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Application of a Cognitive-Inspired Algorithm for Detecting Communities in Mobility Networks

Application of a Cognitive-Inspired Algorithm for Detecting ...

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International conference on Cloud and Green computing (CGC)

作者： Emanuele Massaro Andrea Guazzini Lorenzo Valerio Andrea Passerella Franco Bagnoli Center for the Study of Complex Systems University of Florence Italy Department of Physics and Astronomy University of Florence and INFN Italy Inst. for Inf. & Telematics Pisa Italy

The emergence and the global adaptation of mobile devices has influenced human interactions at the individual, community, and social levels leading to the so called Cyber-Physical World (CPW) convergence scenario [1]. One of the most important features of CPW is the possibility of exploiting information about the structure of the social communities of users, revealed by joint movement patterns and frequency of physical co-location. Mobile devices of users that belong to the same social community are likely to "see" each other (and thus be able to communicate through ad-hoc networking techniques) more frequently and regularly than devices outside the community. In mobile opportunistic networks, this fact can be exploited, for example, to optimize networking operations such as forwarding and dissemination of messages. In this paper we present the application of a cognitive-inspired algorithm [2, 3, 4] for revealing the structure of these dynamic social networks (simulated by the HCMM model [5]) using information about physical encounters logged by the users' mobile devices. The main features of our algorithm are: (i) the capacity of detecting social communities induced by physical co-location of users through distributed algorithms, (ii) the capacity to detect users belonging to more communities (thus acting as bridges across them), and (iii) the capacity to detect the time evolution of communities.

关键词： Communities Mobile handsets Heuristic algorithms Peer-to-peer computing Clustering algorithms Entropy Psychology

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Breast Deformation Modelling: Comparison of Methods to Obtain a Patient Specific Unloaded Configuration

Breast Deformation Modelling: Comparison of Methods to Obtai...

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conference on Medical Imaging - Image-Guided Procedures, Robotic Interventions, and Modeling

作者： Eiben, Bjorn Vavourakis, Vasileios Hipwell, John H. Kabus, Sven Lorenz, Cristian Buelow, Thomas Hawkes, David J. UCL Ctr Med Image Computing Gower St London England Philips Res Hamburg Germany

ISBN: (纸本)9780819498298

In biomechanical simulations of the human breast, the analysed geometry is often reconstructed from in vivo medical imaging procedures. For example in dynamic contrast enhanced magnetic resonance imaging, the acquired geometry of the patient's breast when lying in the prone position represents a deformed configuration that is pre-stressed by typical in vivo conditions and gravity. Thus, physically realistic simulations require consideration of this loading and, hence, establishing the undeformed configuration is an important task for accurate and reliable biomechanical modelling of the breast. We compare three different numerical approaches to recover the unloaded configuration from the loaded geometry given patient-specific biomechanical models built from prone and supine MR images. The algorithms compared are: (i) the simple inversion of gravity without the consideration of pre-stresses, (ii) an inverse finite deformation approach and (iii) a fixed point type iterative approach which uses only forward simulations. It is shown that the iterative and the inverse approach produce similar zero-gravity estimates, whereas the simple inversion of gravity is only appropriate for small or highly constrained deformations.

关键词： Biomechanical modelling unloaded state iterative fixed-point algorithm inverse design

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Self-adapted Frame Selection Module: Refine the Input Strategy for Video Saliency Detection 21st

Self-adapted Frame Selection Module: Refine the Input Strate...

