1 This paper demonstrates how appearance adaptive models can be employed for real-time object tracking using particle swarm optimization. The parallelization of the code is done using OpenMP directives and SSE instructions. The performance of our parallel algorithm was evaluated using multi-core CPUs. Experimental results show the performance of the algorithm in comparison to our GPU based impl...

objective(s):multi-epitopic protein vaccines and direction of vaccine delivery to dendritic cells (dcs) are promising approaches for enhancing immune responses against mutable pathogens. escherichia coli is current host for expression of recombinant proteins, and it is important to optimize expression condition. the aim of this study was the optimization of multi-epitopic hiv-1 tat/pol/gag/env ...

a multi-objective optimization procedure has been developed to determine some kinetic parameters of free radical polymerization of vinyl acetate based on genetic algorithm. for this purpose, mathematical modeling of free radical polymerization of vinyl acetate is carried out first and then selected kinetic parameters are optimized by minimizing objective functions defined from comparing experim...

pinch technology is one of the best methods for designing a multi stream heat exchanger(mshe) through a network; current pinch-based methods, however, lead to a larger and more complicateddesign problems. the major drawback of the current methods is they result in designs having more individual mshe sections than essential, correspond to the enthalpy intervals on temperature vs. enthalpy diagra...

Object tracking and localization is a complex task that typically requires processing power beyond the capabilities of low-power embedded cameras. This paper presents a new approach to real-time object tracking and localization using multi-view binary keypoints descriptor. The proposed approach offers a compromise between processing power, accuracy and networking bandwidth and has been tested u...

Multi-scenario optimization is a convenient way to formulate design optimization problems that are tolerant to disturbances and model uncertainties and/or need to operate under a variety of different conditions. Moreover, this problem class is often an essential tool to deal with semi-infinite problems. Here we adapt the IPOPT barrier nonlinear programming algorithm to provide efficient paralle...

This paper proposes a novel approach for the construction and use of multi-feature spaces in image classification. The proposed technique combines low-level descriptors and defines suitable metrics. It aims at representing and measuring similarity between semantically meaningful objects within the defined multi-feature space. The approach finds the best linear combination of predefined visual d...

We present the design of a global object space in a distributed Java Virtual Machine that supports parallel execution of a multi-threaded Java program on a cluster of computers. The global object space virtualizes a single Java object heap across machine boundaries to facilitate transparent object accesses. Based on the object connectivity information that is available at runtime, the object re...

Online multi-object tracking (MOT) is challenging: frame-by-frame matching of detection hypotheses to the correct trackers can be difficult. The Hungarian algorithm is the most commonly used online MOT data association method due to its rapid assignment; however, the Hungarian algorithm simply considers associations based on an affinity model. For crowded scenarios, frequently occurring interac...

Dominance-based Rough Set Approach (DRSA) has been proposed as an extension of the Pawlak’s concept of Rough Sets in order to deal with ordinal data [see [2, 3]]. Ordinal data are typically encountered in multi-attribute decision problems where a set of objects (also called actions, acts, solutions, etc.) evaluated by a set of attributes (also called criteria, variables, features, etc.) raises ...