5724720
Heterogeneous CAD Hybrid Data Exchange Based on Feature Semantics and Geometry Representation
Product data exchange (DE) is a key technology to implement collaborative design of heterogeneous CAD. Based on analyzing layered expression of product CAD model and current methods of DE, heterogeneous CAD hybrid data exchange (HDE) based on feature semantics and geometry representation is presented. The method integrates advantages of feature semantics exchange (FSE) and geometric data exchange (GDE). It features high flexibility and reliability. A case illustrates the validity of the method
30413553
Reverse innovative design - an integrated product design methodology
Today's product designer is being asked to develop high quality, innovative products at an ever increasing pace. To meet this need, an intensive search is underway for advanced design methodologies that facilitate the acquisition of design knowledge and creative ideas for later reuse. Additionally, designers are embracing a wide range of 3D digital design applications, such as 3D digitization, 3D CAD and CAID, reverse engineering (RE), CAE analysis and rapid prototyping (RP). In this paper, we propose a reverse engineering innovative design methodology called Reverse Innovative Design (RID). The RID methodology facilitates design and knowledge reuse by leveraging 3D digital design applications. The core of our RID methodology is the definition and construction of feature-based parametric solid models from scanned data. The solid model is constructed with feature data to allow for design modification and iteration. Such a construction is well suited for downstream analysis and rapid prototyping. In this paper, we will review the commercial availability and technological developments of some relevant 3D digital design applications. We will then introduce three RE modelling strategies: an autosurfacing strategy for organic shapes; a solid modelling strategy with feature recognition and surface fitting for analytical models; and a curve-based modelling strategy for accurate reverse modelling. Freeform shapes are appearing with more frequency in product development. Since their ''natural'' parameters are hard to define and extract, we propose construction of a feature skeleton based upon industrial or regional standards or by user interaction. Global and local product definition parameters are then linked to the feature skeleton. Design modification is performed by solving a constrained optimization problem. A RID platform has been developed and the main RE strategies and core algorithms have been integrated into SolidWorks as an add-in product called ScanTo3D. We will use this system to demonstrate our RID methodology on a collection of innovative consumer product design examples.
121925502
Similarity search over time series and trajectory data
Time series data have been used in many applications, such as financial data analysis and weather forecasting. Similarly, trajectories of moving objects are often used to perform movement pattern analysis in surveillance video and sensor monitoring systems. All these applications are closely related to similarity-based time series or trajectory data retrieval. 
In this dissertation, various similarity models are proposed to capture the similarities among time series and trajectory data under various circumstances and requirements, such as the appearance of noise and local time shifting. A novel representation, called multi-scale time series histograms , is proposed to answer pattern existence queries and shape match queries. Earlier proposals generally address one or the other; multi-scale time series histograms can answer both types, which offers users more flexibility. A metric distance function, called Edit distance with Real Penalty (ERP), is proposed that can support local time shifting in time series and trajectory data. A second distance function, Edit Distance on Real sequence (EDR) is proposed to measure the similarity between time series or trajectories with local time shifting and noise. 
Since the proposed similarity models are computationally expensive, several indexing and pruning methods are proposed to improve the retrieval efficiency. For multi-scale time series histograms, A multi-step filtering process is introduced to improve the retrieval efficiency without introducing false dismissals. For ERP, a framework is developed to index time series or trajectory data under a metric distance function, which exploits the pruning power of lower bounding and triangle inequality. For EDR, three pruning techniques—mean value Q-grams, near triangle inequality, and trajectory histograms—are developed to improve the retrieval efficiency.
262231
Monochromatic and bichromatic reverse skyline search over uncertain databases
Reverse skyline queries over uncertain databases have many important applications such as sensor data monitoring and business planning. Due to the existence of uncertainty in many real-world data, answering reverse skyline queries accurately and efficiently over uncertain data has become increasingly important. In this paper, we model the probabilistic reverse skyline query on uncertain data, in both monochromatic and bichromatic cases, and propose effective pruning methods to reduce the search space of query processing. Moreover, efficient query procedures have been presented seamlessly integrating the proposed pruning methods. Extensive experiments have demonstrated the efficiency and effectiveness of our proposed approach with various experimental settings.
24767232
The Research and Application of Human Detection Based on Support Vector Machine Using in Intelligent Video Surveillance System
This paper presented a special design and implementation of human detection based on SVM (support vector machine) and this method is used in intelligent video surveillance system. In order to simplify the design of the SVM classifier and improve efficiency of machine learning, both a grid vector representation and a center radiating vector representation are proposed to abstract features of the object. The sample data is obtained through processing and analysis including human and no-human which forms the training input to SVM. Finally, we used the trained recognizer to identify whether there is somebody broken into the object region. If there is, the automatic warning device gives the alarm, which guarantees a real-time surveillance.
38456559
Testing Technology of Torsional Vibration Spring Static Stiffness
The principle and method of testing static stiffness of torsional vibration spring are put forward based on the structure of dual-mass flywheel with torsional vibration spring, and the test bench is designed for these. The testing data is collected by using the PXI-6259 data collection card of National instrument and the data is processed by the LabVIEW software system. The elastic characteristic of the torsional vibration spring is obtained by analyzing the data.
28385041
A Modular System for the Classification of Time Series Data
While the field of classification is witnessing excellent achievement in recent years, not much attention is given to methods that deal with the time series data. In this paper, we propose a modular system for the classification of time series data. The proposed approach explores the diversity through various input representation techniques, each of which focuses on a certain aspect of the temporal patterns. The temporal patterns are identified by aggregation of the decisions of multiple classifiers trained through different representations of the input data. Several time series data sets are employed to examine the validity of the proposed approach. The results obtained from our experiments show that the performance of the proposed approach is effective as well as robust.