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1st international conference on Smart Energy systems and Artificial Intelligence (SESAI)

作者： Feder, Evgeniy Paramonov, Anton Mavrin, Pavel Salem, Iosif Schmid, stefan Aksenov, Vitaly ITMO Univ St Petersburg Russia Ecole Polytech Fed Lausanne Lausanne Switzerland Neapolis Univ Pafos Pafos Cyprus TU Berlin Berlin Germany City Univ London London England

ISBN: (纸本)9798350364613;9798350364606

Datacenter networks are becoming increasingly flexible with the incorporation of new optical communication technologies, such as optical circuit switches, enabling self-adjusting topologies that can adapt to the traffic pattern in a demand-aware manner. In this paper, we take the first steps toward demand-aware and self-adjusting k-ary tree networks. These are more powerful generalizations of existing binary search tree networks (like SplayNet [14]), which have been at the core of self-adjusting network (SAN) designs. k-ary search tree networks are a natural generalization offering nodes of higher degrees, reduced route lengths, and local routing in spite of reconfigurations (due to maintaining the search property). Our main results are algorithms for static k-ary tree networks and two online heuristics for self-adjusting k-ary tree networks.

关键词： self-adjusting networks k-ary trees online algorithms dynamic programming

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MDLoader: A Hybrid Model-driven Data Loader for Distributed Deep Neural networks Training

MDLoader: A Hybrid Model-driven Data Loader for Distributed ...

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1st international conference on Smart Energy systems and Artificial Intelligence (SESAI)

作者： Bae, Jonghyun Choi, Jong Youl Pasini, Massimiliano Lupo Mehta, Kshitij Ibrahim, Khaled Z. Lawrence Berkeley Natl Lab Berkeley CA 94720 USA Oak Ridge Natl Lab Oak Ridge TN USA

In this work, we propose MDLoader, a hybrid in-memory data loader for distributed deep neural networks. MDLoader introduces a model-driven performance estimator to automatically switch between one-sided and collective... 详细信息

ISBN: (纸本)9798350364613;9798350364606

关键词： One-sided communication Collective communication Graph Neural Network Performance estimator

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13th Mining Humanistic Data Workshop, MHDW 2024, 9th Workshop on 5G-Putting Intelligence to the Network Edge, 5G-PINE 2024 and 1st Workshop on AI in Applications for Achieving the Green Deal Targets, AI4GD 2024 held as parallel events of the IFIP WG 12.5 international workshops on Artificial Intelligence Applications and Innovations, AIAI 2024

13th Mining Humanistic Data Workshop, MHDW 2024, 9th Worksho...

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13th Mining Humanistic Data Workshop, MHDW 2024, 9th Workshop on 5G-Putting Intelligence to the Network Edge, 5G-PINE 2024 and 1st Workshop on AI in Applications for Achieving the Green Deal Targets, AI4GD 2024 held as parallel events of the IFIP WG 12.5 international workshops on Artificial Intelligence Applications and Innovations, AIAI 2024

ISBN: (纸本)9783031632266

The proceedings contain 34 papers. The special focus in this conference is on Mining Humanistic Data. The topics include: Boosting Data Monetisation with DATAMITE;Boosting Digitalization Across European Regions: The AMBITIOUS Approach;Data Monetization Opportunities and Challenges: The European Landscape by DATAMITE;Innovative Digital Forensic and Investigation Tools for Law Enforcement: The EMPOWER & TRACY Approach;market Analysis of a Data Platform in the European Data Ecosystem;OCTAPUS: Empowering Next Generation Central Offices with Cross-Layer Network Intelligence Towards a Reconfigurable Data Plane;On 6G-Enabled SDN-Based Mobile Network User Plane with DRL-Based Traffic Engineering;on the Efficient Architecture for 6G System;Promoting Deployment of Innovative Use Cases in Market Verticals for the Support of 6G Evolution: The 6G-PATH Context;scalable Data Profiling for Quality Analytics Extraction;seamless Integration of Efficient 6G Wireless Technologies for communication and Sensing Enabling Ecosystems;testing Plan Description and Field Measurements for Real-Time Wide Area Monitoring of Interconnected Power systems in the Smart5Grid Project;comparative Analysis of Time Series and Machine Learning Models for Air Quality Prediction Utilizing IoT Data;Efficient Energy Disaggregation Using DBSCAN: A Novel Approach for Enhanced Energy Management;integrating Machine Learning and Biological Context for Single-Cell Gene Regulatory Network Inference;museum Education: Integration of Cultural Heritage and Educational Metadata Schemas;net Zero strategies: Empowering Climate Change Solutions Through Advanced Analytics and Time Series;New Perspectives in e-Learning: EEG-Based Modelling of Human Cognition Individual Differences;optimizing Vehicle-to-Vehicle Energy Sharing with Predictive Modeling;predicting Song Popularity Through Machine Learning and Sentiment Analysis on Social networks;transformer-Based Anomaly Detection in Energy Consumption Data;Advancing Agricultural

