Journal: Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Abbreviation

LNICST

Publisher

Springer

Journal Volumes

ISSN

1867-8211
1867-822X

Description

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Publications 1 - 10 of 25
  • VF2x
    Item type: Conference Paper
    Yin, Qin; Roscoe, Timothy (2012)
    Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ~ Proceedings of the 8th Intern. Conference on Testbeds and Research Infrastructures for the Development of Networks and Communities (TridentCom 2012)
  • Minimum Expected *-cast Time in DTNs
    Item type: Conference Paper
    Picu, Andreea; Spyropoulos, Thrasyvoulos (2009)
    Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ~ Bioinspired models of network, information, and computing systems : 4th international conference ; revised selected papers
  • Loscrí, Valeria; Magno, Michele; Surace, Rosario (2014)
    Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
  • Muaremi, Amir; Gravenhorst, Franz; Seiter, Julia; et al. (2014)
    Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ~ Mobile and Ubiquitous Systems: Computing, Networking, and Services [Elektronische Daten] : 10th International Conference, MOBIQUITOUS 2013, Tokyo, Japan, December 2-4, 2013, Revised Selected Papers
  • Sigg, Stephan; Hock, Mario; Scholz, Markus; et al. (2014)
    Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ~ Mobile and Ubiquitous Systems: Computing, Networking, and Services : 10th International Conference, MOBIQUITOUS 2013, Tokyo, Japan, December 2-4, 2013, Revised Selected Papers
  • Schläpfer, Markus; Shapiro, Jonathan L. (2009)
    Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ~ Complex sciences : first international conference, Complex 2009, Shanghai, China, February 23-25, 2009 : revised papers
  • Abdalazim, Nouran; Arbilla Larraza, Joseba Aitzol; Alchieri, Leonardo; et al. (2023)
    Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ~ Pervasive Computing Technologies for Healthcare
    Wearable heart rate (HR) sensing devices are increasingly used to monitor human health. The availability and the quality of the HR measurements may however be affected by the body location at which the device is worn. The goal of this paper is to compare HR data collected from different devices and body locations and to investigate their interchangeability at different stages of the data analysis pipeline. To this goal, we conduct a data collection campaign and collect HR data from three devices worn at different body positions (finger, wrist, chest): The Oura ring, the Empatica E4 wristband and the Polar chestbelt. We recruit five participants for 30 nights and gather HR data along with self-reports about sleep behavior. We compare the raw data, the features extracted from this data over different window sizes, and the performance of models that use these features in recognizing sleep quality. Raw HR data from the three devices show a high positive correlation. When features are extracted from the raw data, though, both small and significant differences can be observed. Ultimately, the accuracy of a sleep quality recognition classifier does not show significant differences when the input data is derived from the Oura ring or the E4 wristband. Taken together, our results indicate that the HR measurements collected from the considered devices and body locations are interchangeable. These findings open up new opportunities for sleep monitoring systems to leverage multiple devices for continuous sleep tracking.
  • Antoniadis, Panayotis; Fdida, Serge; Griffin, Christopher; et al. (2013)
    Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ~ Ad hoc networks : 4th International ICST Conference, ADHOCNETS 2012, Paris, France, October 16-17, 2012, revised selected papers
  • Vindigni, Alessandro; Portmann, Oliver; Saratz, Niculin; et al. (2009)
    Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ~ Complex Sciences
    We investigate a spin model in which a ferromagnetic short-range interaction competes with a long-range antiferromagnetic interaction decaying spatially as 1/r(d)+sigma, d being the dimensionality of the lattice. For a smaller than a certain threshold (sigma) over cap (with (sigma) over cap > 1), the long-range interaction is able to prevent global phase separation, the uniformly magnetized state favored by the exchange interaction for spin systems. The ground state then consists of a mono-dimensional modulation of the order parameter resulting in a superlattice of domains with positive and negative magnetization. We find that the period of modulation shrinks with increasing temperature T and suggest that this is a universal property of the considered model. For d = 2 and sigma = 1 (dipolar interaction) Mean-Field (MF) calculations find a striking agreement with experiments performed on atomically-thin Fe/Cu(001) films. Monte Carlo (MC) results for d = 1 also support the generality of our arguments beyond the MF approach.
  • Ponnada, Tushara; Al-Tous, Hanan; Tirkkonen, Olav; et al. (2019)
    Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ~ Cognitive Radio-Oriented Wireless Networks 14th EAI International Conference, CrownCom 2019, Poznan, Poland, June 11–12, 2019, Proceedings
    Channel-charting (CC) is a machine learning technique for learning a multi-cell radio map, which can be used for cognitive radio-resource-management (RRM) problems. Each base-station (BS) extracts features from the channel-state-information samples (CSI) from transmissions of user-equipment (UE) at different unknown locations. The multi-path channel components are estimated and used to construct a dissimilarity matrix between CSI samples at each BS. A fusion center combines the dissimilarity matrices of all base-stations, performs dimensional reduction based on manifold learning, constructing a Multipoint-CC (MPCC). The MPCC is a two dimension map, where the spatial difference between any pair of UEs closely approximates the distance between the clustered features. MPCC provides a mapping for any given trained UE location. To use MPCC for cognitive RRM tasks, CSI measurements for new UEs would be acquired, and these UEs would be placed on the radio map. Repeating the MPCC procedure for out-of-sample CSI measurements is computationally expensive. For this, extensions of MPCC to out-of-sample UE CSIs are investigated in this paper, when Laplacian-Eigenmaps (LE) is used for dimensional reduction. Simulation results are used to show the merits of the proposed approach.
Publications 1 - 10 of 25