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Proceedings of the 26th Pan-Hellenic Conference on informatics

作者： Georgia Drampalou Nikolaos Kourniatis Ioannis Voyiatzis Department of Informatics and Computer Engineering University of West Attica Greece Department of Civil Engineering University of West Attica Greece

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.

关键词： plug-in SDK Rhino Developer Oculus Quest 2 VR Design OpenVR API

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A Review of the Method of Auxiliary Sources (MAS) in Applied Electromagnetics 25

A Review of the Method of Auxiliary Sources (MAS) in Applied...

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25th International Conference on Electromagnetics in Advanced Applications, ICEAA 2024

作者： Anastassiu, Hristos T. Papakanellos, Panagiotis J. Tsitsas, Nikolaos L. Department of Computer Informatics and Telecommunications Engineering International Hellenic University End of Magnisias Str. SerresGR-62124 Greece Department of Aeronautical Sciences Hellenic Air Force Academy Dekeleia Air Force Base Dekeleia AthensGR-13671 Greece School of Informatics Aristotle University of Thessaloniki ThessalonikiGR-54124 Greece

ISBN: (纸本)9798350360974

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). Superficially it resembles surface integral equation formulations, such as the Method of Moments (MoM), however it has been developed on different mathematical concepts. It was originally proposed by researchers in the former Soviet Union (currently Republic of Georgia) and was further refined at the National Technical University of Athens (NTUA), Greece, through an efficient Greek-Georgian collaboration in the 1990's. The fundamental concept of auxiliary sources, i.e. simulation of E M propagation behaviour in terms of fictitious, elementary fields has prompted several, unrelated scholars to develop practically the same, or very similar techniques, known in the literature by various names, e.g. "The Multifilament Current Model Method" or "The Discrete Singularity Method". Furthermore, MAS is closely related to the "Generalized Multipole Technique" (GMT) or "Multiple Multipole Technique" (MMT). The key mathematical and physical basis, common to all aforementioned methods is the following: the solution to the E M radiation or scattering problem is constructed in terms of discrete fictitious currents (the " auxiliary sources" - ASs), located away from physical boundaries, as opposed to continuous equivalent currents placed on the interfaces, utilized in MoM, for example. © 2024 IEEE.

关键词： Integral equations

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Building e-learning communities: the case of VirRAD

Building e-learning communities: the case of VirRAD

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International Conference on Advanced Learning Technologies (ICALT)

作者： Ch. Bouras El. Giannaka V. Kapoulas M. Nani Th. Tsiatsos Computer Engineering and Informatics Department (CEID) University of Patras Greece Research Academic Computer Technology Institute Greece

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... 详细信息

关键词： Electronic learning computer aided software engineering computer aided instruction Courseware Collaborative work informatics Environmental economics Virtual reality Vocational training Professional communication

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Efficient sequential pattern mining with wildcards for keyphrase extraction

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Knowledge-Based Systems 2017年 115卷 27-39页

作者： Xie, Fei Wu, Xindong Zhu, Xingquan School of Computer Science and Information Engineering Hefei University of Technology Hefei 230009 China Department of Computer Science and Technology Hefei Normal University Hefei 230601 China School of Computing and Informatics University of Louisiana at Lafayette LA 70503 United States Dept. of Computer & Electrical Eng. and Computer Science Florida Atlantic Univ. Boca Raton FL 33431 United States

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

关键词： Classification Document summarization Keyphrase extraction Sequential pattern mining Wildcards

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Mobile RSVP with dynamic resource sharing

Mobile RSVP with dynamic resource sharing

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IEEE Conference on Wireless Communications and Networking

作者： A. Mahmoodian G. Haring Institute for Computer Science and Business Informatics Department for Advanced Computer Engineering University of Technology Vienna Vienna Austria

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.

关键词： Resource management Protocols Quality of service Mobile communication Heuristic algorithms Land mobile radio cellular systems computer science informatics Mobile computing Web and internet services

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Enhancing reliable mobile multicasting with RaptorQ FEC

Enhancing reliable mobile multicasting with RaptorQ FEC

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IEEE Symposium on computers and Communications (ISCC)

作者： Christos Bouras Nikolaos Kanakis Vasileios Kokkinos Andreas Papazois Computer Engineering and Informatics Department University of Patras Greece Computer Technology Institute CTI Greece Patras Greece

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.

关键词： Encoding Forward error correction Decoding Mobile communication Maintenance engineering Delay Reliability

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Algorithmic aspects of optical network design

Algorithmic aspects of optical network design

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International Conference on Optical Network Design and Modeling, ONDM

作者： E. A. Varvarigos K. Christodoulopoulos Computer Engineering and Informatics Department University of Patras Greece Research Academic Computer Technology Institute Patra Greece

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.

关键词： Algorithm design and analysis Cost function Polynomials Optical fiber networks WDM networks Routing

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HAM: Hybrid Associations Models for Sequential Recommendation (Extended abstract)

HAM: Hybrid Associations Models for Sequential Recommendatio...

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International Conference on Data engineering

作者： Bo Peng Zhiyun Ren Srinivasan Parthasarathy Xia Ning Department of Computer Science and Engineering The Ohio State University Department of Biomedical Informatics The Ohio State University Department of Computer Science and Engineering Translational Data Analytics Institute The Ohio State University Department of Biomedical Informatics Department of Computer Science and Engineering Translational Data Analytics Institute The Ohio State University

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.

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HealthAir: A Crowdsourcing mHealth Platform for Air Pollution Effects on Citizens Health Status

HealthAir: A Crowdsourcing mHealth Platform for Air Pollutio...

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International Conference on Distributed Computing in Sensor Systems (DCOSS)

作者： Ioannis Katsidimas Sotiris Nikoletseas Stefanos H. Panagiotou Christina Spyropoulou Computer Engineering and Informatics Department University of Patras Greece Computer Technology Institute and Press “Diophantus” (CTI) Greece

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.

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Deep Reinforcement Learning for Network Security Applications With A Safety Guide

Deep Reinforcement Learning for Network Security Application...

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2023 IEEE/CIC International Conference on Communications in China, ICCC 2023

作者： Liu, Zhibo Lu, Xiaozhen Chen, Yuhan Xiao, Yilin Xiao, Liang Bu, Yanling Nanjing University of Aeronautics and Astronautics College of Computer Science and Technology Nanjing China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen China Xiamen University Department of Informatics and Communication Engineering Xiamen China

ISBN: (纸本)9798350345384

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 the risky policies that cause a severe collision or network disaster. In this paper, we design a safe reinforcement learning algorithm for safety-critical applications (e.g., intelligent transportation systems) to guide the learning agent to avoid exploring risky policies. This algorithm uses Q-network (i.e., a convolutional neural network or a deep neural network) to choose the policy and designs a safety guide to modify the chosen policy that results in dangerous status. More specifically, the safety guide includes a risk alarm module that evaluates the immediate warning value corresponding to the risk of each state-action pair and a G-network that estimates the long-term risk value. By adding the long-term risk value and the long-term expected reward output by the Q-network, this algorithm uses a safety dock to modify the chosen policy. This algorithm uses the immediate warning value to formulate a safe buffer and a risky buffer for the G-network updating to ensure fully exploration in the initial learning process. As a case study, we apply the designed algorithm in a cargo transportation system, in which the experimental results verify the effectiveness of our algorithm compared with the benchmark safe deep Q-network. © 2023 IEEE.

关键词： Network security

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