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Journal articles on the topic 'QoT Estimation'

Author: Grafiati
Published: 4 June 2025
Last updated: 23 June 2025

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1

Zhou, Yuhang, Xiaoli Huo, Zhiqun Gu, et al. "Self-Attention Mechanism-Based Multi-Channel QoT Estimation in Optical Networks." Photonics 10, no. 1 (2023): 63. http://dx.doi.org/10.3390/photonics10010063.

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It is essential to estimate the quality of transmission (QoT) of lightpaths before their establishment for efficient planning and operation of optical networks. Due to the nonlinear effect of fibers, the deployed lightpaths influence the QoT of each other; thus, multi-channel QoT estimation is necessary, which provides complete QoT information for network optimization. Moreover, the different interfering channels have different effects on the channel under test. However, the existing artificial-neural-network-based multi-channel QoT estimators (ANN-QoT-E) neglect the different effects of the interfering channels in their input layer, which affects their estimation accuracy severely. In this paper, we propose a self-attention mechanism-based multi-channel QoT estimator (SA-QoT-E) to improve the estimation accuracy of the ANN-QoT-E. In the SA-QoT-E, the input features are designed as a sequence of feature vectors of channels that route the same path, and the self-attention mechanism dynamically assigns weights to the feature vectors of interfering channels according to their effects on the channel under test. Moreover, a hyperparameter search method is used to optimize the SA-QoT-E. The simulation results show that, compared with the ANN-QoT-E, our proposed SA-QoT-E achieves higher estimation accuracy, and can be directly applied to the network wavelength expansion scenarios without retraining.
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Tania, Panayiotou, Savva Giannis, Tomkos Ioannis, and Ellinas Georgios. "Decentralizing machine-learning-based QoT estimation for sliceable optical networks." IEEE/OSA Journal of Optical Communications and Networking 12, no. 7 (2020): 146–62. https://doi.org/10.1364/JOCN.387853.

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Dynamic network slicing has emerged as a promising and fundamental framework for meeting 5G’s diverse use cases. As machine learning (ML) is expected to play a pivotal role in the efficient control and management of these networks, in this work, we examine the ML-based quality-of-transmission (QoT) estimation problem under the dynamic network slicing context, where each slice has to meet a different QoT requirement. Specifically, we examine ML-based QoT frameworks with the aim of finding QoT model/s that are fine-tuned according to the diverse QoT requirements. Centralized and distributed frameworks are examined and compared according to their model accuracy, routing and spectrum allocation (RSA) accuracy, and CPU (training time) and RAM (memory) requirements.We show that the distributed QoT models outperform the centralized QoT model in accuracy and CPU usage. The RSA accuracy, i.e., measuring the accuracy of the models with regard to the QoT-aware RSA decisions, is sufficiently high for both frameworks. Regarding the RAM usage, as the distributed framework has to train in parallel several QoT models, it may require higher memory, especially as the number of diverse QoT requirements increases. This memory, however, tends to be reserved for a shorter period of time. Moreover, this work develops a dynamic multi-slice QoT-aware (RSA) framework that integrates the ML-based QoT models. The aim is to examine the network performance when the diverse QoT models are considered, as opposed to the state-of-the-art single-slice QoT-aware RSA approach where all connections/slices are provisioned according to a single QoT requirement. We show that the multi-slice QoT-aware RSA approach significantly improves network performance, a clear indicator that the commonly considered single-slice QoT-aware RSA approach may lead to connection overprovisioning.
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3

Hafsa, Maryam, Panayiotou Tania, and Ellinas Georgios. "Learning quantile QoT models to address uncertainty over unseen lightpaths." Computer Networks Volume 212, no. 108992 (2022): 1389–286. https://doi.org/10.1016/j.comnet.2022.108992.

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Uncertainty in quality-of-transmission (QoT) estimation is traditionally addressed through empirical, myopic margins, ignoring the fact that each unseen lightpath is subject to different levels of uncertainty. To address this limitation, in this work, deep quantile regression is leveraged to finer capture QoT estimation uncertainty through the inference of margins that act discriminative over the unseen lightpaths. Specifically, deep-quantile regression is applied to approximate QoT models capable of inferring the QoT of unseen lightpaths, according to a predefined level of certainty. Quantile models automatically account for the uncertainty during inference, without the need to consider additional empirical margins for decision-making (i.e., the margins are learned and considered upon inference). It is shown that quantile QoT models lead to significant margin reduction when compared to baseline myopic margin schemes, resulting in more confident and network efficient allocation decisions.
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Savva, Giannis, Tania Panayiotou, Ioannis Tomkos, and Georgios Ellinas. "Deep Graph Learning for QoT Estimation of Unseen Optical Sub-Network States: Capturing the Crosstalk Impact on the In-Service Lightpaths." Journal of Lightwave Technology 40, no. 4 (2021): 921–34. https://doi.org/10.1109/JLT.2021.3129646.

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In this work, deep graph convolutional neural networks (DGCNN) are applied for estimating the quality-of-transmission (QoT) of unseen network states in elastic optical networks (EONs) in the presence of physical layer impairments (PLIs), including inter- and intra-channel crosstalk (XT). The objective is to find a DGCNN-QoT model that accurately estimates network state feasibility. A network state is considered feasible if the QoT of the in-service lightpaths and of the lightpath under provisioning is sufficient; that is, the DGCNN does not only infer about the feasibility of an unestablished lightpath but also whether the feasibility of the in-service lightpaths will be affected by the establishment of a new lightpath due to XT. As DGCNN model generalization over unseen graphs is known to be negatively affected by the number of possible graphs and their dimensionality, problem uncertainty and complexity is reduced by formulating the QoT estimation problem over sub-network states, capturing only the spatio-temporal correlations that are relevant to the unestablished lightpath at decision time. DGCNN model accuracy is compared to a state-of-the-art deep neural network (DNN) model trained only over per-lightpath information. It is shown that DGCNN achieves accuracies above 92%, while DNN performs poorly with accuracies as low as 77%, as it fails to infer about the feasibility of in-service connections; an indicator of the importance of explicitly considering during the QoT model training, not only the lightpath patterns, but also the network-state patterns capturing the XT effect. Importantly, it is demonstrated that deep graph learning is a promising approach towards accomplishing this objective.
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5

Mahajan, Ankush, Konstantinos Christodoulopoulos, Ricardo Martínez, Salvatore Spadaro, and Raül Muñoz. "Modeling EDFA Gain Ripple and Filter Penalties with Machine Learning for Accurate QoT Estimation." Journal of Lightwave Technology, 38, no. 9 (2020): 2616–29. https://doi.org/10.1109/JLT.2020.2975081.

