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Neural Evolutionary Architecture Search for Compact Printed Analog Neuromorphic Circuits

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 2024年第7期44卷 2655-2668页

作者： Zhao, Haibin Pal, Priyanjana Hefenbrock, Michael Wang, Yuhong Beigl, Michael Tahoori, Mehdi B. Chair for Pervasive Computing Systems Institute of Telematics Germany Chair of Dependable Nano Computing Institute of Computer Engineering Department of Informatics Germany RevoAI GmbH Germany

Printed electronics (PE) is an additive fabrication technology for manufacturing electronic circuits which not only allows for a highly flexible printing of arbitrary circuit patterns, but also produce soft, non-Toxic, and degradable electronics at an extremely low cost. These properties are unmatched by silicon based electronics, making PE an enabler of new application domains, e.g., fast moving consumer goods, wearables, and disposable healthcare devices. A particularly promising class of circuits in this technology is the printed analog neuromorphic circuits, offering efficient and highly tailored computational functionalities. In this work, we leverage the highly flexible fabrication process of PE to address the bottleneck of PE, i.e., the large feature sizes and low device counts. This issue is crucial, as it impairs the integration of printed circuits into target applications with limited footprint, such as smart band aids. We also propose an evolutionary algorithm (EA) to improve the circuit compactness through circuit architecture optimization. As baseline, we compare the proposed EA method with a state-of-The-Art pruning method and a modified area-Aware pruning method. All of them are able to optimize circuit architecture alongside the component values of printed neuromorphic circuits. Experimental simulation reveals that the proposed EA approach can effectively achieve compact circuits and outperform the pruning method by 3.1× lower area with no loss of accuracy. As a byproduct, the power is reduced by 3.0×, paving the way to energy-harvested printed systems. © 1982-2012 IEEE.

关键词： Flexible electronics

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Improving 5 G base station placement through precise rooftop detection using super-resolution diffusion models and satellite image analysis

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Natural computing 2025年 1-13页

作者： García-Aguilar, Iván Galeano-Brajones, Jesús Luna-Valero, Francisco Carmona-Murillo, Javier Fernández-Rodríguez, Jose David Luque-Baena, Rafael Marcos ITIS Software University of Málaga Málaga Spain Biomedical Research Institute of Málaga (IBIMA) Málaga Spain Merida University Center Department of Computing and Telematics Engineering Mérida Spain

The accurate deployment of 5 G base stations (BSs) in urban environments is essential for achieving optimal network performance. In these scenarios, the most common positions for installing BSs are rooftops, which, however, given the complex topography and diverse building structures, present significant challenges when identifying suitable locations. This paper proposes an enhanced method for rooftop detection, integrating diffusion models based on super-resolution with segmentation using convolutional neural networks. Starting from the input image, a super-resolution model is applied to generate sliding windows on which re-inference is performed, thereby improving both the resolution and prediction accuracy for this type of object. By refining these detections, the placement of 5 G base stations is undertaken in a practical, industrial way, thus allowing network operators to perform a more real-world network optimization. The results demonstrate a significant improvement in detection accuracy, directly contributing to more efficient 5 G base station deployment in densely populated urban areas. This methodology offers a scalable, adaptable, and effective solution based on the context of the images it applies to.

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Orthogonal projection for anomaly detection in networking datasets

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Journal of Ambient Intelligence and Humanized computing 2023年第6期14卷 7957-7966页

作者： Cortes-Polo, David Jimenez, Luis I. Paoletti, Mercedes E. Calle-Cancho, Jesus Rico-Gallego, Juan A. Department of Signal Theory and Communication University Rey Juan Carlos Cam. del Molino 5 Madrid Fuenlabrada28942 Spain Intelligent Systems Group Department of Computer Science University of Valladolid P.O de Belén 15 Valladolid47011 Spain Hyperspectral Computing Laboratory Department of Technology of Computers and Communication University of Extremadura Av. de la Universidad s/n Caceres10003 Spain Calle Sola 1 Extremadura Trujillo10200 Spain Computer and Telematics Systems Engineering University of Extremadura Av. de la Universidad s/n Caceres10003 Spain

