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An Efficient Lightweight Authentication and Key Agreement Protocol for Patient Privacy

computers, Materials & Continua 2021年第12期69卷 3495-3512页

作者： Seyed Amin Hosseini Seno Mahdi Nikooghadam Rahmat Budiarto Department of Computer Engineering Ferdowsi University of MashhadMashhad***Iran Department of Informatics Faculty of Science and TechnologyUniversitas Alazhar IndonesiaJakarta12110Indonesia

Tele-medical information system provides an efficient and convenient way to connect patients at home with medical personnel in clinical *** this system,service providers consider user authentication as a critical *** address this crucial requirement,various types of validation and key agreement protocols have been *** main problem with the two-way authentication of patients and medical servers is not built with thorough and comprehensive analysis that makes the protocol design yet has *** paper analyzes carefully all aspects of security requirements including the perfect forward secrecy in order to develop an efficient and robust lightweight authentication and key agreement *** secureness of the proposed protocol undergoes an informal analysis,whose findings show that different security features are provided,including perfect forward secrecy and a resistance to DoS ***,it is simulated and formally analyzed using Scyther *** results indicate the protocol’s robustness,both in perfect forward security and against various *** addition,the proposed protocol was compared with those of other related protocols in term of time complexity and communication *** time complexity of the proposed protocol only involves time of performing a hash function Th,i.e.,:O(12Th).Average time required for executing the authentication is 0.006 seconds;with number of bit exchange is 704,both values are the lowest among the other *** results of the comparison point to a superior performance by the proposed protocol.

关键词： Authentication key agreement protocol tele-medical Scyther perfect forward secrecy

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Investigation of the separation zone for split-domain light field visualization 28

Investigation of the separation zone for split-domain light ...

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2024 28th International Conference on Information Technology, IT 2024

作者： Javidi, Kamran Martini, Maria G. Kara, Peter A. School of Computer Science and Mathematics Faculty of Engineering Computing and the Environment Kingston University Wireless Multimedia and Networking Research Group Department of Computer Science Penrhyn Road Campus Kingston upon Thames LondonKT1 2EE United Kingdom Budapest University of Technology and Economics Faculty of Electrical Engineering and Informatics Department of Networked Systems and Services Budapest1111 Hungary

ISBN: (纸本)9798350369618

Light field visualization commonly provides a single content over the entire field of view. However, the angularly-selective nature of the technology enables the simultaneous visualization of different contents at different viewing angles. Yet segmenting the valid viewing area comes with content interference as well in forms of separation zones, resulting invalid viewing domains. In this paper, we introduce a study on the separation zone of split-domain light field visualization. We created a static-content-based scenario in which we split the valid viewing area into two distinct domains, with a separation zone in between them. This was achieved by merging two light field contents in the middle with an instantaneous switch. The resulting visualization on a light field display was captured by a DSLR camera from two viewing distances, and it was compared to the crosstalk effect caused by insufficient angular resolution. © 2024 IEEE.

关键词： Visualization

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Assessment of the targeted energy saving potential through an energy efficiency action plan adapted to the specific needs of a SME in Romania 13

Assessment of the targeted energy saving potential through a...

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13th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion, MEDPOWER 2022

作者： Mureșan, Claudia Farkas, Timea Șteț, Denisa Czumbil, Levente Cîrstea, Ștefan Turcu, Antoniu Polycarpou, Alexis Micu, Dan D. Energy Transition Research Center Technical University of Cluj-Napoca Cluj-Napoca Romania Department of Electrical Engineering Computer Engineering and Informatics Frederick University Nicosia Cyprus

ISBN: (纸本)9781839538445

This paper aims to contribute to overcoming the barriers that are hindering the adoption of energy efficiency measures in SMEs sector, particularly addressing informational and organizational issues, by presenting a methodology for assessment of the targeted energy saving potential in a SME that has been developed and validated in the framework of H2020 SMEmPower Efficiency project, based on a Monitoring & Targeting (M&T) tool. As a case study, the method was applied in a SME activating in the manufacturing of knitted and crocheted fabrics sector in Romania. After the company's energy profile was created, the M&T simulation generated a series of energy saving and CO2 emission reduction targets, based on which a set of specific energy efficiency (technical and organisational) measures tailored to the company's needs were proposed and assessed from both technical and financial perspectives. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Energy efficiency

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Classification of Arrhythmias 12-Lead ECG Signals Based on 1 Dimensional Convolutional Neural Networks

Classification of Arrhythmias 12-Lead ECG Signals Based on 1...