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For reliable and efficient network planning and operation, accurate estimation of Quality of Transmission (QoT) before establishing or reconfiguring the connection is necessary. In optical networks, a design margin is generally included in a QoT estimation tool (Qtool) to account for modeling and parameter inaccuracies, ensuring the acceptable performance. In this article, we use monitoring information from an operating network combined with supervised machine learning (ML) techniques to understand the network conditions. In particular, we model the penalties generated due to i) Erbium Doped Fiber Amplifier (EDFA) gain ripple effect, and ii) filter spectral shape uncertainties at Reconfigurable Optical Add and Drop Multiplexer (ROADM) nodes. Enhancing the Qtool with the proposed ML regression models yields estimates for new or reconfigured connections that account for these two effects, resulting in more accurate QoT estimation and a reduced design margin. We initially propose two supervised ML regression models, implemented with Support Vector Machine Regression (SVMR), to estimate the individual penalties of the two effects and then a combined model. On Deutsche Telekom (DT) network topology with 12 nodes and 40 bidirectional links, we achieve a design margin reduction of ~1 dB for new connection requests.
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6

Ghasrizadeh, Sadegh, Prasunika Khare, Nelson Costa, et al. "Digital Twin-Assisted Lightpath Provisioning and Nonlinear Mitigation in C+L+S Multiband Optical Networks." Sensors 24, no. 24 (2024): 8054. https://doi.org/10.3390/s24248054.

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Multiband (MB) optical transmission targets increasing the capacity of operators’ optical transport networks. However, nonlinear impairments (NLI) affect each optical channel in the C+L+S bands differently, and, therefore, the routing and spectrum assignment (RSA) problem needs to be complemented with fast and accurate tools to consider the quality of transmission (QoT) within the provisioning process. This paper proposes a digital twin-assisted approach for lightpath provisioning to provide a complete solution for the RSA problem that ensures the required QoT in MB optical networks. The OCATA time domain digital twin is proposed, not only to estimate the QoT of a selected path but also to support the QoT-based channel assignment process. OCATA is based on a Deep Neural Network (DNN) to model the propagation of the optical signal. However, because of the different impacts of nonlinear noise on each channel and the large number of channels that need to be considered in C+L+S MB scenarios, OCATA needs to be adapted to make it scalable, while keeping its high accuracy and fast QoT estimation characteristics. In consequence, a complete methodology is proposed in this work that limits the number of channels being modeled to just a few. Moreover, OCATA-MB helps to mitigate NLI noise by programming the receiver at the provisioning time and thus with very little complexity compared to its equivalent implemented during the operation. NLI noise mitigation can be applied in the case when a lightpath cannot be provisioned because none of the available channels can provide the required QoT, making it an advantageous tool for reducing connection blocking. Exhaustive simulation results demonstrate the remarkable accuracy of OCATA-MB in estimating the QoT for any channel. Interestingly, by utilizing the proposed OCATA-MB-assisted lightpath provisioning approach, a reduction of the blocking ratio exceeding 50% when compared to traditional approaches is shown when NLI noise mitigation is not applied. If NLI mitigation is implemented, an additional over 50% blocking reduction is achieved.
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7

Ibrahimi, Memedhe, Hatef Abdollahi, Cristina Rottondi, et al. "Machine learning regression for QoT estimation of unestablished lightpaths." Journal of Optical Communications and Networking 13, no. 4 (2021): B92. http://dx.doi.org/10.1364/jocn.410694.

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8

Panayiotou, Tania, Giannis Savva, Ioannis Tomkos, and Georgios Ellinas. "Decentralizing machine-learning-based QoT estimation for sliceable optical networks." Journal of Optical Communications and Networking 12, no. 7 (2020): 146. http://dx.doi.org/10.1364/jocn.387853.

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9

Khare, Prasunika, Nelson Costa, Marc Ruiz, et al. "Simulation and Modelling of C+L+S Multiband Optical Transmission for the OCATA Time Domain Digital Twin." Sensors 25, no. 6 (2025): 1948. https://doi.org/10.3390/s25061948.

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C+L+S multiband (MB) optical transmission has the potential to increase the capacity of optical transport networks, and thus, it is a possible solution to cope with the traffic increase expected in the years to come. However, the introduction of MB optical technology needs to come together with the needed tools that support network planning and operation. In particular, quality of transmission (QoT) estimation is needed for provisioning optical MB connections. In this paper, we concentrate on modelling MB optical transmission for provide fast and accurate QoT estimation and propose machine learning (ML) approaches based on neural networks, which can be easily integrated into an optical layer digital twin (DT) solution. We start by considering approaches that can be used for accurate signal propagation modelling. Even though solutions such as the split-step Fourier method (SSFM) for solving the nonlinear Schrödinger equation (NLSE) have limited application for QoT estimation during provisioning because of their very high complexity and time consumption, they could be used to generate datasets for ML model creation. However, even that can be hard to carry out on a fully loaded MB system with hundreds of channels. In addition, in MB optical transmission, interchannel stimulated Raman scattering (ISRS) becomes a major effect, which adds more complexity. In view of that, the fourth-order Runge–Kutta in the interaction picture (RK4IP) method, complemented with an adaptive step size algorithm to further reduce the computation time, is evaluated as an alternative to reduce time complexity. We show that RK4IP provided an accuracy comparable to that of the SSFM with reduced computation time, which enables its application for MB optical transmission simulation. Once datasets were generated using the adaptive step size RK4IP method, two ML modelling approaches were considered to be integrated in the OCATA DT, where models predict optical signal propagation in the time domain. Being able to predict the optical signal in the time domain, as it will be received after propagation, opens opportunities for automating network operation, including connection provisioning and failure management. In this paper, we focus on comparing the proposed ML modelling approaches in terms of the models’ general and QoT estimation accuracy.
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Sambo, Nicola, Yvan Pointurier, Filippo Cugini, Luca Valcarenghi, Piero Castoldi, and Ioannis Tomkos. "Lightpath Establishment Assisted by Offline QoT Estimation in Transparent Optical Networks." Journal of Optical Communications and Networking 2, no. 11 (2010): 928. http://dx.doi.org/10.1364/jocn.2.000928.

