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IEEE Symposium on computers and communications (ISCC)

作者： Lucas N. Silva Paulo H.L. Rettore Vinicius F.S. Mota Bruno P. Santos Dept. of Computer and Systems Federal University of Ouro Preto Joao Monlevade Brazil Dept. of Communication Systems Fraunhofer FKIE Bonn Germany Dept. of Computer Science Federal University of Espirito Santo Vitória Brazil

ISBN: (数字)9781665497923

ISBN: (纸本)9781665497930

Due to the increasing location-aware devices, mobility traces datasets have become an essential source for smart cities planning. Given this scenario, we propose MobVis, a framework to characterize mobility traces through different metrics, allowing comparisons between different mobility traces in a simplified way. Furthermore, MobVis can extract and visualize spatial, temporal, and social aspects of mobility data through a Web interface. MobVis architecture has five main components: input data; data preparation; data processing and analysis to extract mobility metrics; visualization; and a web interface. To demonstrate the framework's process, we created a use case analyzing the characteristics of two distinct traces (Taxi and IoT-Objects). Then, through different metrics, we evaluated the data in two aspects: i) descriptive, through a set of graphics and quantitative data that enables characterizing each trace; and ii) comparative, presenting the main differences between the traces.

关键词： Measurement Graphics Data analysis Smart cities Data visualization Libraries Service-oriented architecture

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Team Precoding Towards Scalable Cell-free Massive MIMO networks 55

Team Precoding Towards Scalable Cell-free Massive MIMO Netwo...

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55th Asilomar Conference on Signals, systems and computers, ACSSC 2021

作者： Miretti, Lorenzo Bjornson, Emil Gesbert, David EURECOM Communication Systems Dept. Sophia Antipolis France KTH Royal Institute of Technology Dept. of Computer Science Stockholm Sweden Dept. of Electrical Engineering Linköping University Linköping Sweden

ISBN: (纸本)9781665458283

In a recent work, we studied a novel precoding design for cell-free networks called team minimum mean-square error (TMMSE) precoding, which rigorously generalizes centralized MMSE precoding to distributed operations based on transmitter-specific channel state information (CSI). Despite its flexibility in handling different cooperation regimes at the CSI sharing level, TMMSE precoding assumes network-wide sharing of the data bearing signals, and hence it is inherently not scalable. In this work, inspired by recent advances on scalable cell-free architectures based on user-centric network clustering techniques, we address this issue by proposing a novel version of the TMMSE precoding design covering partial message sharing. The obtained framework is then successfully applied to derive a variety of novel, optimal, and efficient precoding schemes for a user-centric cell-free network deployed using multiple radio stripes. Numerical simulations of a typical industrial internet-of-things scenario corroborate the gains of TMMSE precoding over competing schemes in terms of spectral efficiency under different power constraints. Although presented in the context of downlink precoding, the results of this paper may be applied also on the uplink. © 2021 IEEE.

关键词： Mean square error

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Physical and System Level Power Reduction Technique for NoC Architectures: Overview of State of the Art

Physical and System Level Power Reduction Technique for NoC ...

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Decision Aid sciences and Application (DASA), International Conference on

作者： Djalila Belkebir Abdelhai Lati Malak Belkebir Faculty of New Information and Communication technologies Kasdi Merbah Ouargla University (UKMO) Ouargla Algeria Dept. Mathematics and Computer Science Research Laboratory on Computer Science's Complex Systems University of Oum El Bouaghi Oum El Bouaghi Algeria

Power dissipation and energy consumption are key factors for the performance improvement of modern technology systems. In recent years, several strategies have been proposed to solve the power management issues on embedded systems. In this paper, we classify the state of the art of those techniques. Classification is done based on run-time, activation, and idle state of the different components of the network on chip (NoC). We illustrate the requirement of power management based on several important parameters. A highlight is put on the drawbacks and benefits. Also, classification is done based on different NoC abstraction levels. However, by this paper, we intend to guide the researchers and application developers in getting insights about the strategies of power management techniques that will lead to the design of more efficient high performances in embedded systems of the future.

