Designing in an environment of Virtual Reality is a field that gains ground. Although more and more applications are constantly released, the majority of designers have not yet been introduced into Virtual Reality. A ...
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ISBN:
(纸本)9781450398541
Designing in an environment of Virtual Reality is a field that gains ground. Although more and more applications are constantly released, the majority of designers have not yet been introduced into Virtual Reality. A widely used tool for designing is Rhino which has been released by McNeel and Rhino Developer encourages the users to create plug-ins for custom use of the software. In parallel, Meta's developing tools offer their users the chance to customize their own applications. Towards the direction of Virtual Reality integration, both have already released new products for their users. RhinoVR is an open source plug-in for Rhino, while at the same time Meta provides Oculus hardware and platform solutions for users to turn their concept into reality. What is yet to be developed is a model that encourages the customization of a VR design platform, focusing mainly on developing a personalized toolbox for designing.
The Method of Auxiliary Sources (MAS) is a broadly used numerical technique, purposely designed for the solution of elliptic boundary value problems in Physics and engineering, including Electromagnetics (EM). Superfi...
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We discuss the development of virtual communities and especially e-learning communities. In particular, we are inspired by VirRAD European project, and we present the intermediate results that have raised from the def...
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We discuss the development of virtual communities and especially e-learning communities. In particular, we are inspired by VirRAD European project, and we present the intermediate results that have raised from the definition of this virtual radiopharmacy community.
A keyphrase (a multi-word unit) in a document denotes one or multiple keywords capturing a main topic of the underlying document. Finding good keyphrases of a document can quickly summarize knowledge for efficient dec...
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A keyphrase (a multi-word unit) in a document denotes one or multiple keywords capturing a main topic of the underlying document. Finding good keyphrases of a document can quickly summarize knowledge for efficient decision making and benefit domains involving intensive text information. To date, existing keyphrase extraction methods cannot be customized to each specific document, mainly because their patterns used to form paraphrases are too restrictive and may not capture flexible keyword relationships inside the text. In this paper, we propose a sequential pattern mining based document-specific keyphrase extraction method. Our key innovation is to use wildcards (or gap constraints) to help extract sequential patterns, so the flexible wildcard constraints within a pattern can capture semantic relationships between words, and the system will have full flexibility to discover different types of sequential patterns as candidates for keyphrase extraction. To achieve the goal, we regard each single document as a sequential dataset, and propose an efficient algorithm to mine sequential patterns with wildcard and one-off conditions that allows important keyphrases to be captured during the mining process. For each extracted keyphrase candidate, we use some statistical pattern features to characterize it, and further collect all keyphrases from the document to form a training set. A supervised learning classifier is trained to identify keyphrases from a test document. Because our pattern mining and pattern characterization processes are customized to each single document, keyphases extracted from our method are highly specific for each document. Experimental results demonstrate that the proposed sequential pattern mining method outperforms existing pattern mining methods in both runtime performance and completeness. Comparisons on keyphrase benchmark datasets also confirm that the proposed document-specific keyphrase extraction method is effective in improving the quality
We propose and analyze an extension of the concept of RSVP to guarantee the service quality of mobile Internet-based applications. Our Mobile RSVP protocol provides an advanced resource reservation mechanism in a wire...
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ISBN:
(纸本)0780365968
We propose and analyze an extension of the concept of RSVP to guarantee the service quality of mobile Internet-based applications. Our Mobile RSVP protocol provides an advanced resource reservation mechanism in a wireless cellular environment. Furthermore, we propose the dynamic resource sharing algorithm to make better use of network resources in those cells, where advance reservation takes place. We analyze our proposed protocol and the corresponding dynamic resource sharing algorithm by simulating the behavior of distinct call types in a single cell. We also investigate the effect of user mobility behavior on the performance of future resource reservation protocols with mobility support. By analyzing the pattern of user mobility as well as possible application priorities, we hope to be able to put constraints to the scope of service provision.