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11

ZHANG, Min, Bo XU, Xiaoyun LI, et al. "Artificial Neural Network-Based QoT Estimation for Lightpath Provisioning in Optical Networks." IEICE Transactions on Communications E102.B, no. 11 (2019): 2104–12. http://dx.doi.org/10.1587/transcom.2018ebp3325.

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12

Azodolmolky, Siamak, Yvan Pointurier, Marianna Angelou, Davide Careglio, Josep Solé-Pareta, and Ioannis Tomkos. "A Novel Impairment Aware RWA Algorithm With Consideration of QoT Estimation Inaccuracy." Journal of Optical Communications and Networking 3, no. 4 (2011): 290. http://dx.doi.org/10.1364/jocn.3.000290.

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13

Mahajan, Ankush, Konstantinos Christodoulopoulos, Ricardo Martínez, Raül Muñoz, and Salvatore Spadaro. "Impact of Multi-Vendor Transponders Performance on Design Margin in Optical Networks." EEE Access 8 (August 1, 2021): 118927–40. https://doi.org/10.1109/ACCESS.2021.3107296.

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For reliable and efficient network planning and operation, accurate estimation of Quality of Transmission (QoT) is necessary. In optical networks, a physical layer model (PLM) is typically used as a QoT estimation tool (Qtool) including a design margin to account for modeling and parameter inaccuracies, to ensure acceptable performance. Such margin also covers the performance variations of the transponders (TPs) which are relatively low in a single vendor environment. However, for disaggregated networks that utilize TPs from multiple vendors, such as partial disaggregated networks with open line system (OLS), this traditional approach limits the Qtool estimation accuracy. Although higher TP performance variations can be covered with an additional margin, this approach would reduce the efficiency and consume the benefits of disaggregation. Therefore, we propose PLM extensions that capture the performance variations of multi- vendor TPs. In particular, we propose four TP vendor dependent performance factors and we also devise a Machine Learning (ML) scheme to learn these performance factors in offline and online network planning scenarios. The proposed extended PLM and ML training scheme are evaluated through realistic simulations. Results show a design margin reduction of greater than 1 dB for new connection requests in a disaggregated network with TPs from four vendors. On top of this, the results also show a ~0.5 dB additional Signal to Noise Ratio (SNR) saving for new connection requests by proper selection of the TPs.
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Diaz-Montiel, Alan A., Bob Lantz, Jiakai Yu, Daniel Kilper, and Marco Ruffini. "Real-Time QoT Estimation Through SDN Control Plane Monitoring Evaluated in Mininet-Optical." IEEE Photonics Technology Letters 33, no. 18 (2021): 1050–53. http://dx.doi.org/10.1109/lpt.2021.3075277.

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15

Silva, Allan A. B., Erick A. Barboza, Felipe C. N. O. Lima, Joaquim F. Martins-Filho, and Marcionilo J. Silva. "Evaluating the impact of EDFA response modeling in the optical network QoT estimation." Optical Fiber Technology 92 (July 2025): 104177. https://doi.org/10.1016/j.yofte.2025.104177.

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16

Sassi, Aymen, Yassin El Hillali, Atika Revenq, Faiza Charfi, and Lotfi Kamoun. "Enhancing V2X Communication Based on a New Comb-Pilot Estimation Approach." International Journal of Vehicular Technology 2016 (September 18, 2016): 1–14. http://dx.doi.org/10.1155/2016/8341490.

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Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) communication systems, known as V2X technologies, have increasingly attracted attention in current research on road safety and traffic ergonomics. The performance evaluation of these communication systems is an important step before their potential integration and use in real systems. V2X communications are based on the IEEE 802.11p standard also known as Wireless Access in Vehicular Environment (WAVE). V2X can affect human life; therefore a deep study related to V2X performance evaluation should be done in order to be sure about the system reliability. In this context, we have elaborated a deep study related to the effect of transmission range on V2X communications by considering the terminal mobility. First, we have evaluated the performance of the PHY layer on the IEEE 802.11p using simulation. Secondly, we have conducted real case measurements using the Arada LocoMate Transmission system. The obtained results shows the necessity to optimize the quality of transmission in V2X communications. Consequently, we propose in this paper a new comb-pilot technique to enhance the quality of Orthogonal Frequency Division Multiplexing (OFDM) transmission. Our proposal consists in two new uses of the pilot subcarrier estimation technique in order to decrease the elevated bit error rate (BER). The quality of transmission (QoT) is first evaluated relating to the pilot symbol rearranged positions. Second, we proposed to optimize the QoT by adding two supplementary pilot symbols as it can offer better channel estimation results. Based on the performance evaluation of our proposal, it is confirmed that both of rearrangement and the adding of the pilot patterns lead to performance enhancement compared to baseline model (standardized one).
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Bergk, Geronimo, Behnam Shariati, Pooyan Safari, and Johannes K. Fischer. "ML-assisted QoT estimation: a dataset collection and data visualization for dataset quality evaluation." Journal of Optical Communications and Networking 14, no. 3 (2021): 43. http://dx.doi.org/10.1364/jocn.442733.

