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Using NOMA Scheme for the Management of Interference and the Improvement of Performance in 5G Networks 13

Using NOMA Scheme for the Management of Interference and the...

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13th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops, ICUMT 2021

作者： Bouras, Christos Kokkinos, Vasileios Tzioumanis, Georgios University of Patras Computer Technology Institute and Press Diophantus' Computer Engineering and Informatics Dept. Patras Greece

ISBN: (纸本)9781665402194

The new generation of 5G networks, compared to 4G networks, is a very important example of change in achieving very high frequencies in the carrier with huge bandwidth, high densities with a huge number of antennas and improved quality of services, making effective interference management necessary. In this paper, we present the contribution of the Non-Orthogonal Multiple Access (NOMA) scheme to improving the performance of 5G networks. We refer to the technique of sequential interference cancellation applied to some NOMA formats, compare NOMA and Orthogonal Multiple Access (OMA) formats in terms of the capabilities they offer users and NOMA's significant contribution to Multiple-Input Multiple-Output (MIMO) technology and compare three basic NOMA formats in three different resource and user reporting scenarios. Finally, we present the results of the simulations of the above comparisons and analyze the contribution of each scheme to the improvement of the system performance. and copy;2021 IEEE. © 2021 IEEE computer Society. All rights reserved.

关键词： 5G mobile communication systems

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On the Quantization of Recurrent Neural Networks for Smiles Generation

On the Quantization of Recurrent Neural Networks for Smiles ...

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Adriano Durao Joel P. Arrais Bernardete Ribeiro Gabriel Falcao Instituto de Telecomunicações Dept. of Electrical and Computer Engineering University of Coimbra Portugal CISUC Dept. of Informatics Engineering University of Coimbra Portugal

This paper focuses on the effects of applying quantization during training to Recurrent Neural Networks (RNNs) used in Simplified Molecular-Input Line-Entry System (SMILES) generation, a form of line notation for molecular information used in the development of pharmaceutical drugs, from the PubChem database. It offers the flexibility to choose the precision used by the model, by defining the number of bits at each layer. The RNNs are the focus of the current study, by comparing the performance of three of the most used algorithms, Simple RNN, Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU). The models were trained on a selection of SMILES. By exploiting the QK-eras library, quantization performance was compared to their floating-point equivalent for several combinations of parameters. The goal of the testing program developed is to generate a large number of novel SMILES, facilitating the process of Drug Discovery which is traditionally long, and thus very expensive and difficult. By understanding how the behavior of quantized networks deviates from the regular model, in relation to the parameters used, we are able to control the process of choosing whether to quantize a model and to which degree it becomes more or less efficient. In this study, we observed good performance even for 4-bit models making use of LSTM and GRU layers, the same way we concluded that Simple RNN quantization does not compensate the effort.

关键词： Training Drugs Quantization (signal) Recurrent neural networks Process control Logic gates Natural language processing

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Drone-to-drone Collision Detection Algorithm in Flight Traffic Management

Drone-to-drone Collision Detection Algorithm in Flight Traff...

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International Electronics Symposium (IES)

作者： Muhajirin Ida Ilyas Idris Winarno Dadet Pramadihanto Dept. of Information and Computer Politeknik Elektronika Negeri Surabaya Surabaya Indonesia Dept. of Informatics and Computer Engineering Politeknik Elektronika Negeri Surabaya Surabaya Indonesia

This paper presents an algorithm for detecting collisions in flight traffic management for drones. The algorithm is simple to implement and can be used to effectively manage the flow of drones in a safe and efficient manner. The algorithm has been tested in simulation and has been shown to be effective in detecting collisions between drones. The algorithm is also simple to implement and can be used with existing drone traffic management systems. As the number of drones in the sky continues to grow, this algorithm will become increasingly important for ensuring the safety of drone operations.

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Trusted Access to 6G Testbeds Through a Security Intent-Driven Software-Defined Perimeter Framework 29

Trusted Access to 6G Testbeds Through a Security Intent-Driv...

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29th IEEE International Workshop on computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2024

作者： Fernandez-Martinez, Carolina Bikos, Anastasios Verikoukis, Christos Siddiqui, Shuaib i2CAT Foundation Barcelona08034 Spain Universitat Pompeu Fabra Dept. of Information and Communication Technologies Barcelona08018 Spain Iquadrat Informatica Sl Barcelona08006 Spain Universitat Politècnica de Catalunya Dept. of Signal Theory and Communications Barcelona08034 Spain Industrial Systems Institute Athena Research Center Patras26504 Greece University of Patras Dept. of Computer Engineering and Informatics Patras26504 Greece

ISBN: (纸本)9798350377644

Parallel to the evolution of recent trends in the cybersecurity industry and the increase of cyberattacks in the last few years, there is renovated interest on the application of software-defined techniques to enforce best security practices, such as in the Software-Defined Perimeter specification and the Zero Trust architectures. This work proposes a software-defined network segmentation and access control framework aligned with these principles. This solution captures minimal security requirements from testbed operators to establish ad-hoc, isolated connectivity and access control for end-users (experimenters) interacting with exposed endpoints from the exposed services in the cloud testbeds. The elicited architecture, design decision and initial implementation are introduced. © 2024 IEEE.

