DiffServ is the basis of contemporary QoS-enabled networks. Setting up DiffServ QoS requires extensive engineering effort in dimensioning and provisioning, especially for adjacent networks under different administrati...
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ISBN:
(纸本)0780395654
DiffServ is the basis of contemporary QoS-enabled networks. Setting up DiffServ QoS requires extensive engineering effort in dimensioning and provisioning, especially for adjacent networks under different administrations linked in a "federated" hierarchy. In this paper we present a case study for QoS techniques employed in the GRNET MAN networks of Athens and Crete. After introducing the supported QoS mechanisms and service types, we discuss our dimensioning methodology and present two algorithms for worst-case dimensioning. We explain the provisioning mechanisms of GRNET and we present in brief our new automated provisioning ANS tool. Finally, we deal with the extension of our mechanisms and tools in hierarchically federated networks and give some future directions of our work.
This work aims a two-fold contribution: it presents a software to analyse logfiles and visualize popular web hot spots and, additionally, presents an algorithm to use this information in order to identify subsets of t...
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ISBN:
(纸本)1595930515
This work aims a two-fold contribution: it presents a software to analyse logfiles and visualize popular web hot spots and, additionally, presents an algorithm to use this information in order to identify subsets of the website that display large access patterns. Such information is extremely valuable to the site maintainer, since it indicates points that may need content intervention or/and site graph restructuring. Experimental validation verified that the visualization tool, when coupled with algorithms that infer frequent traversal patterns, is both effective in indicating popular hot spots and efficient in doing so by using graph-based representations of popular traversals.
People and animals fuse auditory and visual information to obtain robust perception. A particular benefit of such cross-modal analysis is the ability to localize visual events associated with sound sources. We aim to ...
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There are both associations and differences between structured and unstructured data mining. How to unite them together to be a united theoretical framework and to guide the research of knowledge discovery and data mi...
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There are both associations and differences between structured and unstructured data mining. How to unite them together to be a united theoretical framework and to guide the research of knowledge discovery and data mining has become an urgent problem to be solved. On the base of analysis and study of existing research results, the united model of knowledge discovery state space （UMKDSS） is presented, and the structured data mining and the complex type data mining are associated together. UMKDSS can provide theoretical guidance for complex type data mining. An application example of UMKDSS is given at last.
In this paper, we present a Web-based intelligent education system to help students in the context of an AI course. We concentrate on the adaptivity and student evaluation aspects of the system. Adaptivity refers to t...
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In this paper, we present a Web-based intelligent education system to help students in the context of an AI course. We concentrate on the adaptivity and student evaluation aspects of the system. Adaptivity refers to the capability of the system to adapt teaching to student needs, specified by the student model characteristics. Student evaluation refers to the evaluation of the knowledge level of a student, which is one of the most important characteristics, with regards to taught concepts. Adaptive hypermedia techniques, like graphical link annotation, and an intelligent technique, i.e. a rule-based expert system, are used to achieve the above goals. An evaluation of the system showed encouraging results as far as its usability and learning are concerned.
We consider the problem of maximizing the lifetime of a given multicast connection in a wireless network of energy-constrained (e.g., battery-operated) nodes, by choosing ideal transmission power levels for the nodes ...
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We consider the problem of maximizing the lifetime of a given multicast connection in a wireless network of energy-constrained (e.g., battery-operated) nodes, by choosing ideal transmission power levels for the nodes relaying the connection. We distinguish between two basic operating modes: In a static power assignment, the power levels of the nodes are set at the beginning and remain unchanged until the nodes are depleted of energy. In a dynamic power schedule, the powers can be adjusted during operation. We show that while lifetime-maximizing static power assignments can be found in polynomial time, for dynamic schedules the problem becomes NP-hard. We introduce two approximation heuristics for the dynamic case, and experimentally verify that the lifetime of a dynamically adjusted multicast connection can be made several times longer than what can be achieved by the best possible static assignment.
This paper discusses a visual attack to BPCS-Steganography (Bit-Plane Complexity Segmentation-Steganography) and presents a countermeasure. BPCS categorizes each small block within cover images into either a "noi...
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This work is in the area of parallel discrete event simulation. We consider a conservatively synchronized parallel simulation where submodels consist of multiple entities, each with some amount of lookahead. We explor...
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ISBN:
(纸本)9077381228
This work is in the area of parallel discrete event simulation. We consider a conservatively synchronized parallel simulation where submodels consist of multiple entities, each with some amount of lookahead. We explore the issue of improving the lookahead of a submodel by combining the lookahead abilities of individual entities. We review the concepts and conditions for cumulative lookahead. We provide an experimental evaluation of the effect of cumulative lookahead on simulation performance.
In this paper, we first present and compare existing categorization schemes for neuro-symbolic approaches. We then stress the point that not all hybrid neuro-symbolic approaches can be accommodated by existing categor...
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In this paper, we first present and compare existing categorization schemes for neuro-symbolic approaches. We then stress the point that not all hybrid neuro-symbolic approaches can be accommodated by existing categories. Such a case is rule-based neuro-symbolic approaches that propose a unified knowledge representation scheme suitable for use in expert systems. That kind of integrated schemes have the two component approaches tightly and indistinguishably integrated, offer an interactive inference engine and can provide explanations. Therefore, we introduce a new category of neuro-symbolic integrations, namely ‘representational integrations’. Furthermore, two sub-categories of representational integrations are distinguished, based on which of the two component approaches of the integrations is given pre-eminence. Representative approaches as well as advantages and disadvantages of both sub-categories are discussed.
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