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18

Cantono, Mattia, Dario Pilori, Alessio Ferrari, et al. "On the Interplay of Nonlinear Interference Generation With Stimulated Raman Scattering for QoT Estimation." Journal of Lightwave Technology 36, no. 15 (2018): 3131–41. http://dx.doi.org/10.1109/jlt.2018.2814840.

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19

Khan, Ihtesham, Muhammad Bilal, and Vittorio Curri. "Assessment of cross-train machine learning techniques for QoT-estimation in agnostic optical networks." OSA Continuum 3, no. 10 (2020): 2690. http://dx.doi.org/10.1364/osac.399511.

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Mahajan, Ankush, Konstantinos Christodoulopoulos, Ricardo Martinez, Salvatore Spadaro, and Raul Munoz. "Modeling EDFA Gain Ripple and Filter Penalties With Machine Learning for Accurate QoT Estimation." Journal of Lightwave Technology 38, no. 9 (2020): 2616–29. http://dx.doi.org/10.1109/jlt.2020.2975081.

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21

Klinkowski, Mirosław, and Marek Jaworski. "OSNR-Aware Modeling and Optimization of Multi-Core Fiber-Based Spectrally–Spatially Flexible Optical Networks." Telecom 3, no. 3 (2022): 467–83. http://dx.doi.org/10.3390/telecom3030025.

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We focus on the optical signal-to-noise ratio (OSNR)-aware optical path (lightpath) planning problem in spectrally and spatially flexible optical networks (SS-FONs) connected using weakly coupled multi-core fibers (MCFs) in which distance-adaptive and super-channel transmission is realized using multiple modulation formats. In the SS-FON considered, the quality of transmission (QoT) of optical signals is degraded due to the inter-core crosstalk (XT) effect occurring in MCFs. To account for the XT impairment when planning lightpath connections, we make use of a reliable QoT model based on the OSNR estimation, in which the XT impairment is integrated with other physical-layer impairments. To model the lightpath planning optimization problem, we develop a novel mixed-integer programming (MIP) formulation that incorporates the OSNR model. In addition, we propose an efficient heuristic method that is capable of solving larger instances of the optimization problem considered. The results of numerical experiments indicate the low scalability of the MIP method due to the presence of XT and high effectiveness of the heuristic method. The analysis of three different network topologies and two types of MCFs shows a high impact of XT on network performance and limited performance gains from the presence of the central core in a 7-core MCF.
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Pointurier, Yvan, Jelena Pesic, Cristina Rottondi, and Luis Velasco. "Introduction to the JOCN Special Issue on Machine Learning Applied to QoT Estimation in Optical Networks." Journal of Optical Communications and Networking 13, no. 4 (2021): MLAQ1. http://dx.doi.org/10.1364/jocn.424026.

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23

Ujjwal, Jaisingh Thangaraj, and Aaron Antonio Dias Barreto. "Accurate QoT estimation for the optimized design of optical transport network based on advanced deep learning model." Optical Fiber Technology 70 (May 2022): 102895. http://dx.doi.org/10.1016/j.yofte.2022.102895.

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24

Proietti, Roberto, Xiaoliang Chen, Kaiqi Zhang, et al. "Experimental Demonstration of Machine-Learning-Aided QoT Estimation in Multi-Domain Elastic Optical Networks with Alien Wavelengths." Journal of Optical Communications and Networking 11, no. 1 (2018): A1. http://dx.doi.org/10.1364/jocn.11.0000a1.

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Chen, Xiaoliang, Baojia Li, Roberto Proietti, Che-Yu Liu, Zuqing Zhu, and S. J. Ben Yoo. "Demonstration of distributed collaborative learning with end-to-end QoT estimation in multi-domain elastic optical networks." Optics Express 27, no. 24 (2019): 35700. http://dx.doi.org/10.1364/oe.27.035700.

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Savva, Giannis, Tania Panayiotou, Ioannis Tomkos, and Georgios Ellinas. "Deep Graph Learning for QoT Estimation of Unseen Optical Sub-Network States: Capturing the Crosstalk Impact on the In-Service Lightpaths." Journal of Lightwave Technology 40, no. 4 (2022): 921–34. http://dx.doi.org/10.1109/jlt.2021.3129646.

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27

Frnda, Jaroslav, Jan Nedoma, Jan Vanus, and Radek Martinek. "A Hybrid QoS-QoE Estimation System for IPTV Service." Electronics 8, no. 5 (2019): 585. http://dx.doi.org/10.3390/electronics8050585.

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The internet protocol television service (IPTV) has become a key product for internet service providers (ISP), offering several benefits to both ISP and end-users. Because packet networks based on internet protocol have not been prepared for time-sensitive services, such as voice or video, packet networks have had to adopt several mechanisms to secure minimal transmission standards in the form of data stream prioritization. There are two commonly used approaches for video quality assessment. The first approach needs an original source for comparison (full-reference objective metrics), and the second one requires observers for subjective evaluation of video quality. Both approaches are impractical in real-time transmission because it is difficult to transform an objective score into a subjective quality perception, and on the other hand, subjective tests are not able to be performed immediately. Since many countries worldwide put IPTV on the same level as other broadcasting systems (e.g., terrestrial, cable, or satellite), IPTV services are subject to regulation by the national regulation authority. This results in the need to prepare service qualitative criteria and monitoring tools capable of measuring end-user satisfaction levels. Our proposed model combines the principles of both assessment approaches, which results in an effective monitoring solution. Therefore, the main contribution of the created system is to offer a monitoring tool able to analyze the features extracted from the video sequence and transmission system and promptly translate their impact into a subjective point of view.
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Nakagawa, Satoshi, Huang Minlie, and Yasuo Kuniyoshi. "Construction and Evaluation of QOL Specialized Dictionary SqolDic Using Vocabulary Meaning and QOL Scale." Electronics 10, no. 4 (2021): 417. http://dx.doi.org/10.3390/electronics10040417.