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Comparison of Mel Frequency Cepstral Coefficient (MFCC) and Mel Spectrogram Techniques to Classify Industrial Machine Sound

Comparison of Mel Frequency Cepstral Coefficient (MFCC) and ...

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International Conference on Software, Knowledge Information, Industrial Management and Applications (SKIMA)

作者： Nur Fatinah Hafiz Syamsiah Mashohor M. H. S. E. M. A. Shazril M. Fadlee A. Rasid Azizi Ali Dept. of Computer and Communication Systems Engineering Faculty of Engineering Universiti Putra Malaysia Serdang Selangor Malaysia Wireless and Photonic Networks Research Centre Of Excellence (WiPNET) Universiti Putra Malaysia Serdang Selangor Malaysia

The utilization of sound recognition to detect the faulty machines are getting the interest to be explored with the technology advancement in IR 4.0. In this paper, we investigated the performance of two acoustic features in representing the sound of a fan in industrial machines, that is acquired from the MIMII dataset. The Mel Frequency Cepstral Coefficient (MFCC) and Mel Spectrogram techniques are explored and compared in this paper. The classification is performed using Convolutional Neural Network (CNN) with the input of images from both techniques. The dataset of the input images are the audio files of 6dB fans sound in industrial machine. The results suggest that Mel Spectrogram is an effective feature for faulty machine sound recognition when used with CNN model.

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3D Visualization of Femoral Shaft Fractures

3D Visualization of Femoral Shaft Fractures

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International Conference on Artificial Intelligence and Data sciences (AiDAS)

作者： Lam Xin Mi Saw Seow Hoon Khor Siak Wang Saw Seow Hui Dept. of Information Systems Faculty of Information and Communication Technology UTAR Perak Dept. of Allied Health Sciences Dr. WLT-CRCD UTAR Sg. Long Faculty of Science UTAR Perak Department of Computer Science Faculty of Information and Communication Technology UTAR Perak

The absence of an independent learning platform to address femoral shaft fractures poses challenges in understanding and classifying these fractures. The existing anatomy platforms, such as 3D interactive anatomical atlases, are insufficient in providing comprehensive information on the fractures and the high cost of these interactive anatomical atlases can be a barrier for learning to proceed due to the needs of the actual bones and human models. This study aims to develop an accessible, cost-effective educational 3D mobile application that caters to the learning needs associated with human femoral shaft fractures. Although femoral fractures are relatively uncommon, the increased cases of fractures necessitate awareness and preparedness among individuals as well as medical professionals. The proposed mobile application will enhance users' understanding of anatomical structures in femoral shaft fractures and contribute to improved patient care as well as enhance medical education.

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Cybernated Watermarking Approach on Image with Cryptographic Encryption

Cybernated Watermarking Approach on Image with Cryptographic...

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computer, communication and Control (IC4), International Conference on

作者： R. Sivasankari T Veeramakali S M Mustafa Nawaz P. Prakash P Umadevi A Alvin Ancy Dept. of Computer Science and Engineering B.S.Abdur Rahman Crescent Institute of Science and Technology Dept of Data Science and Business Systems School of Computing SRM Institute of Science and Technology Kattankulathur Tamilnadu Dept of Computer Science and Engineering Sri Sai Ram Institute of Technology Dept of Electronics and Communication Engineering Sri Sai Ram Engineering College Department of S & H KPR Institute of Engineering and Technology Coimbatore Dept of Electronics and Communication Engineering Anna University Chennai

Digital watermarking of interactive media content has become an active experimentation field in recent years. In addition to reviewing some of the methods that have been developed for various media types; a general structure for watermark engrafting and identification is outlined. We highlight a few of these application-oriented differences, including copyright protection, substantiation, tamper identification, and data hiding, as well as the technological and system conditions for different media types such as digital photos, digital files, digital audio, and text. We describe a general structure for digital watermarking-based image copyright protection in this approach. In this paper, we outline the pre-processing and implementation of tide marking technique where Twofish algorithm and double encryption is described. The image processing toolbox is also specified by comparing five different image processing techniques. In addition, the post implementation is carried out with the wavelet toolbox and matlab coder to analyze signal, image properties and generate the efficient code for embedding the text.

