augmented downhill simplex method (adsm) is introduced here, that is a heuristic combination of downhill simplex method (dsm) with random search algorithm. in fact, dsm is an interpretable nonlinear local optimization method. however, it is a local exploitation algorithm; so, it can be trapped in a local minimum. in contrast, random search is a global exploration, but less efficient. here, rand...

this study is investigated the optimum parameters for a tuned mass damper (tmd) under the seismic excitation. shuffled complex evolution (sce) is a meta-heuristic optimization method which is used to find the optimum damping and tuning frequency ratio for a tmd. the efficiency of the tmd is evaluated by decreasing the structural displacement dynamic magnification factor (ddmf) and acceleration ...

Chinese text segmentation is important in Chinese text indexing. Due to the lack of word delimiters in Chinese text, Chinese text segmentation is more difficult than English text segmentation. Besides, the segmentation ambiguities and the occurrences of out-of-vocabulary words (i.e. unknown words) are the major challenges in Chinese segmentation. Many research works dealing with the problem of ...

AIM This paper is intended to introduce Moustakas's heuristic method to a wider nursing research audience. It is aimed at identifying the main principles that underpin this approach, and outlining the processes and structure that this form of inquiry might take. BACKGROUND Heurism is a generic term that encapsulates a way of thinking and exploring that is shared by such diverse disciplines as...

Pedestrian detection is an important application in computer vision. Currently, most pedestrian detection methods focus on learning one or multiple fixed models. These algorithms rely heavily on training data and do not perform well in handling various pedestrian deformations. To address this problem, we analyze the cause of pedestrian deformation and propose a method to adaptively describe the...