In connection with the DAML project for bringing about Semantic Web, an ontology of time is being developed describing temporal content Web pages and properties services. This covers topological instants intervals, measures duration, meanings clock calendar terms.

During the assembly of mechanical systems, dual-arm robot is always used for cabin docking. In order to ensure accuracy and reliability docking, a multi-objective trajectory planning method was proposed. A kinematic model constructed based on Denavit–Hartenberg (D-H) firstly. Then, in Cartesian space, end confirmed by fifth-order B-spline curve. On basis traditional cuckoo search algorithm, modified algorithm built using improved initial population generation step size. The total consumption...

In the information age, data is pervasive. some applications, explosion a significant phenomenon. The massive volume poses challenges to both human users and computers. this project, we propose new model for identifying representative set from large database. A special subset of original dataset, which has three main characteristics: It significantly smaller in size compared dataset. captures most dataset other subsets same size. low redundancy among representatives it contains. We use...

The Bare Bones Particle Swarm (BBPS) is evolved from the canonical Optimizer (PSO). velocity term of PSO removed in BBPS and replaced by Gaussian sampling strategy. There no parameter tuning it much easier to implement. In paper, proven that can be mathematically deduced a more general formula also presented. results presented paper represent initial an ongoing research project effort.

Background Intracranial aneurysm (IA) is a nodular protrusion of the arterial wall caused by localized abnormal enlargement lumen brain artery, which primary cause subarachnoid hemorrhage. Accurate rupture risk prediction can effectively aid treatment planning, but conventional estimation based on clinical information subjective and time-consuming. Methods We propose novel classification method CTA images for differentiating aneurysms that are prone to rupture. The main contribution this...

Sampling subnet is an important topic of complex network research. methods influence the structure and characteristics subnet. Random multiple snowball with Cohen (RMSC) process sampling which combines advantages random proposed in this paper. It has ability to explore global information discover local at same time. The experiments indicate that novel method could keep similarity between original on degree distribution, connectivity rate average shortest path. This applicable situation where...

The Histogram of Oriented Gradient (HOG) feature for pedestrian detection has achieved good results, but it is time-consuming. For resolving this problem, a modified method HOG proposed to reduce the dimension features. On base analyzing process HOG, nine independent channels (HOG-C) are extracted according gradient orientation interval. Through evaluating effectiveness HOG-C individually, combination (CHOG-C) presented based on statistical regularities. Comprehensive experiments INRIA...

We have constructed a corpus of news articles in which events are annotated for estimated bounds on their duration. Here we describe method measuring inter-annotator agreement these event duration distributions. then show that machine learning techniques applied to this data yield coarse-grained information, considerably outperforming baseline and approaching human performance.

This paper studies the problem difficulty for a popular optimization method - particle swarm (PSO), particularly PSO variant PSO-cf (PSO with constriction factor), and analyzes its predictive measures. Some previous measures related issues about other optimizers, mainly including deception modality, are checked PSO. It is observed that combination of three factors measure ratios attraction basins, relative distance attractors difference attractors' altitudes. Multimodality multi-funnel...

This article presents our work on constructing a corpus of news articles in which events are annotated for estimated bounds their duration, and automatically learning from this corpus. We describe the annotation guidelines, event classes we categorized to reduce gross discrepancies inter-annotator judgments, use normal distributions model vague implicit temporal information measure agreement these duration distributions. then show that machine techniques applied data can produce...

The decomposition-based multi-objective evolutionary algorithm (MOEA/D) has shown remarkable effectiveness in solving problems (MOPs). In this paper, we integrate the quantum-behaved particle swarm optimization (QPSO) with MOEA/D framework order to make QPSO be able solve MOPs effectively, advantage of being fully used. We also employ a diversity controlling mechanism avoid premature convergence especially at later stage search process, and thus further improve performance our proposed...

Aiming at the disadvantages of traditional manual docking, such as low assembly efficiency and large positioning error, a six-DOF dual-arm robot system for module docking is designed. Firstly, according to operation tasks cabin robot, its functional requirements key indicators are determined, overall scheme designed, composition working principle joints introduced in detail. Secondly, strength analysis core components carried out by finite element software ensure load capacity. Based on...

An unmanned aerial vehicle (UAV) assignment model requires allocating vehicles to targets perform various tasks. It is a complex problem with hard constraints, and potential dimensional explosion when the scenarios become more complicated size of problems increases. In this paper, new UAV proposed which reduces dimension solution space can be easily adapted by computational intelligence algorithms. local version particle swarm optimization (PSO) applied accomplish work. Numerical...

This paper presents an improved clustering algorithm for categorizing data with arbitrary shapes. Most of the conventional approaches work only round-shaped clusters. task can be accomplished by quickly searching and finding methods density peaks (DPC), but in some cases, it is limited allocation strategy. To overcome these limitations, two improvements are proposed this paper. describe center more comprehensively, definitions local relative distance fused multiple distances, including...