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Agents that build interactive relationships with people can provide appropriate support and generate behaviors by accurately grasping the state of the person. This study focuses on the quality of life (QOL), which can be assessed multidimensionally, and aims to estimate QOL scores in the process of human interaction. Although vision-based estimation has been the main method for QOL estimation, we proposed a new text-based estimation method. We created a QOL-specific dictionary called SqolDic, which is based on large-scale Japanese textual data. To evaluate the effectiveness of SqolDic, we implemented a system that outputs the time-series variation of a user’s conversation content and the QOL scores based on it. In an experiment for estimating the content of user conversations based on a QOL scale by inputting data from actual human conversations, we achieved a maximum estimation accuracy of 91.2%. Additionally, in an experiment to estimate QOL score variability, we successfully estimated the mental health state and one of the QOL scales with a smaller distribution of error than that in previous studies. The experimental results demonstrated the effectiveness of our system in estimating conversation content and QOL scores as well as the effectiveness of our newly proposed QOL dictionary.
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Sarwar, Ghulam, Farman Ullah, and Sungchang Lee. "QoS and QoE Aware N-Screen Multicast Service." Journal of Sensors 2016 (2016): 1–11. http://dx.doi.org/10.1155/2016/8040138.

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The paper focuses on ensuring the quality-of-service (QoS) and quality-of-experience (QoE) requirements of users having heterogeneous devices in a multicast session. QoS parameters such as bit rate, delays, and packet losses are good indicators for optimizing network services but fall short in characterizing user perception (QoE). In N-Screen service, the users have different devices with heterogeneous attributes like screen size, resolution, and access network interface, and the users have different QoE on N-Screen devices with the same QoS parameters. We formulate the objective function of the N-Screen multicast grouping to ensure the minimum user’s QoE with smaller bandwidth requirement. We propose a dynamic user reassignment scheme to maintain and satisfy the QoE by adapting the user’s membership to the varying network conditions. The proposed schemes combine the available bandwidth and multimedia visual quality to ensure the QoS and QoE. In the network architecture, we introduce the functions of the QoS and QoE aware multicast group management and the estimation schemes for the QoS and QoE parameters. The simulation results show that the proposed multicast service ensures the network QoS and guarantees the QoE of users in the varying network conditions.
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Andonov, Velin, Stoyan Poryazov, and Emiliya Saranova. "QoS characterization of some service compositions based on intuitionistic fuzzy pairs." Notes on Intuitionistic Fuzzy Sets 30, no. 2 (2024): 190–202. http://dx.doi.org/10.7546/nifs.2024.30.2.190-202.

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In recent years, a new approach to the estimation of uncertainty in service systems has been developed. It is based on a causal characterization of the traffic in virtual service devices and makes use of the notion of an intuitionistic fuzzy pair. In a series of papers, this approach has been used to obtain quality of service estimations of various compositions of services. In the present paper, an overview of the main results related to the estimation of uncertainty in service compositions is presented.
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Margetis, George, Grigorios Tsagkatakis, Stefania Stamou, and Constantine Stephanidis. "Integrating Visual and Network Data with Deep Learning for Streaming Video Quality Assessment." Sensors 23, no. 8 (2023): 3998. http://dx.doi.org/10.3390/s23083998.

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Existing video Quality-of-Experience (QoE) metrics rely on the decoded video for the estimation. In this work, we explore how the overall viewer experience, quantified via the QoE score, can be automatically derived using only information available before and during the transmission of videos, on the server side. To validate the merits of the proposed scheme, we consider a dataset of videos encoded and streamed under different conditions and train a novel deep learning architecture for estimating the QoE of the decoded video. The major novelty of our work is the exploitation and demonstration of cutting-edge deep learning techniques in automatically estimating video QoE scores. Our work significantly extends the existing approach for estimating the QoE in video streaming services by combining visual information and network conditions.
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Anderson, Katrina, and Annaliese Blair. "FC26: What have staff got to do with it? Untangling complex relationships between residential aged care staff, the quality of care they provide, and the quality of life of people with dementia." International Psychogeriatrics 35, S1 (2023): 87–88. http://dx.doi.org/10.1017/s1041610223001242.

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Background:Despite the integral role long term residential care staff play in the lives of residents with dementia, the mechanisms for supporting staff to bring about good quality of care (QOC) and quality of life (QOL) are poorly understood. This study focused on establishing the key mechanisms to improve QOC and in turn QOL of residents with dementia.Method:Over a 10-month period we followed: 247 older adults with dementia from 12 not-for-profit residential care facilities, their families/care partners (n=225), managers (n=12) and staff (n=232). Facilities ranged in size from 10 to 137 beds, located across remote, rural and metropolitan areas of south eastern Australia. Measures included: staff surveys, family member and resident interviews, resident file audits, live resident and staff observations and organisational audits. Multilevel Modelling or Generalised Estimating Equations analyses were conducted for each of the 12 QOC variables, with 22 staff and control variables as the predictors, and for each of the 11 QOL variables, with 20 QOC and control variables as predictors.Results:Analyses established significant associations between a large number of staff and QOC variables and between QOC and QOL variables.Conclusions:The quality of the care provided to residents has strong, widespread influences on the QOL of residents. The most promising areas for intervening with staff were: increasing the relevance and applicability of staff training and qualifications, upskilling staff in empathic care provision, communication, and restraint reduction, using a mixture of permanent and rotating shifts, prioritising recreational activity provision by all staff and increasing assistance with meals. patients with cognitive impairment in rural hospitals.
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Mr. A. Kingsly Jabakumar. "Enhanced QoS and QoE Support through Energy Efficient Handover Algorithm for UMTS Architectures." International Journal of New Practices in Management and Engineering 8, no. 01 (2019): 01–07. http://dx.doi.org/10.17762/ijnpme.v8i01.73.