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21st International conference on algorithms and Architectures for Parallel Processing (ICA3PP)

作者： Wu, Shangrui Wang, Yang Wang, Tian Jia, Weijia Xie, Ruitao Beijing Normal Univ BNU Zhuhai BNU UIC Inst Artificial Intelligence & Future Net Zhuhai Guangdong Peoples R China Southwest Petr Univ Chengdu Sichuan Peoples R China BNU HKBU United Int Coll Guangdong Key Lab AI & Multimodal Data Proc Zhuhai Peoples R China Shenzhen Univ Shenzhen Peoples R China

ISBN: (纸本)9783030953881;9783030953874

Video saliency detection is intended to interpret the human visual system by modeling and predicting while observing a dynamic scene. This method is currently widely used in a variety of devices, including surveillance cameras and Internet-of-Things sensors. Traditionally, each video contains a large amount of redundancies in consecutive frames, while the common practices concentrate on extending the range of input frames to resist the uncertainty of input images. In order to overcome this problem, we propose Self-Adapted Frame Selection (SAFS) module that removes redundant information and selects frames that are highly informative. Furthermore, the module has high robustness and extensive application dealing with complex video contents, such as fast moving scene and images from different scenes. Since predicting the saliency map across multiple scenes is challenging, we establish a set of benchmarking videos for the scene change scenario. Specifically, our method combined with TASED-NET achieves significant improvements on the DHF1K dataset as well as the scene change dataset.

关键词： Video saliency detection Mobile edge computing Deep learning Refine input frames

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Towards Highly Compressed CNN Models for Human Activity Recognition in Wearable devices 26

Towards Highly Compressed CNN Models for Human Activity Reco...

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26th IEEE Signal Processing: algorithms, Architectures, Arrangements, and Applications, SPA 2023

作者： Gkountelos, Dimitrios Kokhazadeh, Milad Bournas, Charalampos Keramidas, Georgios Kelefouras, Vasilios Aristotle University of Thessaloniki School of Informatics Thessaloniki Greece An Applied Materials Company Think Silicon S.A. Patras Greece University of Plymouth School of Engineering Computing and Mathematics Plymouth United Kingdom

ISBN: (纸本)9798350304985

The widespread usage of wearables set the foundations for many new applications that process the wearable sensor data. Human Activity Recognition (HAR) is a well-studied application that targets to classify the data captured by multiple wearable sensors into one of a predefined set of activity classes. Earlier approaches in the area relied on Machine Learning (ML) classifiers, while many researchers proposed solutions based on Deep Neural Networks (DNNs), e.g., using Long Short-Term Memory (LSTMs) or Convolution Neural Network (CNNs). Even though the usage of DNNs for HAR is a widely explored field, the problem of compressing (thus reducing the computational requirements) the resulting DNN models has been disregarded by the research community. This is of paramount importance if we consider that wearables are characterized by scarce memory and computational resources. In this work, we first analyze the impact of the size of the various CNN components (focusing on the convolution and dense layers) to the model validation performance. As a second step, we focus on two CNN models with diverse memory characteristics (the lean and the fat model) and we employ three different compression techniques (Filter-Based Pruning -FBP,- Low Rank Factorization -LRF,- and dynamic range quantization) assuming various compressibility scenarios. © 2023 Division of Signal Processing and Electronic Systems, Poznan University of Technology (DSPES PUT).

关键词： Neural network models

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A Novel Two-Stage Feature Selection Framework for Efficiently Diagnosing Alzheimer's Disease 7

A Novel Two-Stage Feature Selection Framework for Efficientl...

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7th International conference on Data Science and Information Technology, DSIT 2024

作者： Lu, Pinya Gao, Wenzhao Pan, Jie Yang, Hongqin Ding, Xuemei Fujian Normal University College of Computer and Cyber Security Fuzhou China Ulster University School of Computing Engineering & Intelligent Systems NI Derry-Londonderry United Kingdom Xiamen Jingyi Zhikang Technology Company Xiamen China Fujian Normal University College of Photonic and Electronic Engineering Fuzhou China

