Hearing loss impacts over 5% of the world's population, a percent rising due to aging populations, noise exposure, and chronic health conditions. To address this, we developed a non-invasive hearing device designe...
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ISBN:
(数字)9798331532147
ISBN:
(纸本)9798331532154
Hearing loss impacts over 5% of the world's population, a percent rising due to aging populations, noise exposure, and chronic health conditions. To address this, we developed a non-invasive hearing device designed for individuals with hearing challenges that limit the use of hearing aids. The proposed device integrates a set of Bluetooth headphones with a smartphone, that process the ambient sound in real time through a software application and delivers to the hear impaired patient via bone conduction, bypassing traditional auditory pathways. Laboratory tests confirmed that the proposed device effectively replicates auditory perception. The developed device offers an accessible and user-friendly alternative to patients who cannot use traditional hearing aids.
The increased need for accurately modeling the input-output characteristics of linear time-periodic (LTP) systems necessitates novel identification and control algorithms as well as new test benches for their experime...
The increased need for accurately modeling the input-output characteristics of linear time-periodic (LTP) systems necessitates novel identification and control algorithms as well as new test benches for their experimental validation. This paper introduces a simple-to-build test bench for the identification and control of LTP systems. We mechanically coupled the shafts of two DC motors and fed back the angular velocity to the second motor with a time-periodic modulation. This allowed us to imitate a time-periodic load for the first DC motor, thereby yielding an experimental LTP plant. We used Matlab/Simulink target hardware support to implement the entire software in Simulink, which greatly simplifies input design, data collection, and analysis as compared to embedded programming. We used constant-frequency sinusoidal signals for the data collection on the experimental test bench. Subsequently, we estimated the harmonic transfer functions and identified the parameters of a state-space model of the proposed LTP system. We then designed a time-periodic controller in order to regulate the output of the LTP system. We designed a reference-tracking controller along with a Linear Quadratic Integrator (LQI) to improve the system performance. We validated our results through experiments on the physical LTP system plant.
Thermal stress is a critical failure factor for power electronics components. Hence, when developing a precise digital twin for a power system, it is imperative that thermal models provide a reliable portrayal of the ...
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ISBN:
(数字)9798350364446
ISBN:
(纸本)9798350364453
Thermal stress is a critical failure factor for power electronics components. Hence, when developing a precise digital twin for a power system, it is imperative that thermal models provide a reliable portrayal of the component physics. In that regard, manufacturers offer simplified thermal models that enable designers and users to estimate its behaviour. Nevertheless, the accuracy of these models remains unknown, thus compromising the overall certainty of the digital twin. Therefore, it is of interest to discern whether these simplified models are sufficient for the precision required by the digital twin, and to assess the need of developing a more accurate model. Hence, this paper focuses on validating the theoretical thermal model of a power electronics switch module setup by using the deviation of the module mean time to failure (MTTF) as the acceptance parameter. To achieve this, a novel experimental validation methodology is proposed to retrieve an experimental thermal model and compare it to the theoretical one. This validation is performed considering the discrete thermal impedances and introducing the study of the coupling effects within the module.
Service Function Chaining (SFC), defines the capability of interconnecting a number of ordered Service Functions (SFs) to create composite network services. A critical issue in SFC is the autonomic fault recovery, i.e...
Service Function Chaining (SFC), defines the capability of interconnecting a number of ordered Service Functions (SFs) to create composite network services. A critical issue in SFC is the autonomic fault recovery, i.e., bringing the system back to its normal operation after a hardware or software failure. To address this challenge, in this paper, we propose a novel distributed methodology that treats the SFC Self-Healing problem in an Edge-Cloud infrastructure, while accounting for the various stakeholders. In particular, the individual SFC healing decisions are iteratively optimized and determined, while a Reinforcement Learning (RL)-based SFC-to-datacenter association procedure is realized. This process is complemented by a combinatorial auction-based resource allocation mechanism that resolves the potential SFC collocations at the end of each iteration. The proper operation, effectiveness and efficiency of our proposed healing mechanism is assessed under various evaluation scenarios.
Online customer reviews have developed into a significant source of information about a business's performance. Due to shifting consumer expectations and growing internet penetration, the Middle East, especially J...
