Enhanced Compressive Imaging Using Model-Based Acquisition: Smarter sampling by incorporating domain knowledge

2016 ◽  
Vol 33 (5) ◽  
pp. 81-94 ◽  
Author(s):  
Aswin C. Sankaranarayanan ◽  
Matthew A. Herman ◽  
Pavan Turaga ◽  
Kevin F. Kelly
2012 ◽  
Vol 155-156 ◽  
pp. 1175-1179
Author(s):  
Zhong Biao Sheng ◽  
Hua Ping Jia ◽  
Xiao Rong Tong

The features of vast distributed dynamic information on Web caused the problem of “overload” and “mislead” while query. Intelligent agent is a way to solve it. After considering the problems of users’ personal interests during the information retrieve adequately, the paper proposes an intelligent information retrieval model based-on Agent. This system integrated domain knowledge and used many arithmetic of learning user’s interest. Each Agent co-operates to finish information retrieval task, manifest the characteristics of intellectualization and individuality of in information retrieval. It is a good way to realize the highly effective intelligent retrieval system research.


2014 ◽  
Vol 496-500 ◽  
pp. 2295-2298
Author(s):  
Dong Juan Gu ◽  
Li Yong Wan

In order to meet the requirement better of heterogeneous information integration, this paper proposes a XML information integration model based on ontology technology. This model comes to share and reuse of structured knowledge, explicitness of domain knowledge. According to mapping method from ontology to XML schema, the model also comes to document query based on global semantic, solves the semantic heterogeneity of XML information integration. This paper gives a mapping algorithm to implement the validated verify of XML semantic information for automatic indexing information. Finally, this paper explained simply the query algorithm so that the users can conveniently the query of heterogeneous XML information.


2011 ◽  
pp. 23-38 ◽  
Author(s):  
Arnor Solberg ◽  
Jon Oldevik ◽  
Audun Jensvoll

How do you tailor a general-purpose system development methodology to appropriately fit the specific needs of your company and the actual domain or product-family you are working with? Moreover, how do you alter a general-purpose methodology to utilize the domain knowledge possessed by your company? This chapter describes a generic framework for tailoring general-purpose, model-based methodologies in order to deliver domain-specific models.


Author(s):  
Gerald Eaglin ◽  
Joshua Vaughan

Abstract While many model-based methods have been proposed for optimal control, it is often difficult to generate model-based optimal controllers for nonlinear systems. One model-free method to solve for optimal control policies is reinforcement learning. Reinforcement learning iteratively trains an agent to optimize a reward function. However, agents often perform poorly at the beginning of training and require a large number of trials to converge to a successful policy. A method is proposed to incorporate domain knowledge of dynamics and control into the controllers using reinforcement learning to reduce the training time needed. Simulations are presented to compare the performance of agents utilizing domain knowledge to those that do not use domain knowledge. The results show that the agents with domain knowledge can accomplish the desired task with less training time than those without domain knowledge.


2021 ◽  
Vol 552 ◽  
pp. 80-101
Author(s):  
Muhammad Irfan ◽  
Zheng Jiangbin ◽  
Muhammad Iqbal ◽  
Muhammad Hassan Arif

2020 ◽  
Vol 10 (20) ◽  
pp. 7311
Author(s):  
Xuequan Zhou ◽  
Gregory Zacharewicz ◽  
David Chen ◽  
Dianhui Chu

With the emergence and development of servitization, more and more enterprises are turning from product focus to service focus. Service is customer-oriented, and driven by customer requirements. Value is the goal pursued by all actors in the service. In order to analyze the mechanism of multi-actor collaborative value creation in the service process, this paper proposes a method for building a service process value model, based on process mining. Driven by the raw data and an event log of service activities and processes in the real world, stored in the service system, the method uses process mining techniques and combines domain knowledge to describe the construction steps of the service process value model at the conceptual level. We focus on the specific processes and activities in the service, and mainly consider the value creation of the activity. The model proposed in this paper aims, to reflect how service actors co-create value in the actual execution of service processes, and to help service actors achieve their value goals. We use a case study inspired by an industrial case to validate our idea. Moreover, we develop a new plug-in, based on the α-algorithm for ProM, to realize the model construction in the case study.


Sign in / Sign up

Export Citation Format

Share Document