In recent years, the impressive growth of new wireless technologies, together with the appearance of new requirements in applications and services, is progressively changing the use of networks. Due to the high mobility required, the network must adapt to the infrastructure to meet the demands of the users. As a result, service providers currently have to over-provision network capacity, which is costly. In addition, considering efficient resource planning in advance involves a lot of labor-intensive efforts. Consequently, network usage analysis is a very useful tool that allows network administrators to find patterns and anomalies. Whilst pattern detection provides administrators the ability to define the infrastructure, anomaly detection provides rich and valuable information for certain applications, for example, to avoid network saturation in urban areas during peak hours. This article proposes a new methodology based on orthogonal projections over Call Detail Records (CDR) for anomaly detection to help in the dynamic management of the network in an urban area. The method is evaluated in a real scenario provided by an Italian telecommunications operator, considering different locations in the Milan metropolitan area, differentiated by the geographic resolution of the data, reaching F1 scores above 0.8. In addition, a new ground truth is presented, hoping it will become a reference data set for the community, in the form of a set of locations that have been corroborated for use in evaluating anomaly detection techniques. © 2023, The Author(s).

关键词： Anomaly detection

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A System for Automatic English Text Expansion

arXiv

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arXiv 2024年

作者： Méndez, Silvia García Gavilanes, Milagros Fernández Montenegro, Enrique Costa Martínez, Jonathan Juncal Castaño, Francisco Javier González Reiter, Ehud GTI Research Group Telematics Engineering Department School of Telecommunications Engineering University of Vigo Vigo36310 Spain Defense University Center Marín Pontevedra36920 Spain CLAN Research Group Department of Computing Science University of Aberdeen Meston Building AberdeenAB24 3UE United Kingdom

We present an automatic text expansion system to generate English sentences, which performs automatic Natural Language Generation (NLG) by combining linguistic rules with statistical approaches. Here, "automatic" means that the system can generate coherent and correct sentences from a minimum set of words. From its inception, the design is modular and adaptable to other languages. This adaptability is one of its greatest advantages. For English, we have created the highly precise aLexiE lexicon with wide coverage, which represents a contribution on its own. We have evaluated the resulting NLG library in an Augmentative and Alternative Communication (AAC) proof of concept, both directly (by regenerating corpus sentences) and manually (from annotations) using a popular corpus in the NLG field. We performed a second analysis by comparing the quality of text expansion in English to Spanish, using an ad-hoc Spanish-English parallel corpus. The system might also be applied to other domains such as report and news generation. © 2024, CC BY.

关键词： Expansion

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An Enhanced Fuzzy Routing Protocol for Energy Optimization in the Underwater Wireless Sensor Networks

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Computers, Materials & Continua 2025年第5期83卷 1791-1820页

作者： Mehran Tarif Mohammadhossein Homaei Amir Mosavi Department of Computer Science University of VeronaVerona37134Italy Department of Computer Systems Engineering and Telematics University of ExtremaduraCaceres10003ExtremaduraSpain Institute of the Information Society Ludovika University of Public ServiceBudapest1083Hungary John Von Neumann Faculty of Informatics Obuda UniversityBudapest1034Hungary Department of Information and Computing Systems Abylkas Saginov Karaganda Technical UniversityKaraganda100000Kazakhstan

Underwater Wireless Sensor Networks(UWSNs)are gaining popularity because of their potential uses in oceanography,seismic activity monitoring,environmental preservation,and underwater ***,these networks are faced with challenges such as self-interference,long propagation delays,limited bandwidth,and changing network *** challenges are coped with by designing advanced routing *** this work,we present Under Water Fuzzy-Routing Protocol for Low power and Lossy networks(UWF-RPL),an enhanced fuzzy-based protocol that improves decision-making during path selection and traffic distribution over different network *** method extends RPL with the aid of fuzzy logic to optimize depth,energy,Received Signal Strength Indicator(RSSI)to Expected Transmission Count(ETX)ratio,and *** protocol outperforms other techniques in that it offersmore energy efficiency,better packet delivery,lowdelay,and no queue *** also exhibits better scalability and reliability in dynamic underwater networks,which is of very high importance in maintaining the network operations efficiency and the lifetime of UWSNs *** to other recent methods,it offers improved network convergence time(10%–23%),energy efficiency(15%),packet delivery(17%),and delay(24%).