ISBN: (纸本)9798350384093

Research focus on the trade-off between diagnostic accuracy for Alzheimer's disease (AD) and time management for diagnosis is very limited. This study proposes a novel two-stage feature selection framework integrating variance inflation factor (VIF) and NSGA-ii optimization algorithm to obtain a set of sub-items of cognitive and neuropsychological assessments (CNAs) with high diagnostic accuracy and short managing time. What sets the proposed framework apart is that it 1) mitigates multicollinearity issues caused by multiple types of feature selection algorithms employed on multiple CNAs and 2) has the multi-objective optimization capacity of searching Pareto solutions in a reduced decision space. Crucially, we design a VIF-based fast forward search for feature selection which takes into account the cost of managing time for CNAs. Experimental results demonstrate a significantly shortened managing time of 905 seconds (reduced by two-third), with a slightly improved AUC performance of 0.9113 for classifying cognitively normal controls, mild cognitive impairments, and AD patients based on a set of selected combination of sub-items compared to their involved full CNAs, thereby offering promising prospects for accurate diagnosis and fast assessment in clinical practice. © 2024 IEEE.

关键词： Neurodegenerative diseases

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Novel growth and device concepts for high-efficiency InGaN quantum wells light-emitting diodes

Novel growth and device concepts for high-efficiency InGaN q...

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conference on Lasers and Electro-Optics (CLEO)

作者： Hongping Zhao Guangyu Liu Xiao-Hang Li Yik-Khoon Ee Hua Tong Jing Zhang G.S. Huang Nelson Tansu Center for Optical Technologies Department of Electrical and Computer Engineering Lehigh University Bethlehem PA USA

The growths and characteristics of staggered InGaN quantum wells (QWs) and type-ii InGaN-GaNAs QWs are presented for high-efficiency green-emitting light-emitting diodes (LEDs). Approaches for enhancing internal-quant... 详细信息

ISBN: (纸本)9781557528896

关键词： Light emitting diodes Radiative recombination Current density Power generation Gallium nitride Wave functions Power measurement Quantum computing Optical devices Quantum well devices

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A battery level aware MADM combination for the vertical handover decision making 13

A battery level aware MADM combination for the vertical hand...

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13th International Wireless Communications and Mobile computing conference (IWCMC)

作者： Mansouri, Mouad Leghris, Cherkaoui Hassan II Univ Dept Comp Sci L M Lab FSTRTM Team Casablanca Morocco

ISBN: (纸本)9781509043729

The internet services became so various, that the number of its users is exponentially increased these last two decades, and wireless technologies are developed as well. Nowadays, people are willing to use mobile devices to connect wirelessly anywhere, anytime and to any available technology under the ABC (Always Best Connected) concept. To access the bet service wirelessly, mobile nodes "MNs" try to connect to the best wireless network technology available anytime, even when quitting the base station or access point area to one another, or changing the wireless access type, which is called vertical handover (VH). This supposes that the MN must connect to the wireless network available, that offers the best quality of service (QoS), without session breaks. To reach this objective, VH decision-making need to be quick and efficient to determine which wireless technology is the best, among those available anytime. Thus, we are seeking to optimize the network selection phase in the process of VH. Several network selection algorithms have been used, based on different theories, such as basic algorithms (based on simple metrics), Neural Networks models, Gaming theory algorithms and Multi Attributes Decision Making (MADM) methods. This paper presents a comparison of different MADM methods, taking into account an important criterion which is the battery level, so as to determine which method makes the best VH decisions, while extending the MN's battery life.

关键词： MADM methods Mobile networks Network selection Vertical handover Wireless networks

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Parameterizable implementation of full search block matching algorithm using FPGA for real-time applications

Parameterizable implementation of full search block matching...

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IEEE International Caracas conference on devices, Circuits and Systems

作者： M. Mohammadzadeh M. Eshghi M.M. Azadfar ECE Faculty Shahid Beheshti University Electrical and Computer Engineering Faculty Shahid Beheshti University Multimedia and Signal Processing Group Iran Telecommunication Research Center

In this paper, a systolic array architecture for FSBMA is implemented by RTL-level VHDL for using as a motion estimation unit in low bit rate and real-time applications such as video telephony. This implementation is synthesized for two FPGA families, Xilinx Spartan ii and Xilinx Virtex ii and the results for area occupation and maximum opening frequency are presented. The results show it is possible to implement real-time video encoding systems with motion estimation, on a single FPGA chip.