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Spectrum inefficiency is a significant issue because of the increasingly more solicitation of transmission capacity by the end clients. Accomplishing high transmission rates and elevated levels of Quality of Service (QoS) speaks to in any case an open issue. Long haul Evolution (LTE) has been proposed as the reason for the fourth era versatile cell systems (4G) that points of the LTE standard are higher client bit rates, lower delays, expanded range proficiency, diminished expense, and operational effortlessness. In any case, this innovation is as yet being worked on and a few open issues must be still explored, for example, obstruction coordination, and power utilization, assets the board and handover procedures. The point of this work is to ensure the decrease of intensity utilization utilizing another handover calculation dependent on green arrangement. Also, the proposed conspire ensures the minimization of superfluous handovers. In any case, the issue in this technique is doesn't mulls over of the impact of green strategies in high force hubs. Along these lines, in the proposed framework the impact of high force hubs are thought of. This situation is expanded more than one full scale cell and various kinds of low force hubs, for example, pico-cell and microcells. In this situation, the force sparing is broke down during the handover strategies. Think about these issues; another strategy is proposed called Dynamic base Station arranging (DBSP) for accomplishing vitality productivity. The fundamental idea is to kill a BS individually that will insignificantly influence the system by utilizing a recently presented thought of system sway, which considers the extra burden increases brought to its neighboring BSs. So as to additionally diminish the flagging and execution overhead over the air and back take, utilize the estimated estimations of system sway as their choice measurements. A trial result shows that the proposed strategy accomplishes high vitality proficiency under different situations. In this work the presentation of an UMTS organize situation is assessed by utilizing different estimations of the priority bits of the CBR application.
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Biro, Jozsef. "Fast Algorithms for Computing Parsimonious Estimates of QoS Measures." ECTI Transactions on Electrical Engineering, Electronics, and Communications 6, no. 2 (2008): 202–9. http://dx.doi.org/10.37936/ecti-eec.200862.171794.

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In recent publications concerning quality of service (QoS) measures in communication networks several attempts have been made to improve the techniques of computing or estimating the quality of data transfer. Many of the promising results are based on the knowledge of only very few parameters on the traffic situation, some of which are known a priory, others are measured. The paper deals with such parsimonious estimation techniques of QoS measures under the bufferless fluid flow multiplexing (bffm) framework, and concentrates on the efficient computation of them. The proposed fixed-point recursive algorithms are key elements in applying either the implicit formulae or ones containing optimization tasks in real-time environment.
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35

Karadimce, Aleksandar, Danco Davcev, and Rechkoska Shikoska Ustijana. "Developing multimedia distance learning services using mobile cloud computing." Journal of Wireless Information Networks & Business information System WINBIS 5, September / October , 2012 (2012): 92–99. https://doi.org/10.5281/zenodo.22951.

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Abstract: The integration of the mobile devices with mobile cloud computing is achieved by diversity of services that are supported by wireless technologies. The main contribution of this paper is the integration of the mobile devices within the mobile cloud computing environment for multimedia distance learning. By using the hardware resources from High performance clustering centers and variety of services offered by the mobile cloud computing technology our approach improves the Quality of Learning (QoL). This way learners are provided with all necessary laboratory resources and scaffolding during the learning process, which makes an efficient distance learning expressed by Quality of Experience (QoE) estimation which is directly related to the QoL.
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Mukesh, Kalla*1 Avinash Panwar2 Prasun Chakrabarti3 Anil Purohit4. "QOS AWARE BANDWIDTH CONSTRAINED PRECEDENCE BASED ROUTING PROTOCOL FOR MOBILE AD-HOC NETWORKS." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 5, no. 7 (2016): 1330–38. https://doi.org/10.5281/zenodo.58568.

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A Mobile Ad-hoc network (MANETs) is a dynamically formed self-configured network by an autonomous system of mobile nodes connected by wireless links. With the advancements of wireless technology, the necessity of Quality of Service (QoS) is increasing rapidly. Developing QoS constraint routing protocol for MANETs is still a challenging task. As the nodes are free to move randomly, most routing protocols for MANETs are susceptible to node mobility. As routing protocol has to decide which route is able to fulfill the requirement of the desired QoS. Routing is the most important part to accomplish the specified application with desired QoS metrics. This paper is based on design of such a kind of technique that will estimate the available bandwidth throughout the path by assigning precedence. Based on available bandwidth, packets are transferred from source to destination of the applications in queue based on precedence. Results of this approach implemented using network simulator and show that protocol can significantly reduce overheads and decrease overall end-to-end delay and improved packet delivery ratio.
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TOMINAGA, Toshiko, Kanako SATO, Noriko YOSHIMURA, Masataka MASUDA, Hitoshi AOKI, and Takanori HAYASHI. "Web-Browsing QoE Estimation Model." IEICE Transactions on Communications E100.B, no. 10 (2017): 1837–45. http://dx.doi.org/10.1587/transcom.2016ebp3411.

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Linden, Noah, and Ronald de Wolf. "Average-Case Verification of the Quantum Fourier Transform Enables Worst-Case Phase Estimation." Quantum 6 (December 7, 2022): 872. http://dx.doi.org/10.22331/q-2022-12-07-872.

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The quantum Fourier transform (QFT) is a key primitive for quantum computing that is typically used as a subroutine within a larger computation, for instance for phase estimation. As such, we may have little control over the state that is input to the QFT. Thus, in implementing a good QFT, we may imagine that it needs to perform well on arbitrary input states. Verifying this worst-case correct behaviour of a QFT-implementation would be exponentially hard (in the number of qubits) in general, raising the concern that this verification would be impossible in practice on any useful-sized system. In this paper we show that, in fact, we only need to have good average-case performance of the QFT to achieve good worst-case performance for key tasks – phase estimation, period finding and amplitude estimation. Further we give a very efficient procedure to verify this required average-case behaviour of the QFT.
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de Oliveira, Ariel Flores Monteiro, Elisan dos Santos Magalhães, Kahl Dick Zilnyk, Philippe Le Masson, and Ernandes José Gonçalves do Nascimento. "Numerical Estimation of Nonlinear Thermal Conductivity of SAE 1020 Steel." Computation 12, no. 5 (2024): 92. http://dx.doi.org/10.3390/computation12050092.