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Smart Computing, IoT and Machine Learning (SIML), International Conference on

作者： Arief Kurniawan Bayu Aditya Triwibowo Dion Hayu Fandiantoro Department of Computer Engineering Faculty of Intelligent Electrical and Informatics Technology Institut Teknologi Sepuluh Nopember

ISBN: (数字)9798350364101

ISBN: (纸本)9798350364118

Heart disease is the highest cause of death in the world. Arrhythmia is an abnormality in the rhythm of the heartbeat. The heart beats too fast, too slow, or irregularly. Arrhythmias are not always dangerous, e.g., someone who does excessive activity has a faster heart rate. Then, a diagnosis is needed to classify arrhythmias. One method used is ECG (Electrocardiogram) signal analysis. The ECG signal consists of P, QRS Complex, and T waves. The morphology of the QRS is used for arrhythmia classification. Currently, cardiologists analyze ECG signals by observing directly. This method is depending on the level of expertise of the cardiologist. Previous research classified arrhythmias based on the QRS morphology from a single ECG lead. As 12-lead ECG devices have now become standard in ECG examinations because abnormalities can be observed from multiple angles. This study proposes the classification of arrhythmias in 12-lead ECG signals based on the morphology of QRS complex waves using a deep learning 1-dimensional Convolutional Neural Network. The output of deep learning is the classification of arrhythmias into four classes, namely: Normal, Right Bundle Branch Block, Premature Ventricular Contraction, and Atrial Premature Beat. The outcome of the proposed system is that each QRS segment is used as input for deep learning, which can improve classification performance compared to the classification carried out by each lead. The experimental results show the method can be done well, with an average Accuracy, Precision, Sensitivity, and F1-Score were 98.8%, 99.2%, 99.2%, and 99.2%, respectively.

关键词： Deep learning Accuracy Sensitivity Heart beat Arrhythmia Morphology Electrocardiography

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What Drives I4.0 Adoption? Establishing the Importance of Strategy

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IEEE engineering Management Review 2023年第3期51卷 33-41页

作者： Arcidiacono, Francesco Ancarani, Alessandro Di Mauro, Carmela Schupp, Florian University of Catania Department of Electrical Electronic and Computer Engineering Catania95124 Italy Schaeffler Automotive Bühl Bühl77815 Germany University of Catania Department of Civil Engineering and Architecture Catania95124 Italy Corvinus University of Budapest Corvinus Institute for Advanced Studies Budapest1093 Hungary Constructor University School of Business Social and Decision Sciences Bremen28759 Germany

This article investigates the adoption patterns of Industry 4.0 (I4.0) technologies in the automotive component sector and links I4.0 adoption to competitive strategies. Analysis of survey data concerning 288 automotive suppliers reveals that most firms currently focus on implementing real-time collection and analysis of production data (i.e., the Internet of Things, Big Data, and Artificial Intelligence), while other technologies, such as additive manufacturing and blockchain, are infrequently adopted. I4.0 adoption is associated with a simultaneous strategic emphasis on cost, quality, and delivery, thus suggesting automotive suppliers look at I4.0 as a mean to overcome performance tradeoffs. Findings also confirm that small- and medium-sized firms are less likely to adopt I4.0. Based on these results, implications for academics, managers, and policymakers are suggested. © 1973-2011 IEEE.

关键词： Supply chains

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Predictive Analysis of Sarajevo’s AQI using Machine Learning Models for Varied Data Granularity and Prediction Windows

Predictive Analysis of Sarajevo’s AQI using Machine Learnin...

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Proceedings of the International Convention MIPRO

作者： Emina Zolota Vahidin Hasić Amina Mević Amra Delić Senka Krivić Department for Computer Science and Informatics Faculty of Electrical Engineering University of Sarajevo Sarajevo Bosnia and Herzegovina

ISBN: (数字)9798350382501

ISBN: (纸本)9798350382518

This study scrutinizes five years of Sarajevo’s Air Quality Index (AQI) data using diverse machine learning models — Fourier autoregressive integrated moving average (Fourier ARIMA), Prophet, and Long short-term memory (LSTM)—to forecast AQI levels. Focusing on various prediction frames, we evaluate model performances and identify optimal strategies for different temporal granularities. Our research unveils subtle insights into each model’s efficacy, shedding light on their strengths and limitations in predicting AQI across varied timeframes. This research presents a robust framework for automatic optimization of AQI predictions, emphasizing the influence of temporal granularity on prediction accuracy, automatically selecting the most efficient models and parameters. These insights hold significant implications for data-driven decision-making in urban air quality control, paving the way for proactive and targeted interventions to improve air quality in Sarajevo and similar urban environments.

关键词： Accuracy Atmospheric modeling Urban areas Machine learning Predictive models Air quality Data models

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EMPRN: Reinforcement Learning-based ECN Tuning Using Message Passing Graph Recurrent Networks for Datacenters

EMPRN: Reinforcement Learning-based ECN Tuning Using Message...