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A reactive system for pedestrian mobility simulation

A reactive system for pedestrian mobility simulation

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12th international conference on Ambient systems, networks and Technologies (ANT) / 4th international conference on Emerging Data and Industry 4.0 (EDI40)

作者： Nahri, Mohamed Boulmakoul, Azedine Karim, Lamia Lbath, Ahmed Hassan II Univ Casablanca FSTM LIM IOS Casablanca Morocco Hassan 1st Univ LISA Lab ENSA Berrechid Settat Morocco Univ Grenoble Alpes CNRS LIG MRIM Grenoble France

Handling the microscopic level of Vehicle-Pedestrian interactions is highly useful for analyzing patterns-based pedestrian accident exposure. Recently proposed systems are based on vehicle-to-pedestrian communication to analyze real-time situations and thus warning both sides of potential crashes. Two parts are composing those systems. The first concerns network technologies ensuring direct communication between vehicles and pedestrians and the second is related to information processing analyzing and predicting trajectories and dangers. One of the most challenges facing the last systems category is to provide them with precise and sufficient data to test and improve them. Precisely, to analyze vehicle-pedestrian interactions, we suggest detecting pedestrian behavior with respect to its surrounding vehicles as well as detecting vehicle behavior with respect to its surrounding pedestrians. In this work, we consider generating pedestrians and vehicles' data using SUMO. Moreover, we design a handler for preparing Vehicle-Pedestrian interactions data for upper layers for deep analytic and patterns finding purposes. Mixed realistic traffic simulation is performed in Mohammedia city and the first results are shown. (C) 2021 The Authors. Published by Elsevier B.V.

关键词： Pedestrian-vehicle interactions Mixed traffic flow simulation Pedestrian safety systems

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Prediction of electrical energy consumption through recurrent neural networks 4

Prediction of electrical energy consumption through recurren...

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Joint of the 4th international conference on Applied Informatics workshops, ICAIW 2021, 2nd international Workshop on Applied Artificial Intelligence, WAAI 2021, 3rd international Workshop on Applied Informatics for Economy, Society, and Development, AIESD 2021, 4th international Workshop on Data Engineering and Analytics, WDEA 2021, 1st international Workshop on Knowledge Management and Information Technologies, WKMIT 2021 and 4th international Workshop on Smart and Sustainable Cities, WSSC 2021

作者： Díaz-Castillo, Oscar Daniel Puerto-Lara, Andrés Esteban Sáenz-Leguizamón, Javier Alejandro Ducón-Sosa, Vladimir Wavelet S.A.S. Bogotá Colombia Compensar Fundación Universitaria Bogotá Colombia

It is almost unthinkable to conceive the modern world without the use of electricity;every day around the world demand for electric energy is increasing, not only for society development but also to reduce the fossil fuel consumption and CO2 emissions to combat climate change, as recommended in the UN Sustainable Development Goals (SDGs). One approach to improve energy efficiency related to electricity consumption is the use information and communication technologies (ICT) integrated with the electrical systems to model and predict electricity consumption. This article presents a prediction model based on recurrent neural networks (RNN) for the prediction of electricity consumption, verifying its validity with real data taken from a local company. The model is compared to an ARIMA model and to real data to verify its prediction capacity, the results showed a 95% similarity using the Deep learning model while ARIMA yields 40% of similarity. © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 international (CC BY 4.0). CEUR Workshop Proceedings (***)

关键词： Forecasting

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Editorial-Special Issue on Molecular communications for Diagnostics and Therapeutic Development of Infectious Diseases

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IEEE TRANSACTIONS ON MOLECULAR BIOLOGICAL AND MULTI-SCALE communicationS 2021年第3期7卷 117-120页

作者： Balasubramaniam, Sasitharan Barros, Michael Taynnan Veletic, Mladen Kanada, Masamitsu Pierobon, Massimiliano Vainio, Seppo Balasingham, Ilangko Univ Nebraska Lincoln Dept Comp Sci & Engn Lincoln NE 68588 USA Univ Essex Sch Comp Sci & Elect Engn Colchester CO4 3SQ Essex England Oslo Univ Hosp Intervent Ctr N-0372 Oslo Norway Michigan State Univ Dept Pharmacol & Toxicol E Lansing MI 48824 USA Univ Oulu Biochem & Mol Med Oulu 90570 Finland Norwegian Univ Sci & Technol Dept Elect Syst N-7491 Trondheim Norway

The COVID-19 pandemic in the last year has brought along numerous challenges on all fronts for humanity. Besides the high number of fatalities, economic and societal impact, the virus has also raised a question on the current approaches and methodologies for combatting pandemics. An important factor in this global fight against the pandemic, is the fact that key experts within the fields of biotechnology, virology and immunology have to return to the drawing board to develop new approaches to treat the virus. This has triggered a multi and inter-disciplinary research drive to bring in new concepts, techniques and methodologies that can be used to understand the virus in order to develop novel treatment techniques. The field of molecular communications, which is just over a decade old, is one area of research in the field of communications and networking that can contribute towards understanding of virus and their infection process. This is the aim of this special issue, where we have collected a number of publications from key researchers in the field of molecular communications that can contribute towards understanding the viral properties and behavior, which can be used to support the current as well as future pandemics.