关键词： Underwater sensor networks(UWSNs) routing energy fuzzy logic multipath load balancing

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CyberTOMP: A novel systematic framework to manage asset-focused cybersecurity from tactical and operational levels

TechRxiv

引用

TechRxiv 2022年

作者： Domínguez-Dorado, Manuel Carmona-Murillo, Javier Polo, David Cortés Rodríguez Pérez, Francisco J. Department of Information Systems and Digital Toolkit. Public Business Entity Red.es. Madrid28020 Spain Department of Computing and Telematics Engineering Universidad de Extremadura Cáceres10003 Spain Department of Signal Theory and Communications and Telematics Systems and Computing Rey Juan Carlos University Móstoles Madrid28933 Spain

Currently different reference models are used to manage cybersecurity, although practically none are applicable "as is" to lower levels as they do not detail specific procedural aspects for them. However, they urge organizations to develop a methodological foundation to manage cybersecurity at those levels. Although they allow organizations to adhere to a recognized standard at the strategic level, this advantage vanishes when organizations must define specific low-level procedures, allowing the appearance of inconsistency at tactical and operational levels between departments of the same organization or between organizations. The design of these elements with the required holism and homogeneity is difficult, and this is why generic processes focused on getting certified regarding a standard are usually originated, but they are insufficient to obtain effective cybersecurity because they are not focused on dealing with real cyber threats. Because of the great responsibility of lower levels to achieve effective cybersecurity, this lack of methodological definition makes it difficult to adapt cybersecurity to the highly dynamic cyber context with the required holism and strategic alignment. Our proposal provides CyberTOMP, a process for managing cybersecurity at lower levels, as well as a set of methodological elements that support it. The novelty of these contributions is that they complement the strategic standard selected by the organization, providing it with a set of procedural elements ready to be used out of the box, contributing those aspects required by high-level frameworks to manage cybersecurity at lower levels, for which there is no alternative with a managerial approach. © 2022, CC BY-SA.

关键词： Cybersecurity

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Admission control for 5G network slicing based on (deep) reinforcement learning

TechRxiv

引用

TechRxiv 2021年

作者： Villota-Jacome, William F. Rendon, Oscar Mauricio Caicedo da Fonseca, Nelson Luis Saldanha Institute of Computing University of Campinas Brazil Telematics Engineering Group Universidad del Cauca Colombia The Department of Telematics Universidad del Cauca Popayán Colombia

Network Slicing is a promising technology for providing customized logical and virtualized networks for the industry’s vertical segments. Distinct use cases in 5G networks, such as enhanced Mobile Broadband, Ultra-Reliable Low Latency Communications, and Massive Internet of Things, have their Quality of Service requirements, which must be supported. In line with that, this paper proposes an approach encompassing mechanisms for Admission Control and Resource Allocation. The Admission Control mechanism introduces two solutions, one based on Reinforcement Learning (called SARA) and the other based on Deep Reinforcement Learning (named DSARA), to learn the admission policy that optimizes the profit of Network Slice Providers. SARA and DSARA consider the 5G use cases defined by the International Telecommunications Union. The Resource Allocation mechanism tries to balance the load on the network nodes as well as minimize the network resource utilization. Results show that both SARA and DSARA outperform existing mechanisms to manage network slicing in 5G networks. © 2021, CC BY-NC-SA.

关键词： Reinforcement learning

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Low-Rank Tensor Completion for Heart Failure Exacerbation Detection in Multivariate Time Series with Missing Data

Low-Rank Tensor Completion for Heart Failure Exacerbation De...

引用

Annual IEEE Symposium on Computer-Based Medical Systems

作者： Óscar Escudero-Arnanz Rosa Sicilia Cristina Soguero-Ruiz Inmaculada Mora-Jiménez Diana Lelli Claudio Pedone Antonio G. Marques Dept. Signal Theory & Communications Telematics & Computing Systems Rey Juan Carlos University Fuenlabrada Spain Department of Engineering Unit of Computer Systems & Bioinformatics Università Campus Bio-Medico di Roma Italy Operative Research Unit of Geriatrics Fondazione Policlinico Universitario Campus Bio-Medico Italy

