and multiple contingency...
A robust Hinfin controller design in an LMI framework has been carried out for a load-frequency control problem of a single-area uncertain power system model. For carrying out this design, the uncertainties have been restructured by considering norm-bounded uncertainty instead of rank-1 uncertainty structure of . The proposed design is simple and can be easily solved to obtain optimal values of the...
The significance of beam's phase front in light localization in a disordered medium from application point of view is studied. The results show the advantage of plane phase front irrespective of the input beam profile.
The expectation maximization algorithm is a popular approach to learning Gaussian mixture models from unlabeled data. In addition to the unlabeled data, in many applications, additional sources of information such as a-priori knowledge of mixing proportions are also available. We present a weakly supervised approach, in the form of a penalized expectation maximization algorithm that uses a-priori...
There is a need for rigorous analysis techniques that developers can use to uncover security policy violations in their UML designs. There are a few UML analysis tools that can be used for this purpose, but they either rely on theorem-proving mechanisms that require sophisticated mathematical skill to use effectively, or they are based on model-checking techniques that require a ldquoclosed-worldrdquo...
Object detection is receiving a growing attention with the emergence of surveillance systems. This paper presents a hybrid adaptive scheme based on selective Gaussian modeling for detecting objects in complex outdoor scenes with gradual illumination changes and dense, moving background objects like swinging tree branches. The proposed technique combines simple frame difference (FD), simple adaptive...
This paper applies the differential evolution (DE) algorithm to the task of automatic fuzzy clustering in a Multi-objective optimization (MO) framework. It compares the performances of four recently developed multi-objective variants of DE over the fuzzy clustering problem, where two conflicting fuzzy validity indices are simultaneously optimized. The resultant Pareto optimal set of solutions from...
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