A crucial point on the successful deployment of multicast services is the enhanced reliability by means of advanced error control schemes. To this direction Third Generation Partnership Project (3GPP) has standardized...
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A crucial point on the successful deployment of multicast services is the enhanced reliability by means of advanced error control schemes. To this direction Third Generation Partnership Project (3GPP) has standardized exclusively for Multimedia Broadcast/Multicast Services (MBMS) the use of a Forward Error Correction (FEC) mechanism on the application layer based on Raptor codes. Since the standardized systematic, fountain Raptor code is now considered obsolete, the emergence of a new variant of Raptor codes, named RaptorQ, provides enhanced capabilities for mobile multicast services. In this paper, we provide a performance comparison of the standardized Raptor Application Layer FEC (AL-FEC) scheme with the very promising RaptorQ FEC code. We examine the enhancements that RaptorQ introduces on the AL-FEC protection robustness, providing a thorough performance analysis in comparison with the current Raptor FEC scheme. Furthermore, in order to verify the improved performance of RaptorQ, we provide several simulation results utilizing the ns-3 environment, considering the application of both the examined AL-FEC schemes over multicast services for next generation mobile networks.
Optical network design problems fall in the broad category of network optimization problems. We give a short introduction on network optimization and general algorithmic techniques that can be used to solve complex an...
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Optical network design problems fall in the broad category of network optimization problems. We give a short introduction on network optimization and general algorithmic techniques that can be used to solve complex and difficult network design problems. We apply these techniques to address the static Routing and Wavelength Assignment problem that is related to planning phase of a WDM optical network. We present simulation result to evaluate the performance of the proposed algorithmic solution.
Sequential recommendation aims to identify and recommend the next few items of users’ interest. It becomes an effective tool to help users select their favorite items from a variety of options. A key challenge in seq...
Sequential recommendation aims to identify and recommend the next few items of users’ interest. It becomes an effective tool to help users select their favorite items from a variety of options. A key challenge in sequential recommendation is to learn the patterns and dynamics, which are most pertinent to inform future interactions of users. With the prosperity of deep learning, many deep models, particularly based on recurrent neural networks [1] and with attention mechanisms [2] , [3] , have been developed for sequential recommendation purposes. However, our analysis demonstrates that, these deep models, particularly those with attention mechanisms, may not always learn meaningful attention weights from the extremely sparse recommendation data, and thus, could degrade the recommendation performance. Therefore, in this study, instead of deep models, we develop novel, effective and efficient hybrid associations models (HAM) to better learn from the sparse and limited recommendation data. This study has been published in IEEE Transactions on Knowledge and Data engineering. Please refer to the full manuscript [4] for more details.
Crowdsourcing systems offer numerous advantages for acquiring data, which can contribute to the development of modern concepts such as Smart Cities. Air quality in urban areas has been identified as a crucial theme an...
Crowdsourcing systems offer numerous advantages for acquiring data, which can contribute to the development of modern concepts such as Smart Cities. Air quality in urban areas has been identified as a crucial theme and requirement, towards ideal city of the future that can be adapted upon its citizens' needs and comfort. Thus, besides the sensing infrastructure, a complementary system must be implemented in order to enable the public authority and municipality awareness over citizens' personalised and subjective input, in a cost efficient way that can be easily upscaled. In this work, we present HealthAir, an mHealth application alongside its subsystems (namely a web application and a smartwatch version), that aims to increase and complement the sensing capacity of a Smart City, with respect to the air quality-wise health of the citizens. This is achieved based on questionnaires and surveys approved by the health community, and services and features that implement a bidirectional interaction between the system and the users. Finally, users' data and air quality measurements from a third party platform are combined and presented for the case study realization and demonstration.
Most of the typical reinforcement learning algorithms help wireless devices choose the security policy such as the moving strategy and communication policy by exploring all the possible state-action pairs including th...
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