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Acoustics, Speech, and Signal Processing Workshops (ICASSPW), IEEE International Conference on

作者： Kuan-Cheng Chen Yi-Tien Li Tai-Yu Li Chen-Yu Liu Po-Heng Henry Lee Cheng-Yu Chen Department of Electrical and Electronic Engineering Imperial College London London UK Centre for Quantum Engineering Science and Technology (QuEST) Imperial College London London UK Translational Imaging Research Center Taipei Medical University Hospital Taipei Taiwan Research Center for Neuroscience Taipei Medical University Taipei Taiwan Ph.D. Program in Medical Neuroscience College of Medical Science and Technology Taipei Medical University Taipei Taiwan National Center for High-Performance Computing NARlabs Hsinchu Taiwan Graduate Institute of Applied Physics National Taiwan University Taipei Taiwan Department of Medical Imaging Taipei Medical University Hospital Taipei Taiwan Department of Radiology National Defense Medical Center Taipei Taiwan Department of Radiology School of Medicine College of Medicine Taipei Taiwan

ISBN: (数字)9798331519315

ISBN: (纸本)9798331519322

This paper introduces CompressedMediQ, a novel hybrid quantum-classical machine learning pipeline specifically developed to address the computational challenges associated with high-dimensional multi-class neuroimaging data analysis. Standard neuroimaging datasets, such as large-scale MRI data from the Alzheimer’s Disease Neuroimaging Initiative and Neuroimaging in Frontotemporal Dementia, present significant hurdles due to their vast size and complexity. CompressedMediQ integrates classical HPC nodes for advanced MRI pre-processing and Convolutional Neural Network (CNN)-PCA-based feature extraction and reduction, addressing the limited-qubit availability for quantum data encoding in the NISQ era. This is followed by Quantum Support Vector Machine (QSVM) classification. By utilizing quantum kernel methods, the pipeline optimizes feature mapping and classification, enhancing data separability and outperforming traditional neuroimaging analysis techniques. Experimental results highlight the pipeline’s superior accuracy in dementia staging, validating the practical use of quantum machine learning in clinical diagnostics. Despite the limitations of NISQ devices, this proof-of-concept demonstrates the transformative potential of quantum-enhanced learning, paving the way for scalable and precise diagnostic tools in healthcare and signal processing.

关键词： Neuroimaging Support vector machines Quantum computing Accuracy Magnetic resonance imaging Pipelines Machine learning Medical services Signal processing Standards

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Case-based cybersecurity incident resolution 31

Case-based cybersecurity incident resolution

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31st International Conference on Software Engineering and Knowledge Engineering, SEKE 2019

作者： Colome, Marcelo Nunes, Raul Ceretta De Lima Silva, Luis Alvaro Graduate Program in Computer Science - PPGCC Applied Computing Department Federal University of Santa Maria Av. Roraima Campus UFSM Camobi Santa Maria RS Brazil

ISBN: (纸本)1891706489

Intelligent computing techniques have a paramount importance to the treatment of cybersecurity incidents. In such Artificial Intelligence (AI) context, while most of the algorithms explored in the cybersecurity domain aim to present solutions to intrusion detection problems, these algorithms seldom approach the correction procedures that are explored in the resolution of cybersecurity incident problems that already took place. In practice, knowledge regarding cybersecurity resolution data and procedures is being under-used in the development of intelligent cybersecurity systems, sometimes even lost and not used at all. In this context, this work proposes to integrate Case-Based Reasoning techniques and IODEF standard in order to retain concrete problem-solving experiences of cybersecurity incident resolution to be reused in the resolution of new incidents. Experimental results so far obtained with a Case-based Cybersecurity Incident Resolution System (CbCSecIRS) implemented show that information security knowledge can be retained in a reusable memory, so improving the resolution of new cybersecurity problems. © 2019 Knowledge Systems Institute graduate School. All rights reserved.

关键词： Intrusion detection

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Criteria Selection and Decision-Making Support in IT Governance: A Study via Fuzzy AHP applied to a Multi-institutional Consortium

Criteria Selection and Decision-Making Support in IT Governa...