关键词： Testbeds

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Digital Map Generation Workflow Demonstrated on ZalaZONE Automotive Proving Ground Elements 36

Digital Map Generation Workflow Demonstrated on ZalaZONE Aut...

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36th IEEE/IFIP Network Operations and Management Symposium, NOMS 2023

作者： Somogyi, Árpád Tettamanti, Tamás Varga, Pál Szalay, Zsolt Baranyai, Dániel Lovas, Tamás Budapest University of Technology and Economics Fac. of Civil Engineering Dept. of Photogrammetry and Geoinformatics Budapest Hungary Institute for Computer Science and Control The Eötvös Loránd Research Network Systems and Control Laboratory Budapest Hungary Budapest University of Technology and Economics Fac. of Electrical Engineering and Informatics Dept. of Telecommunications and Media Informatics Budapest Hungary Budapest University of Technology and Economics Fac. of Transportation Eng. and Vehicle Eng. Dept. of Automotive Technologies Budapest Hungary

ISBN: (纸本)9781665477161

One major goal of digital twin technology applied in the Architecture, engineering, and Construction (AEC) Industry is the mapping of roads and road environments with their associated information. Such digital twins can support cost-effective testing, simulations, and the production of mapping backgrounds for automated vehicles and generally for Cooperative, Connected and Automated Mobility (CCAM) developments. The efficient workflow that leads from data acquisition to finished products depends on a number of requirements and knowledge sets. The main contribution of the paper is a general methodology of creating HD-map from point cloud and image data set. Accordingly, the most widely used survey techniques are presented and the requirements for the objects to be derived are summarized. The paper then outlines a general implementation procedure as an expert knowledge through a real-life example, where the results obtained for the ZalaZONE Automotive Proving Ground are demonstrated. © 2023 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Distributed and Biometric Signature-Based Identity Proofing System for the Maritime Sector

Distributed and Biometric Signature-Based Identity Proofing ...

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International Conference on computer Science and engineering (UBMK)

作者： Taylan Akbas Ahmet Koltuksuz Cagatay Yucel Dept. of Computer Engineering School of Eng. Yasar University Izmir Turkiye Dept. of Computing and Informatics Bournemouth University UK

The maritime sector is an industry that faces significant and various challenges related to cyber security and data management, such as fraud and user authentication. Therefore, there is a need for a secure solution that can effectively manage data transactions while resolving digital identity. A biometric signature application in blockchain for fighting fraud and fake identities may provide a solution in the maritime sector. This research proposes a biometric signature and an IPFS network-blockchain framework to address these challenges. This paper also discusses the proposed framework's cyber security challenges that threaten behavioral biometric security.

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Carotid plaque stroke risk assessment using multiscale AM-FM analysis based on DoG filterbanks

Carotid plaque stroke risk assessment using multiscale AM-FM...

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International Conference on Digital Signal Processing (DSP)

作者： Kyriacos P. Constantinou Ioannis P. Constantinou Marios S. Pattichis Efthyvoulos Kyriacou Constantinos S. Pattichis Dept. of Computer Science University of Cyprus Nicosia Cyprus Istognosis Ltd Nicosia Cyprus Dept. of Electrical and Computer Engineering University of New Mexico Albuquerque NM USA Dept. of Electrical Engineering Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus

The objective of this work was the investigation of multiscale Amplitude Modulation - Frequency Modulation (AM-FM) analysis based on Difference of Gaussians (DoG) filterbanks representations in order to predict the risk of stroke by analysing carotid plaques ultrasound images of individuals with asymptomatic carotid stenosis. We computed the instantaneous amplitude, instantaneous phase and the magnitude of instantaneous frequency to extract histogram features on each plaque region. The Support Vectors Machine classifier was implemented to classify asymptomatic versus symptomatic plaques. A dataset of 100 carotid plaque images (50 asymptomatic and 50 symptomatic) were tested, and showed that the AM-FM features based on DoG filterbanks and simple histograms performed better than the traditional AM-FM features. Best results were obtained when an eight scale filterbank with a combination of scales was used reaching the accuracy of 75%.

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Information Storage and Retrieval System for a Molecular Dynamics Based Digital Twin of Materials

Information Storage and Retrieval System for a Molecular Dyn...

