6957023
PASE: A Prototype for Ad-hoc Process-Aware Information System Declaratively Constructing Environment
Traditional workflow management technology can deal with pre-defined business processes well. However, a practical ad-hoc process case in knowledge-intensive domain is often driven by not only process control, but also the real-time application data or user interactions. So the structure of those processes are hard to be completely fixed ahead. In addition, as the only basic element in traditional process, task, is often too coarse or too fine in real applications. Even though the process structure could be pre-defined completely, there is only a non-declarative way to build the process by traditional methods. To solve the above problems, we developed a declaratively constructing environment, named PASE. We propose a multi-layer model to percept ad-hoc process. And we adopt a transformation strategy to translate the model to process specifications based on logic reasoning and calculus. We also provide a graphical tool to help user construct information systems declaratively.
1170919
A Hybrid Method for Constructing Semi-structural Process in Knowledge-Intensive Information System
Recent research on processes in information system has revealed that processes in prevalent fields present to be semi-Structural. It seems to be structural at the process layer, but in the enacting time, executive situation might change due to various reasons. To solve that, in this paper, we illustrate how the flexibility of construction processes can be handled using a hybrid method. At structural layer, we construct the process in imperative way, whereas at the lower level, we decompose tasks into fine-grained operations, and declaratively perceive operation sequence. Moreover, we propose a prototype tool for constructing and enacting semi-Structural business processes.
17368152
WISE: A Prototype for Ontology Driven Development of Web Information Systems
The development of Web Information Systems(WIS) is a hot research topic both in industry and academia. This paper presents a platform for ontology driven WIS development: the Web Information System auto-construction Environment(WISE). The novel features of WISE are: 1) Employing WIS ontology to specify user requirements; 2) Providing graphical tools to support ontology construction; 3) Drawing user interfaces and generating source code automatically from WIS ontology.
2862393
Online Constrained Pattern Detection over Streams
Online pattern detection poses a challenge in many data-intensive applications, including network traffic management, trend analysis, intrusion detection, and various intelligent sensor networks. These applications have to be time and space efficient while providing high quality answers. Meanwhile, far less attention has been paid for detecting constrained patterns, that cannot be simply matched because there is no available pattern for prediction. This paper presents our research effort in efficient pattern detection with constraint. We propose a new method named Online Pattern Detection with Constraint (OPDC) to detect constrained patterns over evolving data stream, taking into account various user-defined constraints. To ensure that the constrained patterns are representative, we extend regular expression in a simple but powerful way. Our experimental results on real data sets demonstrate the feasibility and effectiveness of the proposed scheme.
119668212
Impulsive optimal control model for the trajectory of horizontal wells
This paper presents an impulsive optimal control model for solving the optimal designing problem of the trajectory of horizontal wells. We take fully into account the effect of unknown disturbances in drilling. The optimal control problem can be converted into a nonlinear parametric optimization by integrating the state equation. We discuss here that the locally optimal solution depends in a continuous way on the parameters (disturbances) and utilize this property to propose a revised Hooke-Jeeves algorithm. The uniform design technique is incorporated into the revised Hooke-Jeeves algorithm to handle the multimodal objective function. The numerical simulation is in accordance with theoretical results. The numerical results illustrate the validity of the model and efficiency of the algorithm.
17707568
Object Boundary Detection For Ontology-Based Image Classification
Technology in the field of digital media generates huge amounts of non-textual information, audio, video, and images, along with more familiar textual information. The potential for exchange and retrieval of information is vast and daunting. The key problem in achieving efficient and user-friendly retrieval in the domain of image is the development of a search mechanism to guarantee delivery of minimal irrelevant information (high precision) while insuring that relevant information is not overlooked (high recall). The traditional solution to the problem of image retrieval employs content-based search techniques based on color, histogram, texture or shape features. The traditional solution works well in performing searches in which the user specifies images containing a sample object, or a sample textural pattern, in which the object or pattern is indexed. One can overcome this restriction by indexing images according to meanings rather than objects that appear in images, although this will entail a way of converting objects to meanings. We have solved this problem of creating a meaning based index structure through the design and implementation of a concept-based model using domain dependent ontologies. An ontology is a collection of concepts and their interrelationships which provide an abstract view of an application domain. With regard to converting objects to meaning the key issue is to identify appropriate concepts that both describe and identify images. For this, first we need to identify all object boundaries accurately that appear in images. We propose an automatic scalable object boundary detection algorithm based on edge detection and region growing techniques. We also propose an efficient merging algorithm to join adjacent regions using an adjacency graph to avoid the over-segmentation of regions. To illustrate the effectiveness of our algorithm in automatic image classification we implement a very basic system aimed at the classification of images in the sports domain. By identifying objects in images, we show that our approach works well when objects in images have less complex organization.
14940474
The Representation of Chinese Semantic Knowledge and its Application in the Document Copy Detection
Digital documents are easily copied and distributed ille- gally. Document copy detection is a powerful tool to pro- tect the author's intellectual property and to improve the efficiency of information retrieval. It is difficult for the ex- isting copy detection systems to identify the sentence struc- ture changed copies. To address the problem, we research the semantic level of natural language processing and pro- pose a document copy detection method based on Chinese semantic knowledge. We introduce the realization mecha- nisms of Chinese language analysis, which contains syn- tactic parsing and semantic analyzing. We also report on the experimental comparison the proposed method with the representative document copy detection systems. The result is satisfying.
18111881
Worst-Case Response Time Analysis for OSEK/VDX Compliant Real-Time Distributed Control Systems
Temporal behaviors prediction is very critical for real-time control systems. This paper presents a method to analysis the worst-case response time of OSEK/VDX compliant hard real-time distributed control systems. OSEK/VDX is an industry standard for an open-ended architecture for distributed control units in vehicles. Traditional time analysis methods based on the fixed priority preemptive scheduling model do not account for the problems occur in practical systems. Based on the current time analysis technologies, we propose an accurate time analysis method considering the practical effects of resource access synchronization, mixed preemptive and non-preemptive scheduling, as well as the overheads of OSEK OS. Furthermore, we also propose a scheme to efficiently integrate time analysis tools into the current development process for electronic control units in vehicles.
11254057
Time multiplexed color image processing based on a CNN with cell-state outputs
A practical system approach for time-multiplexing cellular neural network (CNN) implementations suitable for processing large and complex images using small CNN arrays is presented. For real size applications, due to hardware limitations, it is impossible to have a one-on-one mapping between the CNN hardware cells and all the pixels in the image involved. This paper presents a practical solution by processing the input image, block by block, with the number of pixels in a block being the same as the number of CNN cells in the array. Furthermore, unlike other implementations in which the output is observed at the hard-limiting block, the very large scale integrated (VLSI) architecture hereby described monitors the outputs from the state node. While previous implementations are mostly suitable for black and white applications because of the thresholded outputs, our approach is especially suitable for applications in color (gray) image processing due to the analog nature of the state node. Experimental complementary metal-oxide-semiconductor (CMOS) chip results in good agreement with theoretical results are presented.