ISBN: (数字)9798350384727

ISBN: (纸本)9798350384734

Heart failure exacerbations (HFE) represent a critical challenge in healthcare due to their significant role in global mortality. The rise of home and wearable devices capable of monitoring cardiac conditions provides valuable opportunities for data-driven analysis and HFE detection. However, these devices frequently generate low-quality measurements with irregular sampling frequencies and high rates of missing data. Our paper presents a methodology that processes these measurements as a three-dimensional tensor, applying a low-rank tensor completion scheme to manage missing data effectively, thus facilitating anomaly detection without necessitating data imputation. We validate our method on a dataset from 4 patients with chronic HF in the compensation phase, collected at the Hospital Fondazione Policlinico Universitario Campus Bio-Medico in Rome, Italy. Our results demonstrate the tensor-based method’s superiority over traditional techniques, highlighting its potential for detecting anomalies within complex multivariate time series data. This research emphasizes the critical role of advanced data analysis in enhancing HFE identification, which could lead to improved patient care and reduced hospitalization rates.

关键词： Tensors Data analysis Hospitals Time series analysis Imputation Data models Frequency measurement

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HoneyDOC: An Efficient Honeypot Architecture Enabling All-Round Design

arXiv

引用

arXiv 2024年

作者： Fan, Wenjun Du, Zhihui Smith-Creasey, Max Fernández, David School of Computing University of Kent Canterbury CT2 7NF United Kingdom Department of Computer Science and Technology Tsinghua University Beijing100084 China School of Mathematics Computer Science and Engineering City University of London LondonEC1V 0HB United Kingdom Department of Telematics Engineering Technical University of Madrid Madrid28040 Spain

Honeypots are designed to trap the attacker with the purpose of investigating its malicious behavior. Owing to the increasing variety and sophistication of cyber attacks, how to capture high-quality attack data has become a challenge in the context of honeypot area. All-round honeypots, which mean significant improvement in sensibility, countermeasure and stealth, are necessary to tackle the problem. In this paper, we propose a novel honeypot architecture termed HoneyDOC to support all-round honeypot design and implementation. Our HoneyDOC architecture clearly identifies three essential independent and collaborative modules, Decoy, Captor and Orchestrator. Based on the efficient architecture, a Software-Defined Networking (SDN) enabled honeypot system is designed, which supplies high programmability for technically sustaining the features for capturing high-quality data. A proof-of-concept system is implemented to validate its feasibility and effectiveness. The experimental results show the benefits by using the proposed architecture comparing to the previous honeypot solutions. Copyright © 2024, The Authors. All rights reserved.

关键词： Cybersecurity

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Success-Enablers of Learning Analytics Adoption in Higher Education: A Quantitative Ethnographic Study 1

引用

3rd International Conference on Quantitative Ethnography, ICQE 2021

作者： Alzahrani, Asma Tsai, Yi-Shan Kovanović, Vitomir Moreno-Marcos, Pedro Manuel Jivet, Ioana Aljohani, Naif Gašević, Dragan Centre for Learning Analytics at Monash Faculty of Information Technology Monash University ClaytonVIC Australia UniSA Education Futures University of South Australia AdelaideSA Australia Department of Telematics Engineering Universidad Carlos III de Madrid Getafe Spain Open Universiteit Heerlen Netherlands Faculty of Computing and Information Technology King Abdulaziz University Kingdom of Saudi Arabia Jeddah Saudi Arabia

ISBN: (数字)9783030938598

ISBN: (纸本)9783030938581

This paper focuses on the area of success-enablers in learning analytics (LA) adoption from the perspective of senior managers in higher education institutions (HEIs). A significant body of academic literature exists about challenges in LA. However, to date, the success-enablers from the perspectives of institutional senior managers have received limited attention. This research aims to address this gap reporting on the findings of a study that conducted a series of semi-structure interviews with senior managers at 44 European HEIs. A detailed thematic analysis was conducted on the interviews to tease out the main success-enablers. Then, connections of different success-enablers were analyzed using epistemic network analysis (ENA). The analysis showed that the success-enablers in HEIs that had fully adopted LA depended on the involvement of high-level stakeholders, setting an embedded strategy, getting a technology support from the external partnership, or having a strategic analytical culture. The HEIs that were preparing or only partly adopted LA depended on success-enablers such as having a developing analytical culture or a delegation of expertise in LA-related activity. The findings of this study can help HEIs create strategies that can support successful adoption of LA. © 2022, Springer Nature Switzerland AG.

关键词： Managers

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