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2022 IEEE International Multi-Conference on engineering, computer and Information Sciences, SIBIRCON 2022

作者： Topolsky, Dmitry Belyakov, Alexander Pochinskaia, Veronica Topolskaya, Irina Yumagulov, Nikolay Fedorov, Dmitry South Ural State University Dept. of Electronic Computing Machines Chelyabinsk Russia South Ural State University Dept. of Energy and Power Engineering Chelyabinsk Russia Nizhnevartovsk State University Dept. for Education in Physics and Mathematics Name of Organization Nizhnevartovsk Russia Surgut State University Dept. of Informatics and Computer Engineering Surgut Russia

ISBN: (纸本)9781665464802

Digital twin technology becomes an appropriate respond to the new challenge of rapid development in science and industry. Chemical data include the information about structure and properties of materials and compounds. Machine learning technology can help to predict properties of innovative compounds and material, but it takes enormous amount of raw data. The implementation of digital twin technology in spectral and molecular dynamics helps to reduce risks introducing the innovations. Large systems technologies are used in multiscale modeling of materials with computer programs. The world experience of chemical data aggregation and storage is based on specialized databases creation. Disunity of data sources demands a single multiscale data model to operate raw data and amend the accuracy of prediction. To collect and analyze unstructured data full-text search and distributed computing were applied. In respond to perpetual raw data expansion a Data Lake technology is used to store, analyze and search for information of atomic and molecular systems. © 2022 IEEE.

关键词： Big data

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Approximating Edit Distance in the Fully Dynamic Model

Approximating Edit Distance in the Fully Dynamic Model

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Annual IEEE Symposium on Foundations of computer Science

作者： Tomasz Kociumaka Anish Mukherjee Barna Saha Max Planck Institute for Informatics Saarland Informatics Campus Saarbrücken Germany Dept. of Computer Science University of Warwick Coventry UK Dept. of Computer Science & Engineering University of California San Diego US

The edit distance is a fundamental measure of sequence similarity, defined as the minimum number of character insertions, deletions, and substitutions needed to transform one string into the other. Given two strings of length at most n, a simple dynamic programming computes their edit distance exactly in $\mathcal{O}\left(n^{2}\right)$ time, which is also the best possible (up to subpolynomial factors) assuming the Strong Exponential Time Hypothesis (SETH). The last few decades have seen tremendous progress in edit distance approximation, where the runtime has been brought down to subquadratic, to near-linear, and even to sublinear at the cost of approximation. In this paper, we study the dynamic edit distance problem where the strings change dynamically as the characters are substituted, inserted, or deleted over time. Each change may happen at any location of either of the two strings. The goal is to maintain the (exact or approximate) edit distance of such dynamic strings while minimizing the update time. The exact edit distance can be maintained in $\mathcal{O}\left(n \log ^{2} n\right)$ time per update (Charalampopoulos, Kociumaka, Mozes; 2020), which is again tight assuming SETH. Unfortunately, even with the unprecedented progress in edit distance approximation in the static setting, strikingly little is known regarding dynamic edit distance approximation. Utilizing the best near-linear-time (Andoni, Nosatzki; 2020) and sublinear-time (Goldenberg, Kociumaka, Krauthgamer, Saha; 2022) approximation algorithm, an old exact algorithm (Landau and Vishkin; 1988), and a generic dynamic strings implementation (Mehlhorn, Sundar, Uhrig; 1996), it is possible to achieve an $\mathcal{O}\left(n^{c}\right)$-approximation in $n^{0.5-c+o(1)}$ update time for any constant $c \in\left[0, \frac{1}{6}\right]$. Improving upon this trade-off, characterized by the approximation-ratio and update-time product $n^{0.5+o(1)}$, remains wide open. The contribution of this work is a dynami

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DCGAN-based Medical Image Augmentation to Improve ELM Classification Performance 11

DCGAN-based Medical Image Augmentation to Improve ELM Classi...

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11th IEEE International Conference on Communication, Networks and Satellite, COMNETSAT 2022

作者： Rando Setiawan, Noor Akhmad Permanasari, Adhistya Erna Rulaningtyas, Riries Suksmono, Andriyan Bayu Sitanggang, Imas Sukaesih Universitas Gadjah Mada Dept. of Electrical and Information Engineering Yogyakarta Indonesia Biomedical Engineering Program Dept. of Physics Universitas Airlangga Surabaya Indonesia Institut Teknologi Bandung School of Electrical Engineering and Informatics Bandung Indonesia Ipb University Department of Computer Science Bogor Indonesia

ISBN: (纸本)9781665460309

Cervical cancer is one of the deadliest diseases in women. One of the cervical cancer screening methods is pap smear method. However, using a pap smear method to detect cervical cancer takes a long time for a pathologist to diagnose. Hence, a rapid development of medical computerization for early detection to get the results quickly is needed. This paper proposes synthetic data augmentation by using Deep Convolutional Generative Adversarial Network (DCGAN) to increase number of pap smear samples in dataset. Gray Level Co-occurrence Matrix (GLCM) is employed to extract features from dataset. Classification of 3 classes which are Adenocarcinoma, High-Grade Squamous Intraepithelial Lesion (HSIL), and Squamous Cell Carcinoma (SCC) is conducted using Extreme Learning Machine (ELM). The result shows that the addition of synthetic data improves the performance of ELM with the accuracy of 90%. This accuracy is better than the accuracy of ELM using only the original dataset which is 85%. © 2022 IEEE.

关键词： Generative adversarial networks

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