关键词： Field programmable gate arrays Systolic arrays Signal processing algorithms Application software Motion estimation Hardware Bandwidth Redundancy Telecommunication computing Array signal processing

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Parallel performance of "Synchrotron Radiation Workshop" code: partially coherent calculations for storage rings and time-dependent calculations for XFELs 5

Parallel performance of "Synchrotron Radiation Workshop" cod...

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conference on Advances in Computational Methods for X-Ray Optics V

作者： He, A. Chubar, O. Rakitin, M. Samoylova, L. Fortmann-Grote, C. Yakubov, S. Buzmakov, A. Brookhaven Natl Lab Natl Synchrotron Light Source 2 Upton NY 11973 USA European XFEL GmbH D-22869 Schenefeld Germany German Electron Synchrotron DESY D-22607 Hamburg Germany RAS FSRC Crystallog & Photon Moscow 119333 Russia

ISBN: (数字)9781510637931

ISBN: (纸本)9781510637931;9781510637924

The "Synchrotron Radiation Workshop" (SRW) computer code is extensively used for the development of insertion devices (IDs) and X-ray beamlines at the National Synchrotron Light Source ii and at other light source facilities. Among frequently used types of SRW calculations are the calculations of spontaneous emission from an ID in a storage ring, physical optics based simulations of propagation of this partially-coherent radiation through a beamline, and the simulations of propagation of 3D time-dependent radiation pulses through instruments of X-ray Free-Electron Lasers (XFELs). The two types of radiation propagation calculations are CPU-intensive, therefore for each of them parallel algorithms have been developed in SRW. For the storage ring related calculations, the parallel processing was implemented using the Message Passing Interface (MPI). For the XFEL calculations, a shared memory approach provided by the Open Multi-Processing (OpenMP) was adopted. The two parallelization methods, and their implementation in SRW, have different advantages and drawbacks: the MPI-parallelization of partially-coherent calculations for storage rings has a good scaling, but over-consumes memory, whereas the OpenMP-parallelization of time-dependent XFEL calculations is memory-efficient, but it can only scale within one multi-core server. We are reporting the results of the efficiency tests of these two types of parallel calculations, obtained for representative optical schemes. The tests were performed on an isolated server as well on a large computer cluster - the US DOE's NERSC scientific computing facility.

关键词： SRW XFEL storage ring synchrotron radiation radiation propagation partially-coherent calculations parallel computing MPI OpenMP

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Investigation of In_xGa_{1-x}As Ultra-Thin-Body Tunneling FETs Using a Full-Band and Atomistic Approach

Investigation of In_xGa_{1-x}As Ultra-Thin-Body Tunneling FE...

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International conference on Simulation of Semiconductor Processes and devices (SISPAD)

作者： Mathieu Luisier Gerhard Klimeck Network for Computational Nanotechnology Purdue University West Lafayette IN USA

Using a 2-D, full-band, atomistic, quantum mechanical simulator based on the sp 3 d 5 s * tight-binding method with spin-orbit coupling, we investigate the performances of single- and double-gate relaxed In x Ga 1-x As p-i-n ultra-thin-body (UTB) tunneling field-effect transistors (TFETs) with 20 nm to 50 nm gate lengths. The ON-current, OFF-current leakage, and subthreshold slope (SS) properties are analyzed as function of the In concentration in 5 nm thick structures. We find (i) that devices with a high In concentration allow more ON-current, but suffer from higher OFF-currents and lower SS, (ii) that double-gate devices perform better than single-gate ones, and (iii) that a longer gate length reduces the source-to-drain tunneling leakage and the OFF-current of the UTB TFETs.

关键词： Tunneling Computational modeling Poisson equations iiI-V semiconductor materials photonic band gap Sparse matrices Atomic layer deposition Effective mass Double-gate FETs Quantum computing

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