In this paper, we present a memory management system that reflects user behavior and preference. A user can run multiple applications at the same time even if the capacity of physical memory is not enough. The operati...
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In this paper, we present a memory management system that reflects user behavior and preference. A user can run multiple applications at the same time even if the capacity of physical memory is not enough. The operating system supports virtual memory in order to supply larger memory space, however low performance can be observed in some cases. For example, a user runs multiple applications and wants to reuse one application, which has not been used for a while. As the application is already stored in virtual memory, it takes a long time for the user to be able to reuse it. To solve this problem, the system needs to know what applications are frequently used by the user and which application is more important than others for the user. The memory management system suggested in this paper enables to record the user behavior and assumes user preference in applications. The effects of our system on the performance in application execution are evaluated and reported
This paper addresses the need of semantic component in the grid environment to discover and describe the grid resources semantically. We propose semantic grid architecture by introducing a knowledge layer at the top o...
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This paper addresses the need of semantic component in the grid environment to discover and describe the grid resources semantically. We propose semantic grid architecture by introducing a knowledge layer at the top of Gridbus broker architecture and thereby enabling broker to discover resources semantically. The semantic component in the knowledge layer enables semantic description of grid resources with the help of ontology template. The ontology template has been created using Protege-OWL editor for different types of computing resources in the grid environment. The Globus Toolkit's MDS is used to gather grid resource information and Protege-OWL libraries are used to dynamically create knowledge base of grid resources. Algernon inference engine is used for interacting with the knowledge base to discover suitable resources.
In this research, we propose an integrated and interactive framework to manage and retrieve large scale video archives. The video data are modeled by a hierarchical learning mechanism called HMMM (hierarchical Markov ...
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In this research, we propose an integrated and interactive framework to manage and retrieve large scale video archives. The video data are modeled by a hierarchical learning mechanism called HMMM (hierarchical Markov model mediator) and indexed by an innovative semantic video database clustering strategy. The cumulated user feedbacks are reused to update the affinity relationships of the video objects as well as their initial state probabilities. Correspondingly, both the high level semantics and user perceptions are employed in the video clustering strategy. The clustered video database is capable of providing appealing multimedia experience to the users because the modeled multimedia database system can learn the user's preferences and interests interactively
In this paper, a novel supervised classification approach called collateral representative subspace projection modeling (C-RSPM) is presented. C-RSPM facilitates schemes for collateral class modeling, class-ambiguity ...
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In this paper, a novel supervised classification approach called collateral representative subspace projection modeling (C-RSPM) is presented. C-RSPM facilitates schemes for collateral class modeling, class-ambiguity solving, and classification, resulting a multi-class supervised classifier with high detection rate and various operational benefits including low training and classification times and low processing power and memory requirements. In addition, C-RSPM is capable of adaptively selecting nonconsecutive principal dimensions from the statistical information of the training data set to achieve an accurate modeling of a representative subspace. Experimental results have shown that the proposed C-RSPM approach outperforms other supervised classification methods such as SIMCA, C4.5 decision tree, decision table (DT), nearest neighbor (NN), KNN, support vector machine (SVM), I-NN best warping window DTW, I-NN DTW with no warping window, and the well-known classifier boosting method AdaBoost with SVM
The development of effective classification techniques, particularly unsupervised classification, is important for real-world applications since information about the training data before classification is relatively ...
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The development of effective classification techniques, particularly unsupervised classification, is important for real-world applications since information about the training data before classification is relatively unknown. In this paper, a novel unsupervised classification algorithm is proposed to meet the increasing demand in the domain of network intrusion detection. Our proposed UNPCC (unsupervised principal component classifier) algorithm is a multiclass unsupervised classifier with absolutely no requirements for any a priori class related data information (e.g., the number of classes and the maximum number of instances belonging to each class), and an inherently natural supervised classification scheme, both which present high detection rates and several operational advantages (e.g., lower training time, lower classification time, lower processing power requirement, and lower memory requirement). Experiments have been conducted with the KDD Cup 99 data and network traffic data simulated from our private network testbed, and the promising results demonstrate that our UNPCC algorithm outperforms several well-known supervised and unsupervised classification algorithms
For many years discrete-event simulation has been used to analyze production and logistics problems in manufacturing and defense. In the early 1980s, visual interactive modelling environments were created that support...
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ISBN:
(纸本)9781424405015
For many years discrete-event simulation has been used to analyze production and logistics problems in manufacturing and defense. In the early 1980s, visual interactive modelling environments were created that supported the development, experimentation and visualization of simulation models. Today these environments are termed commercial-off-the-shelf simulation packages (CSPs). With the advent of distributed simulation and, later, the high level architecture, the possibility existed to link together these CSPs and their models to simulate larger problems within enterprises (e.g. multiple production lines) and across supply chains. However, the problem of standardizing the use of the HLA and its constituent parts in this domain exists. The solution of this problem is the work of the CSP interoperability product development group (CSPI PDG). The purpose of this paper is to introduce the CSPI PDG and to review the suite of standards proposed by the group and current progress
The effect of faults on electronic systems has been studied since the 1970s when it was noticed that radioactive particles caused errors in chips. This led to further research on the effect of charged particles on sil...
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The advantage of magnetic resonance imaging (MRI)-guided surgery, in which MR images taken during surgery are used to guide the surgery, has been recognized recently. However, there is a problem, due to long imaging t...
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