关键词： Special issues and sections Molecular communication (telecommunication) Infectious diseases Pandemics COVID-19 Modeling

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11th international conference on Emerging Ubiquitous systems and Pervasive networks, EUSPN 2020, - The 10th international conference on Current and Future Trends of Information and communication Technologies in Healthcare, ICTH 2020 / Affiliated workshops

11th International Conference on Emerging Ubiquitous Systems...

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1st international Symposium on Synthesis, Characterization and Processing of Inorganic, Bio and Nano Materials, SCPINM 2019

The proceedings contain 46 papers. The topics discussed include: thermo-mechanical aspects and temperature measurement techniques of bone grinding;3D printing of food materials: a state of art review and future applications;evaluation of mechanical properties of polytherimide reinforced carbon/glass/ aramid hybrid composites;comparative evaluation of aluminum and stainless steel dissimilar welded joints;a numerical study on the performance of water based copper oxide nanofluids in compact channel;reduction of abrasive wear via hardfacing of mouldboard ploughshare;application of cryo-treatment for improving machining characteristics and reduce manufacturing cost;and performance evaluation of Inconel 718 under vegetable oils based nanofluids using minimum quantity lubrication grinding.

关键词： Grinding (machining)

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The m-Ranking of nodes in complex networks

The m-Ranking of nodes in complex networks

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international communication systems and networks and workshops, comsnets

作者： K. Reji Kumar Shibu Manuel Deepu Benson Department of Mathematics N. S. S. College Pandalam Kerala Department of Mathematics St. Dominic's College Kanjirapally Kerala Department of Computer Science and Engineering Amal Jyothi College of Engineering Kanjirapally Kerala

ISBN: (纸本)9781509042517

Identifying influential nodes in complex networks has attracted much attention because of its great theoretical significance and wide application. The m-Ranking method takes into account degree of all nodes and weight of all edges to rank nodes of the network with different weight. This ranking method can be used for unweighted networks also by fixing the value of the parameter α = 1. In addition, we demonstrate our new method on a real air traffic network and show that the ranks calculated using the new method is more meaningful compared with other methods.

关键词： Complex networks Airports Joining processes communication systems Mathematics Diseases

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1st international conference on communication systems and networks and workshops, comsnets 2009

1st International Conference on Communication Systems and Ne...

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1st international conference on communication systems and networks and workshops, comsnets 2009

ISBN: (纸本)9781424429127

The proceedings contain 91 papers. The topics discussed include: community formation and search in P2P: a robust and self-adjusting algorithm;resource adaptive hierarchical organization in pervasive environments;a framework for application centric wireless sensor network management;design of efficient ternary-tree based group key agreement protocol for dynamic group;performance enhancement in mobile adhoc networks;bandwidth measurement and management for end-to-end connectivity over IP networks;control-theoretic, mission-driven, optimization techniques for wireless sensor networks;a greedy minimum energy consumption forwarding protocol for wireless sensor networks;genetic algorithm approach to dynamic multi constraint multi path QoS routing algorithm for IP networks (GA-DMCMPRA);and efficient flow-aware dynamic link load balancing.

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Continuous Monitoring and Digital systems for Elders 1

Continuous Monitoring and Digital Systems for Elders

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1st international conference on Information and communication Technologies for Ageing Well and E-Health (ICT4AgeingWell)

作者： Rocha, Nuno Sousa, Raquel Goncalves, Gil Inst Engn Porto Informat Engn Dept Porto Portugal Increase Time SA Matosinhos Portugal Univ Porto Informat Engn Dept Engn Fac Porto Portugal

ISBN: (纸本)9789897581021

Ageing of the European population raises issues both socially and economically, creating major challenges for the traditional care and healthcare paradigm. Recent technological developments generate a favorable environment for a paradigm shift in the way care and healthcare is provided, by promoting the inclusion of the elders in the digital society. This paper presents an approach to promote elders inclusion, based on a RWD platform, capable of being used in multiple devices (including SmartTVs), and in wireless sensor networks. studies involving end users have shown how well-adjusted interfaces ease the process of inclusion of IT in elders' life. This work has been developed within the frame of the European project HELASCoL.

关键词： Active Ageing Ambient Assisted Living RWD Elders

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