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5G New Radio Techniques for 3D networks in Connection-critical Scenarios

5G New Radio Techniques for 3D Networks in Connection-critic...

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IEEE Conference on Aerospace

作者： Luca Valcarenghi Justine Cris Borromeo Riccardo Bassoli Frank H.P. Fitzek Koteswararao Kondepu Nicola Andriolli Henok Berhanu Tsegaye Claudio Sacchi Scuola Superiore Sant’Anna Pisa Italy Deutsche Telekom Chair of Communication Networks Technische Universitaet at Dresden Dresden Germany Department of Computer Science and Engineering Indian Institute of Technology Karnataka India University of Pisa Pisa Italy Dept. of Information Engineering and Computer Science (DISI) University of Trento Trento Italy Department of Electrical and Computer Engineering The University of New Mexico Albuquerque (NM) NM

The recent natural disasters, such as the Earthquake in Morocco in September 2023, have demonstrated one more time the necessity of immediately restoring lost connectivity to rescue victims living in rural villages that are far from urban areas. In such a framework, three-dimensional (3D) Non-Terrestrial networks (NTNs) are expected to provide continuous wireless coverage at low Average Revenue Per User (ARPU), in disaster-hit and hotspot areas with the help of 5G New Radio (NR). This paper investigates the use of Unmanned Aerial Vehicles (UAV) as transparent aerial networks that perform signal amplification and frequency conversion between a satellite-based 5G network and a User Equipment (UE) using five different frequency bands (i.e., S-band, C-band, X-band, Ku-band, and Ka-band) supporting the satellite communication. The applications of the proposed technology concern connection-critical scenarios like emergency rescue and digital divide mitigation. Results show that 180Mbps to 4.85Gbps throughput can be achieved on the satellite-to-UAV link. Simulated transmission delay and average session time are also evaluated considering a delay budget of 2ms. The related results discussion confirms the viability and effectiveness of the proposed approach in the concerned case of study.

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Mobility Prediction at the Tactical Edge: A Handover for Centralized/Decentralized networks

Mobility Prediction at the Tactical Edge: A Handover for Cen...

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International Conference on Military communications and Information systems (ICMCIS)

作者： Merlin von Rechenberg Johannes F. Loevenich Philipp Zißner Paulo H. L. Rettore Roberto Rigolin F. Lopes Peter Sevenich Dept. of Communication Systems Fraunhofer FKIE Bonn Germany Institute of Computer Science 4 University of Bonn Bonn Germany Department of Mathematics/Computer Science University of Osnabrück Bonn Germany Secure Communications & Information (SIX) Thales Deutschland Ditzingen Germany

This paper presents a mobility prediction model as part of a handover mechanism combining centralized and decentralized network control to improve performance and resilience in tactical networks. Our approach utilizes mobility prediction to optimally switch between control modes, minimizing packet loss from live user data flows and maximizing the duration of centralized control connectivity. The prediction model ingests mobility trace files, extracts supplementary mobility features, and employs a Recurrent Neural Network (RNN) to forecast system states representing the network link quality. We evaluate the model using two mobility paradigms: Gauss-Markov and Manhattan-Grid. For the Gauss-Markov model, our method achieves 44% accuracy in predicting network states 60 seconds into the future and up to 72% accuracy for 5-second predictions. Our approach exhibits higher accuracy with the Manhattan-Grid model, attaining 67% and 82% for 60 and 5-second predictions, respectively. A comparative analysis with a previously implemented RSSI-based mechanism demonstrates that our prediction-based mechanism enhances centralized control connectivity duration by 56% and mitigates packet loss by 1.24%. This work contributes to advancing adaptive handover mechanisms for complex tactical networks.