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IEEE International Conference on Communications (ICC)

作者： Kasra Zaeri Ahmed M. Abdelmoniem Department of Electrical and Computer Engineering The University of Tehran Tehran Iran School of Electronic Engineering and Computer Science Queen Mary University of London UK

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

Congestion control (CC) based on explicit congestion notification (ECN) is a common method for reducing latency and increasing link utilization in data center networks (DCN). Proper ECN tuning significantly impacts the performance of ECN-based CC algorithms. Due to the fast buffer buildup and dynamic spatial-temporal nature of traffic in high-speed DCNs, fast and online ECN tuning can reduce latency and packet loss. Most existing approaches do not capture the spatial dependencies between egress ports of switches. In this paper, we propose EMPRN, a novel in-network CC algorithm based on multi-agent reinforcement learning (MARL). We design a graph recurrent neural network for online ECN tuning. EMPRN is implemented in a distributed manner on switches, and it can be adapted to most ECN-based CC protocols. We use a message-passing neural network (MPNN) architecture to capture the spatial dependencies between egress ports. We integrate the proposed MPNN with a gated recurrent unit (GRU) network to learn both the spatial and temporal dependencies. Our simulation results show that our proposed approach achieves up to 21% and 87.9% reductions in terms of flow completion time (FCT) and average queue length, respectively, compared to a state-of-the-art reinforcement learning-based approach for online ECN tuning.

关键词： Protocols Recurrent neural networks Simulation Heuristic algorithms Message passing Packet loss Reinforcement learning

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Comparison of Model in Predicting Customer Churn Based on Users' habits on E-Commerce 5

Comparison of Model in Predicting Customer Churn Based on Us...

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5th International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2022

作者： Lubis, Arif Ridho Prayudani, Santi Julham Nugroho, Okvi Lase, Yuyun Yusnida Lubis, Muharman Politeknik Negeri Medan Department of Computer Engineering and Informatics Medan Indonesia SMA Muhammadiyah 2 Medan Indonesia School of Industrial Engineering Telkom University Bandung Indonesia

ISBN: (纸本)9781665455121

Customer churn is a situation that receives extensive analysis using a variety of techniques from data mining or machine learning. Data mining techniques may be used to anticipate customer churn. A data mining algorithm was used in this study to forecast client turnover. Logistic Regression and gradient boosting models were employed as one of the data mining techniques for implementing customer churn forecasts. The gradient boosting model could be said to perform better in predicting customer churn when compared to the logistic regression model, which produced accuracy training 87% and testing 88%. The results showed that the gradient boosting model was able to carry out the training and testing process with a training accuracy of 93% and a testing accuracy of 91%. © 2022 IEEE.

关键词： Forecasting

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The Effect of E-Commerce and Purchase Effectiveness on Student Learning 5

The Effect of E-Commerce and Purchase Effectiveness on Stude...

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5th International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2022

ISBN: (纸本)9781665455121

E-commerce is the practice of purchasing and selling products or services online or through other electronic channels. E-commerce is expanding quite quickly right now, as seen by the rise in e-commerce sites like Tokopedia, Shopee, and Lazada. The study examined how e-commerce affects students' learning, who frequently utilize it as a tool to fill their learning needs. With the rise in student e-commerce, learning is a must for students if they want to enhance knowledge generally. Analyzing whether e-commerce has a positive or negative impact on enhancing learning is required. The results showed that only the primary channel variable for e-commerce transactions (X1) had a significant influence on the student learning variable (Y), whereas the ease-of-use variable (X2), learning correlation (X3), and transaction variable (X4) did not have a significant effect on student learning. The tests had been conducted using the SPSS software to test the classical assumptions. Some e-commerce specialists believed that e-commerce was only utilized to address fundamental necessities and lifestyle requirements, not educational requirements. © 2022 IEEE.

关键词： Students

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On Utilizing Unused Slots In Topology-Transparent TDMA MAC Policies for Ad Hoc Networks

On Utilizing Unused Slots In Topology-Transparent TDMA MAC P...

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2022 Global Information Infrastructure and Networking Symposium, GIIS 2022

作者： Dragonas, Vasileios Kallergis, Dimitrios Tsoumanis, Georgios Oikonomou, Konstantinos Ionian University Department of Informatics Corfu Greece University of West Attica Dept. of Informatics & Computer Engineering Aegaleo Greece University of Ioannina Dept. of Informatics & Telecommunications Arta Greece

ISBN: (数字)9781665490955

ISBN: (纸本)9781665490955

In the age of the Internet of Things, numerous devices of diverse characteristics are communicating with each other. The underlying networks supporting those communications can either use some sort of infrastructure or implement an ad hoc network. For the latter type of networks and depending on the application requirements, Topology-Transparent TDMA MAC policies can be considered as they are inherently suited for dynamic and unstructured topologies. However, such TDMA-based schemes may suffer from low throughput performance, especially in sparse networks, where a significant portion of available time slots remains unused. To address this challenge, a Topology-Transparent TDMA MAC policy is revisited in this paper, which utilizes unused slots by allowing nodes to transmit in them under a common and fixed probability p. Additionally, an improvement is proposed, where every node can calculate its own individual access probability based on information gathered from its local neighborhood. Simulation results demonstrate that the use of the individual access probability leads to improved performance in terms of system throughput. Moreover, the requirement for assigning a value to probability p during the network initialization is relaxed, as this value is now calculated dynamically and distributively during the network operation. © 2022 IEEE.

关键词： Ad hoc networks

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