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International Conference on Information Technology and Systems, ICITS 2023

作者： de Oliveira, José Fábio de Sousa, Paulo Evelton Lemos Reis, Ana Carla Bittencourt Graduate Program in Applied Computing University of Brasília - UnB PPCA University Campus Darcy Ribeiro - Asa Norte DF CEP: 70910-900 Brasília Brazil

ISBN: (纸本)9783031332579

The formation of consortia between public and private institutions to achieve projects with a common objective is a practice considered usual in Brazil. Due to the different destinations between these institutions, divergences among decision-makers regarding the prioritization of actions may occur with some frequency. With this approach, this work seeks to minimize the impact of subjectivity in the prioritization of actions of a multi-institutional consortium, formed by public and private entities, with the support of Fuzzy logic and multi-criteria analysis to support the decision. Criteria and decision alternatives were identified and analyzed with the support of experts. At the end of the hierarchy, it was possible to present the top management of the Consortium with a proposal of ranked alternatives for optimizing the use of financial resources targeting IT Governance actions. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Fuzzy logic

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Detecting Center Pivots in Matopiba Using Hough Transform and Web Time Series Service

Detecting Center Pivots in Matopiba Using Hough Transform an...

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2020 IEEE Latin American GRSS and ISPRS Remote Sensing Conference, LAGIRS 2020

作者： Rodrigues, M.L. Korting, T.S. De Queiroz, G.R. Sales, C.P. Da Silva, L.A.R.D. Graduate program in Applied computing National Institute for Space Research Sçao José dos Campos SP Brazil Sçao José dos Campos SP Brazil

ISBN: (数字)9781728143507

ISBN: (纸本)9781728143507

In the last decades, the Brazilian Cerrado biome has undergone major transformations due to the expansion of the agricultural frontier. The region called MATOPIBA acronym for states Maranhão, Tocantins, Piauí, and Bahia can be considered very attractive for agricultural expansion. The Cerrado predominates in the MATOPIBA region (91% of the area), also having small areas of the Amazon and Caatinga biomes to the northeast and east, respectively. In this work, we will present a study to identify center pivot irrigation systems in the MATOPIBA region using remote sensing images from Landsat-8 satellite. The methodology is based on the use of robust edge detection techniques such as Canny, Circular Hough Transform (CHT) and time series extraction through the Moderate Resolution Imaging Spectroradiometer (MODIS) product MOD13Q1 which has two vegetation indices NDVI and EVI. These time series will be used to filter the detected circles, seeking to eliminate the circles that do not correspond to center pivots. Our approach detected 80% of the center pivots mapped by the Brazilian National Water Agency (ANA) used as a knowledge base. The states with better detection were Piauí and Bahia that showed the accuracy of 90% and 85% respectively, Maranhão obtained 57% and Tocantins 41%. © 2020 IEEE.

关键词： Landsat

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Climate Precipitation Prediction by Neural Network

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Journal of Mathematics and System Science 2015年第5期5卷 207-213页

作者： Juliana Aparecida Anochi Haroldo Fraga de Campos Velho Applied Computing Graduate Program National Institute for Space Research (INPE) Brazil. Associated Laboratory for Computing and Applied Mathematics National Institute for Space Research (INPE).

In this work a neural network model for climate forecasting is presented. The model is built by training a neural network with available reanalysis data. In order to assess the model, the development methodology considers the use of data reduction strategies that eliminate data redundancy thus reducing the complexity of the models. The results presented in this paper considered the use of Rough Sets Theory principles in extracting relevant information from the available data to achieve the reduction of redundancy among the variables used for forecasting purposes. The paper presents results of climate prediction made with the use of the neural network based model. The results obtained in the conducted experiments show the effectiveness of the methodology, presenting estimates similar to observations.

关键词： Climate Prediction Neural Networks Rough Sets Theory

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An IoT Transport Architecture for Passenger Counting: A Real Implementation

An IoT Transport Architecture for Passenger Counting: A Real...

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IFIP/IEEE International Symposium on Integrated Network Management

作者： Janine Kniess Julio Cezar Rutke William Alberto Cruz Castañeda Graduate Program in Applied Computing Santa Catarina State University Brazil

A smart urban mobility considers the technological-based development in transport systems, services and their use to improve the movement of people and goods inter or intra-cities. Cities increasingly face problems caused by traffic and need to find solutions to improve mobility and to reduce congestion and pollution. In this paper, we present a Passenger Counting Scheme into buses. Embedded counting algorithms based on Computer Vision are proposed to count passenger arrivals and departures in real time. Experiments in a real scenario expose that the proposed scheme achieved a high percentage of success in passenger count.