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Thermally characterizing high-thermal conductivity materials is challenging, especially considering high temperatures. However, the modeling of heat transfer processes requires specific material information. The present study addresses an inverse approach to estimate the thermal conductivity of SAE 1020 relative to temperature during an autogenous LASER Beam Welding (LBW) experiment. The temperature profile during LBW is computed with the aid of an in-house CUDA-C algorithm. Here, the governing three-dimensional heat diffusion equation is discretized through the Finite Volume Method (FVM) and solved using the Successive Over-Relaxation (SOR) parallelized iterative solver. With temperature information, one may employ a minimization procedure to assess thermal properties or process parameters. In this work, the Quadrilateral Optimization Method (QOM) is applied to perform estimations because it allows for the simultaneous optimization of variables with no quantity restriction and renders the assessment of parameters in unsteady states valid, thereby preventing the requirement for steady-state experiments. We extended QOM’s prior applicability to account for more parameters concurrently. In Case I, the optimization of the three parameters that compose the second-degree polynomial function model of thermal conductivity is performed. In Case II, the heat distribution model’s gross heat rate (Ω) is also estimated in addition to the previous parameters. Ω [W] quantifies the power the sample receives and is related to the process’s efficiency. The method’s suitability for estimating the parameters was confirmed by investigating the reduced sensitivity coefficients, while the method’s stability was corroborated by performing the estimates with noisy data. There is a good agreement between the reference and estimated values. Hence, this study introduces a proper methodology for estimating a temperature-dependent thermal property and an LBW parameter. As the performance of the present algorithm is increased using parallel computation, a pondered solution between estimation reliability and computational cost is achieved.
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Nie, Peng. "A SVM QoS Estimation Model for the Component-Based Software System." Applied Mechanics and Materials 631-632 (September 2014): 991–94. http://dx.doi.org/10.4028/www.scientific.net/amm.631-632.991.

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More software application are intend to be developed by the automated code synthesis or the component integration. We proposed a SVM QoS estimation model for the component-based software system (SVMQEM). Our estimation model learns various system QoS properties and outputs a comprehensive QoS by SVM, which is different from the approaches available in the literature. The experiments shows that the SVMQEM has an acceptable QoS estimation accuracy for the component-based software system.
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Uthansakul, Peerapong, Patikorn Anchuen, Monthippa Uthansakul, and Arfat Ahmad Khan. "Estimating and Synthesizing QoE Based on QoS Measurement for Improving Multimedia Services on Cellular Networks Using ANN Method." IEEE Transactions on Network and Service Management 17, no. 1 (2020): 389–402. http://dx.doi.org/10.1109/tnsm.2019.2946091.

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Jahromi, Hamed Z., Declan Delaney, and Andrew Hines. "A Sign of Things to Come: Predicting the Perception of Above-the-Fold Time in Web Browsing." Future Internet 13, no. 2 (2021): 50. http://dx.doi.org/10.3390/fi13020050.

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Content is a key influencing factor in Web Quality of Experience (QoE) estimation. A web user’s satisfaction can be influenced by how long it takes to render and visualize the visible parts of the web page in the browser. This is referred to as the Above-the-fold (ATF) time. SpeedIndex (SI) has been widely used to estimate perceived web page loading speed of ATF content and a proxy metric for Web QoE estimation. Web application developers have been actively introducing innovative interactive features, such as animated and multimedia content, aiming to capture the users’ attention and improve the functionality and utility of the web applications. However, the literature shows that, for the websites with animated content, the estimated ATF time using the state-of-the-art metrics may not accurately match completed ATF time as perceived by users. This study introduces a new metric, Plausibly Complete Time (PCT), that estimates ATF time for a user’s perception of websites with and without animations. PCT can be integrated with SI and web QoE models. The accuracy of the proposed metric is evaluated based on two publicly available datasets. The proposed metric holds a high positive Spearman’s correlation (rs=0.89) with the Perceived ATF reported by the users for websites with and without animated content. This study demonstrates that using PCT as a KPI in QoE estimation models can improve the robustness of QoE estimation in comparison to using the state-of-the-art ATF time metric. Furthermore, experimental result showed that the estimation of SI using PCT improves the robustness of SI for websites with animated content. The PCT estimation allows web application designers to identify where poor design has significantly increased ATF time and refactor their implementation before it impacts end-user experience.
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Mansouri, Taha, Ali Nabavi, Ahad Zare Ravasan, and Hamid Ahangarbahan. "A practical model for ensemble estimation of QoS and QoE in VoIP services via fuzzy inference systems and fuzzy evidence theory." Telecommunication Systems 61, no. 4 (2015): 861–73. http://dx.doi.org/10.1007/s11235-015-0041-6.

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Sevcik, Lukas, and Miroslav Voznak. "Adaptive Reservation of Network Resources According to Video Classification Scenes." Sensors 21, no. 6 (2021): 1949. http://dx.doi.org/10.3390/s21061949.

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Video quality evaluation needs a combined approach that includes subjective and objective metrics, testing, and monitoring of the network. This paper deals with the novel approach of mapping quality of service (QoS) to quality of experience (QoE) using QoE metrics to determine user satisfaction limits, and applying QoS tools to provide the minimum QoE expected by users. Our aim was to connect objective estimations of video quality with the subjective estimations. A comprehensive tool for the estimation of the subjective evaluation is proposed. This new idea is based on the evaluation and marking of video sequences using the sentinel flag derived from spatial information (SI) and temporal information (TI) in individual video frames. The authors of this paper created a video database for quality evaluation, and derived SI and TI from each video sequence for classifying the scenes. Video scenes from the database were evaluated by objective and subjective assessment. Based on the results, a new model for prediction of subjective quality is defined and presented in this paper. This quality is predicted using an artificial neural network based on the objective evaluation and the type of video sequences defined by qualitative parameters such as resolution, compression standard, and bitstream. Furthermore, the authors created an optimum mapping function to define the threshold for the variable bitrate setting based on the flag in the video, determining the type of scene in the proposed model. This function allows one to allocate a bitrate dynamically for a particular segment of the scene and maintains the desired quality. Our proposed model can help video service providers with the increasing the comfort of the end users. The variable bitstream ensures consistent video quality and customer satisfaction, while network resources are used effectively. The proposed model can also predict the appropriate bitrate based on the required quality of video sequences, defined using either objective or subjective assessment.
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Collange, Denis, and Jean-Laurent Costeux. "Passive Estimation of Quality of Experience." JUCS - Journal of Universal Computer Science 14, no. (5) (2008): 625–41. https://doi.org/10.3217/jucs-014-05-0625.