Online customer reviews have developed into a significant source of information about a business's performance. Due to shifting consumer expectations and growing internet penetration, the Middle East, especially Jordan, is seeing an increase in the usage of online banking. This propensity toward digital transition has been accelerated by the COVID-19 pandemic. Mobile banking service companies aim to effectively use customers' feedback to identify areas for improvement in customer satisfaction. Although Arabic is becoming one of the most widely used languages on the Internet, only a few studies have focused on Arabic sentiment analysis to date. The present study conducts an extensive emotion mining and sentiment analysis on mobile banking reviews in Arabic, exploiting machine learning, natural language processing, and resampling methods to obtain subjective feedback, determine polarity, and identify customers' feelings in the banking domain. This work walks the reader through detailed steps of cleaning and preprocessing a manually annotated dataset of online banking reviews in Arabic, followed by features extraction and modeling, dataset splitting, and balancing training data. Finally, we examined classification algorithms including Decision Tree (DT), Support Vector Machine (SVM), Logistic Regression (LR), Naïve Bayes (NB), K-Nearest Neighbors (KNN), and Random Forest (RF). Ensemble hard and soft voting ML methods were also evaluated. We achieved a maximum accuracy of about 94% using the LR classifier and a maximum precision of 94% using the LR and hard voting methods. Our methodology will enable banks to acquire insights on how to develop their online presence and meet the demands of customers and stakeholders.
Modern networking paradigms like Service Function Chaining (SFC) allow for services to be broken down to a series of ordered and interconnected Virtualized Network Functions (VNFs) that can be hosted in generic server...
Modern networking paradigms like Service Function Chaining (SFC) allow for services to be broken down to a series of ordered and interconnected Virtualized Network Functions (VNFs) that can be hosted in generic servers in EdgeCloud datacenters. Nonetheless, a critical issue arises, when a hardware or software failure occurs and the VNFs of an SFC need to be repositioned, allowing to autonomously bring the system back to its normal operation, a process called self-healing. In this paper, a distributed methodology is proposed that aims to address this challenge, considering the requirements of all involved actors. Specifically, a Reinforcement Learning (RL) based algorithm is proposed that allows to iteratively optimize and determine an SFC healing solution upon a datacenter failure. As a second stage, a revenue-driven resource allocation mechanism is integrated, to resolve the contention for resources in an already functional datacenter that potentially occurs due to the repositioning. Various simulation scenarios prove the efficiency of our proposed resilient healing mechanism.
Software development involves a significant amount of team effort where collaboration and communication of the team members are crucial. The team meetings are core activities in all stages of the software development ...
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Sampled-data control via output feedback is studied for a family of strongly nonlinear systems with state and input delays. Under sample and hold, a delay-free output feedback control scheme is developed based on the ...
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ISBN:
(数字)9798350382655
ISBN:
(纸本)9798350382662
Sampled-data control via output feedback is studied for a family of strongly nonlinear systems with state and input delays. Under sample and hold, a delay-free output feedback control scheme is developed based on the emulation method, adding a power integrator (AAPI) technique, and recursive design of nonlinear observers. With the aid of Lyapunov-Krasovskii functional theorem, together with the idea of homogeneous domination, we prove that the proposed sampled-data output feedback controller makes the hybrid closed-loop systems with delays and uncertainty globally asymptotically stable, if the input delay and sampling period are limited. The family of time-delay uncertain systems under consideration goes beyond the Lipschitz or linear growth condition and is genuinely nonlinear as it contains uncontrollable/unobservable linearization and is not stabilizable, even locally, by any linear or smooth feedback. Application of the sampled-data control scheme presented in this paper is illustrated by an example with simulation.
Many countries, including Ukraine, are beginning to regulate the generation of energy produced from renewable energy sources more tightly to mitigate power imbalances. For this reason, electricity energy providers fro...
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This paper aims to develop a low-cost laser engraving machine. Materials like plastics, acrylic, glass, wood, cardboard, and leather have been used to engrave desired inputs. It have been found that this laser engravi...
This paper aims to develop a low-cost laser engraving machine. Materials like plastics, acrylic, glass, wood, cardboard, and leather have been used to engrave desired inputs. It have been found that this laser engraving process has a higher precision and accuracy as compared to traditional embellishing and embossing. The laser beam acquires thermal energy, which emerges from the machine and engraves the material. CREO 2.0 software is used for the 3D modeling and simulation of the machine. Arduino and different controller boards are tried and used in assembling the machine in less time. Different dependency and dimensional tests are conducted in order to validate the machine. The results are found to be satisfactory in terms of quality and cost. The final assembly is experimentally verified which is based on a 2D gantry that is mounted with a laser LED payload for laser engraving on various compatible materials.
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