关键词： Training Computer vision Pollution Urban areas Computer architecture Cameras Real-time systems

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GreenRM: Reference model for sustainable software development 26

GreenRM: Reference model for sustainable software developmen...

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26th International Conference on Software Engineering and Knowledge Engineering, SEKE 2014

作者： Thiry, Marcello Frez, Liliane Zoucas, Alessandra Applied Computing Graduate Program University of Vale do Itajaí - UNIVALI Florianópolis Brazil Department of Knowledge Management Federal University of Santa Catarina - UFSC Florianópolis Brazil

Information technology and the environment have a relationship until then signaled by the effects caused by excessive energy consumption, greenhouse gas emissions and the e-waste. In our paper we present the GreenRM reference model for sustainable software development. We focus on the model structure definition and the benefits identified with its implementation. We also present a comparison between the model processes and attributes with the environmental requirements of ISO/IEC 14001 to demonstrate its compatibility. In addition we present a model early assessment in three Brazilian software organizations to evaluate the model technical and financial feasibility. Copyright © 2014 by Knowledge Systems Institute graduate School.

关键词： Green IT Green software engineering Process reference model Sustainable development

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An Energy-Efficient Bio-Scheduling Model For Emergency Networks

An Energy-Efficient Bio-Scheduling Model For Emergency Netwo...

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IEEE Conference on Wireless Communications and Networking

作者： Janine Kniess Marcelo Petri Rafael Stubs Parpinelli Graduate Program in Applied Computing Santa Catarina State University Brazil

The efficient management of resources after a disaster, must take place within a short time and efficiently. Therefore, resource scheduling protocol which shares resources among the victims, respecting time constraints, is decisive. In disaster scenarios, communication infrastructure is usually damaged and a commonly used solution for ensuring connectivity between victims and providers is Mobile Ad Hoc Network (MANET). Fire brigade and ambulances might be insufficient if the number of victims is high. Hence, in order to provide an efficient resource scheduling approach that cares about the energy consumption, the number of requesters attended and the processing time, we present a Scheduling Resource protocol. Thus, to reduce the provider dislocation time and increase the number of victims attended the protocol was modeled based on Genetic Algorithms. Results show that this approach maintains the trade-off between the number of victims attended, therefore, minimize the energy consumption.

关键词： Energy consumption Protocols Scheduling algorithms Biological system modeling Process control Scheduling Space exploration

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Joint Cache Placement and Request Routing Optimization in Heterogeneous Cellular Networks

Joint Cache Placement and Request Routing Optimization in He...

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IEEE Symposium on Computers and Communications (ISCC)

作者： Marisangila Alves Guilherme Piĉgas Koslovski Graduate Program in Applied Computing - Santa Catarina State University - UDESC

ISBN: (数字)9781665497923

ISBN: (纸本)9781665497930

The 5G Quality-of-Service (QoS) objectives con-tributed to the Heterogeneous Cellular Network (HCN) evolution, dictating that applications can rely on low-latency and high-bandwidth networks. However, concurrent requests of large amount of multimedia data generate a burden on the backhaul and fronthaul networks due to redundant retransmissions and pose challenges for achieving the QoS objectives. Although mobile network operators can place content closer to the HCN edge to improve the overall QoS indicators, there are still challenges to design a cache policy aware of limited storage capacity, different content popularity, device mobility, and network congestion. This work innovates by introducing a cooperative policy to join caches placement and routing users' requests atop an HCN. By combining networking and cache QoS requirements, the policy balances the fronthaul network load and dynamically maps the caches to HCN resources. We formulated the cache policy through linear programming and in-depth evaluated its performance using extensive simulation scenarios. The results indicate that the proposed network-aware policy decreases the network latency, even when subject to changes in content popularity distribution and total HCN storage capacity.

关键词： Cellular networks Measurement 5G mobile communication Quality of service Routing Linear programming Low latency communication

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Evaluation of Distance Education through Blended Learning: Comparisons and Important Factors for the Learning Process

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Creative Education 2014年第2期5卷 70-74页

作者： Júlio C. G. Bertolin Ana Carolina Bertoletti De Marchi Graduate Program in Applied Computing University of Passo Fundo Passo Fundo Brazil Graduate Program in Education University of Passo Fundo Passo Fundo Brazil

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