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Quality of Experience (QoE) is a promising method to take into account the users' needs in design ing, monitoring and manag ing networks. However, there is a challenge in finding a quick and simple way to estimate th e QoE due to the diversity of needs , habits and customs. We propose a new empirical method to approximate it automatically from passive network measurements and we compare its pros and cons with usual techniques. We apply it, as an example , on ADSL traffic traces to estimate the QoE dependence on the loss rate for the most used applications . We analyze more precisely the correlations between packet losses and some traffic characteristics of TCP connections, the duration, the sizes and the inter-arrival. We define different thresholds on the loss rate for network management. A nd we propose a notion of sensitiveness to compare these correlations on different applications.
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Wang, Shangguang, Qibo Sun, and Fangchun Yang. "Towards Web Service selection based on QoS estimation." International Journal of Web and Grid Services 6, no. 4 (2010): 424. http://dx.doi.org/10.1504/ijwgs.2010.036406.

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Chand, Prem, and M. K. Soni. "QoS Performance Analysis of MANET with Bandwidth Estimation." International Journal of Computer Applications 49, no. 18 (2012): 18–21. http://dx.doi.org/10.5120/7727-1139.

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Kira, E. F., V. F. Bezhenar, and N. N. Ruhliada. "Quality-of-life of the women after surgical treatment of ectopic pregnancy." Journal of obstetrics and women's diseases 48, no. 3 (1999): 30–34. http://dx.doi.org/10.17816/jowd88716.

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Estimation of quality-of-life (QOL) - modern method of researches allowing to reveal even insignificant change in any spheres of ones life with the purpose of all-round definition of efficiency of treatment. The questionnaire, developed by the authors, for an QOL estimation f the patients after operations concerning ectopic pregnancy has high sensitivity, and allows to reveal statistically significant authentic distinctions since 14 day postoperation. The conducting factor determining QOL of patients after all kinds of surgical ectopic pregnancy treatment is the infertility. The increase of a share carried out organ-saving operations considerably improves reproductive health of the population in comparison with results of radical surgeries with removal of uterine tube, that is reflected in fastest positive dynamics in QOL in various terms after operation.
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Arestova, Olga N., Grigoriy A. Osipiyan, Gleb D. Vzorin, Irina V. Malinovskaya, and Margarita V. Maslova. "QUALITY OF LIFE IN RELATION TO IMPAIRED VISUAL FUNCTION AND THE RESULTS OF SURGERY." Moscow University Psychology Bulletin, no. 1 (2020): 55–76. http://dx.doi.org/10.11621/vsp.2020.01.04.

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Relevance. Studies of Quality of Life (QOL) are among the most topical concerns for both psychological and medical research. Although there are many studies abroad, very few have been done in Russia, and with regard to QOL in relation to vision problems they are practically non-existent. Objectives: 1. To develop a Russian-language questionnaire for QOL in relation to vision disorders and the results of their treatment. 2. To measure the relationship among a priori subjective estimations of visual function, expectations of treatment results, and estimations of treatment effects. Method. A pilot investigation was conducted using a questionnaire that we devised for QOL in relation to vision impairment. It included three informational blocks: The first was devoted to a priori estimations of visual problems; the second integrated the patient’s expectations concerning different effects of treatment, and the last estimated the treatment results. Nineteen patients with keratoconus took part in the research. Results. The diagnostic value of the method we developed was empirically confirmed. Ways to fine-tune it to the level of a standardized questionnaire were identified. The comparisons among a priori subjective estimations of visual function, expectations of treatment results, and estimations of treatment effects make it possible to describe the dynamics of QOL. It was shown that subjective estimations of vision are nor related to the objective quality of vision and are probably determined by personality characteristics. Respondents’ treatment results expectations were found to be quite generalized. There are some differences between expectations and estimations of treatment effects: The respondents usually a priori overvalued the instrumental results of the treatment and underestimated the personality-oriented ones. Conclusions. 1. The questionnaire could be used for QOL investigations. This method could be widely used after appropriate standardization procedures are introduced. 2. Subjective estimations of visual function are not related to the objective quality of vision and are probably determined by personality characteristics.
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Devigili, Mariano, Marc Ruiz, Nelson costa, et al. "Applications of the OCATA Time Domain Digital Twin: from QoT Estimation to Failure Management." Journal of Optical Communications and Networking, June 5, 2024. https://doi.org/10.1364/JOCN.507128.

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Optical in-phase and quadrature (IQ) constellations enclose valuable information regarding the optical elements traversed by the optical signal. Such information can be extracted and exploited by algorithms and models within an optical layer digital twin. In this paper, we investigate the feasibility of extracting information from IQ constellations and its use for both accurate quality of transmission (QoT) estimation and efficient failure management within. First, we observe the correlations between the measured QoT of lightpaths and the value of specific features extracted from IQ constellation samples collected from the optical receiver and design Deep Neural Networks (DNN) models for QoT estimation. Next, specific DNN models and algorithms that exploit IQ constellation features are proposed for soft-failure detection, identification and severity estimation. Results show noticeable accuracy on the estimation of QoT and on the prediction of failures affecting the transmitter, optical filters and amplifiers.
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