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Adaptive Control for Shunt Active Power Filter under Stochastic Solar Photovoltaics Behavior

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IEEE Journal of Emerging and Selected Topics in Power Electronics 2025年

作者： Prakash, Surya Alkhatib, Mohamed Sindi, Hatem F. Alghamdi, Sultan Behera, Ranjan Kumar Muduli, Utkal Ranjan Nit Jamshedpur Dept. of Electrical Engg Jharkhand Jamshedpur India Uae University Al Ain Dept. of Electrical and Communication Engg Coe Abu Dhabi15551 United Arab Emirates King Abdulaziz University Center of Research Excellence in Renewable Energy and Power Systems Department of Electrical and Computer Engineering Faculty of Engineering Jeddah21589 Saudi Arabia Indian Institute of Technology Patna Dept. of Electrical Engineering Bihta801103 India Khalifa University Apec Dept. of Electrical Engineering and Computer Science Abu Dhabi127788 United Arab Emirates

The paper discusses the challenges in controlling a two-stage photovoltaic (PV)-based shunt active power filter (SAPF) under distorted grid conditions and stochastic PV system behavior. To address this, the paper proposes an adaptive proportional integral (API) regulator to regulate the DC-link voltage, which adapts its parameters based on the DC-link error voltage to provide low bandwidth for disturbance rejection and high bandwidth for dynamic performance enhancement. The paper also proposes an estimation method for the reference current using the sliding discrete Fourier transform and the instantaneous symmetrical component theory, which is suitable for non-ideal grid or load conditions. The accuracy of the proposed reference current estimation method is analyzed using time- and frequency-domain analysis. The performance of the PV-SAPF system with the proposed control algorithms is illustrated through simulation and real-time hardware validation under various grid conditions. Despite distorted grid conditions, the total harmonic distortion of the grid current is substantially within IEEE Std 519-2014. The proposed API regulator and reference current estimation method show promising results in improving the performance of the PV-SAPF system in the presence of internal and external disturbances. © 2013 IEEE.

关键词： Frequency domain analysis

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Mastering Reference Architectures with Modeling Assistants

Mastering Reference Architectures with Modeling Assistants

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Conference on Model Driven Engineering Languages and systems Companion (MODELS-C)

作者： Amleto Di Salle Ludovico Iovino Leonardo Mariani Dept. of Human Sciences European University of Rome Rome Italy Computer Science area Gran Sasso Science Institute L'Aquila Italy Dept. of Informatics Systems and Communication Università degli Studi di Milano-Bicocca Milan Italy

Reference architectures (RA) can significantly simplify and speed up the design and evolution of software systems in virtually any domain. Rather than starting from scratch or trying to reuse models not meant for reuse, software architects can exploit RAs to initiate their designs from rigorously-defined architectural models specifically defined to support reuse. RAs can guarantee the satisfaction of key functional and non-functional requirements, including those related to technical and societal challenges, such as security and sustainability, significantly reducing the design effort and improving the design quality. The growing popularity of RAs is confirmed by the many providers, including Amazon AWS, Microsoft Azure, IBM, and Salesforce, that offer RAs for application deployment on their infrastructures. Unfortunately, RAs are expensive to define since they must comprehensively synthesize the design knowledge of specific application domains (e.g., e-commerce, automotive, etc.) and technical contexts (e.g., cloud systems, mobile apps, IoT, etc.). This challenge limits the availability of RAs to a few domains and contexts, hindering their adoption. We envision the opportunity to facilitate RA-based design by introducing a novel combination of mining in-the-wild and continuous knowledge refinement through a framework named ASSISTRA. Mining in-the-wild consists of bots crawling architectural models at scale (e.g., from public repos) and analyzing them continuously to automatically synthesize RAs and extract RAs-related practices that shall feed knowledge bases. Continuous knowledge refinement consists of a population of recommender systems that, while interactively supporting the architects in their activity using the shared knowledge bases, shall continuously refine the mined content in the knowledge base (e.g., based on architects accepting, modifying, or rejecting suggestions). This process shall generate high-quality recommendations, drastically simplifying the

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