This paper proposes an integrated approach to arrive at optimal build orientations, simultaneously minimizing surface roughness ’Ra’ and build time ’T ’, for object manufacturing in SLS process. The optimization task is carried out by two popularly known multi-objective evolutionary optimizers NSGA-II (non-dominated sorting genetic algorithm) and MOPSO (multi-objective particle swarm optimizer)...

In order to improve the internal structure of object-oriented software, refactoring has proved to be a feasible technique. Scheduling a refactoring process for a complex software system is a difficult task to do. Refactorings may be organized and prioritized based on goals established by the project management leadership, that shapes a refactoring strategy. The paper presents a multi-objective ...

This paper studies a resource allocation problem in a graph, concerning the joint optimization of capacity allocation decisions and object placement decisions, given a single capacity constraint. This problem has applications in internet content distribution and other domains. The solution to the problem comes through a multi-commodity generalization of the single commodity k-median problem. A ...

This paper introduces geometry and object shape and pose costs for multi-object tracking in urban driving scenarios. Using images from a monocular camera alone, we devise pairwise costs for object tracks, based on several 3D cues such as object pose, shape, and motion. The proposed costs are agnostic to the data association method and can be incorporated into any optimization framework to outpu...

because the underlying physiology of pathological tremor in a parkinson's patient is not well understood, the existing physical and drug therapies have not been successful in tremor treatment. different mathematical modeling of such vibration has been introduced to investigate the problem and reduce the existing vibration. most of the models have represented the induced vibration as a sinusoida...

The emergence of low-cost high-quality personal wearable cameras combined with the increasing storage capacity of video-sharing websites have evoked a growing interest in first-person videos, since most videos are composed of longrunning unedited streams which are usually tedious and unpleasant to watch. State-of-the-art semantic fast-forward methods currently face the challenge of providing an...

In this paper, we propose a novel approach for learning multi-label classifiers with the help of privileged information. Specifically, we use similarity constraints to capture the relationship between available information and privileged information, and use ranking constraints to capture the dependencies among multiple labels. By integrating similarity constraints and ranking constraints into ...