Bone conduction hearing aids(BCHA)actively serve patients with conductive hearing loss or external auditory canal problems,including auditory canal atresia,ossicular dislocation,*** are typically categorized into surg...
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Bone conduction hearing aids(BCHA)actively serve patients with conductive hearing loss or external auditory canal problems,including auditory canal atresia,ossicular dislocation,*** are typically categorized into surgically implanted devices,embedded directly into the skull,and adhesive devices,which transmit sound through the *** latter are advantageous for being noninvasive and suitable for children under ***,adhesive devices,due to their sound transmission method,require enhanced sound output performance compared to implanted ***,known for its low mass density yet excellent mechanical and electrical properties,finds application in various electronic ***,it serves as a diaphragm in electroacoustic transducers,enabling stable vibrations across broad frequency *** electroacoustic transducers of BCHA are typically driven by electromagnetic methods,which may be effective in low-frequency ranges but not in high-frequency *** study successfully introduced a hybrid approach that combines the complementary advantages of both electromagnetic and electrostatic modes by utilizing a graphene sheet as the diaphragm for a hybrid graphene *** electrostatic mode,which performs better in highfrequency ranges compared to the electromagnetic mode,was implemented in this hybrid *** to the measured frequency response data,the hybrid mode showed up to an 11 dB improvement compared to the electromagnetic mode and up to a 21 dB improvement compared to the electrostatic mode,exhibiting a relatively flat shape over a wide frequency ***,the device’s effectiveness as a BCHA is confirmed through experiments on rabbits,showcasing its potential in auditory aid advancement.
This paper presents a novel millimeter-wave (mmWave) antenna design for 5G applications, featuring a parasitic elliptical patch antenna with beam-switching capabilities and coaxial feeding. The antenna was initially d...
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Capacitive sensors are common ubiquitous sensing devices that permeate through many industries. The overwhelming majority of touchscreens use capacitive sensor arrays for the precise detection of touch. Many MEMS sens...
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In this paper,we propose a game theory framework to solve advanced persistent threat problems,especially considering two types of insider threats:malicious and *** this framework,we establish a unified three-player ga...
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In this paper,we propose a game theory framework to solve advanced persistent threat problems,especially considering two types of insider threats:malicious and *** this framework,we establish a unified three-player game model and derive Nash equilibria in response to different types of insider *** analyzing these Nash equilibria,we provide quantitative solutions to advanced persistent threat problems pertaining to insider ***,we have conducted a comparative assessment of the optimal defense strategy and corresponding defender's costs between two types of insider ***,our findings advocate a more proactive defense strategy against inadvertent insider threats in contrast to malicious ones,despite the latter imposing a higher burden on the *** theoretical results are substantiated by numerical results,which additionally include a detailed exploration of the conditions under which different insiders adopt risky *** conditions can serve as guiding indicators for the defender when calibrating their monitoring intensities and devising defensive strategies.
Oil spills represent significant environmental hazards in ocean ecosystems, requiring rapid and accurate detection and response mechanisms. Due to its efficacy, synthetic aperture radar (SAR) is an important tool for ...
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In this paper, we model and characterize an unconventionally wide GaN HEMT device. Each finger of the device has a width of 150 μ m which allows the modeling methodology to examine the wave propagation effects at hig...
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With the advent of generative artificial intelligence (AI), the scope of data analysis, prediction of performances, real-time feedback, etc. in learning analytics has widened. The purpose of this study is to explore t...
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Mobile technology is developing *** phone technologies have been integrated into the healthcare industry to help medical ***,computer vision models focus on image detection and classification ***2 is a computer vision...
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Mobile technology is developing *** phone technologies have been integrated into the healthcare industry to help medical ***,computer vision models focus on image detection and classification ***2 is a computer vision model that performs well on mobile devices,but it requires cloud services to process biometric image information and provide predictions to *** leads to increased *** biometrics image datasets on mobile devices will make the prediction faster,but mobiles are resource-restricted devices in terms of storage,power,and computational ***,a model that is small in size,efficient,and has good prediction quality for biometrics image classification problems is *** pre-trained CNN(PCNN)MobileNetV2 architecture combined with a Support Vector Machine(SVM)compacts the model representation and reduces the computational cost and memory *** proposed novel approach combines quantized pre-trained CNN(PCNN)MobileNetV2 architecture with a Support Vector Machine(SVM)to represent models efficiently with low computational cost and *** contributions include evaluating three CNN models for ocular disease identification in transfer learning and deep feature plus SVM approaches,showing the superiority of deep features from MobileNetV2 and SVM classification models,comparing traditional methods,exploring six ocular diseases and normal classification with 20,111 images postdata augmentation,and reducing the number of trainable *** model is trained on ocular disorder retinal fundus image datasets according to the severity of six age-related macular degeneration(AMD),one of the most common eye illnesses,Cataract,Diabetes,Glaucoma,Hypertension,andMyopia with one class *** the experiment outcomes,it is observed that the suggested MobileNetV2-SVM model size is *** testing accuracy for MobileNetV2-SVM,InceptionV3,and MobileNetV2 is 90.11%,86.88%,a
This paper investigates how distributed energy resources investment capacities impact the carbon footprint of a renewable energy community. The investigation is conducted through the formulation of an optimisation pro...
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Lie detection has gained importance and is now extremely significant in a variety of fields. It plays an important role in several domains, including law enforcement, criminal investigations, national security, workpl...
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Lie detection has gained importance and is now extremely significant in a variety of fields. It plays an important role in several domains, including law enforcement, criminal investigations, national security, workplace ethics, and personal relationships. As advances in lie detection continue to develop, real-time approaches such as voice stress technology have emerged as a feasible alternative to traditional methods such as polygraph testing. Polygraph testing, a historical and generally established approach, may be enhanced or replaced by these revolutionary real-time techniques. Traditional lie detection procedures, such as polygraph testing, have been challenged for their lack of reliability and validity. Newer techniques, such as brain imaging and machine learning, might offer better outcomes, although they are still in their early phases and require additional testing. This project intends to explore a deception-detection module based on sophisticated speech-stress analysis techniques that might be applied in a real-time deception system. The purpose is to study stress and other articulation cues in voice patterns, to establish their precision and reliability in detecting deceit, by building upon previous knowledge and applying state-of-the-art architecture. The performance and accuracy of the system and its audio aspects will be thoroughly analyzed. The ultimate purpose is to contribute to the advancement of more accurate and reliable lie-detection systems, by addressing the limitations of old techniques and proposing practical solutions for varied applications. This paper proposes an efficient feature-selection strategy, which uses random forest (RF) to select only the significant features for training when a real-life trial dataset consisting of audio files is employed. Next, utilizing the RF as a classifier, an accuracy of 88% is reached through comprehensive evaluation, thereby confirming its reliability and precision for lie-detection in real-time scena
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