This paper demonstrates the novel approach of sub-micron-thick InGaAs broadband photodetectors(PDs)designed for high-resolution imaging from the visible to short-wavelength infrared(SWIR)*** approaches encounter chall...
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This paper demonstrates the novel approach of sub-micron-thick InGaAs broadband photodetectors(PDs)designed for high-resolution imaging from the visible to short-wavelength infrared(SWIR)*** approaches encounter challenges such as low resolution and crosstalk issues caused by a thick absorption layer(AL).Therefore,we propose a guided-mode resonance(GMR)structure to enhance the quantum efficiency(QE)of the InGaAs PDs in the SWIR region with only sub-micron-thick *** TiOx/Au-based GMR structure compensates for the reduced AL thickness,achieving a remarkably high QE(>70%)from 400 to 1700 nm with only a 0.98μm AL InGaAs PD(defined as 1μm AL PD).This represents a reduction in thickness by at least 2.5 times compared to previous results while maintaining a high ***,the rapid transit time is highly expected to result in decreased electrical *** effectiveness of the GMR structure is evident in its ability to sustain QE even with a reduced AL thickness,simultaneously enhancing the transit *** breakthrough offers a viable solution for high-resolution and low-noise broadband image sensors.
Handwriting is an important skill for children during their academic years. It is the coordination of perceptual-motor and cognitive abilities. Some children have difficulties in handwriting, which is an indication of...
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Reversible data hiding is an information hiding technique that requires the retrieval of the error free cover image after the extraction of the secret *** suggested a technique in this research that uses a recursive e...
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Reversible data hiding is an information hiding technique that requires the retrieval of the error free cover image after the extraction of the secret *** suggested a technique in this research that uses a recursive embedding method to increase capacity substantially using the Integer wavelet transform and the Arnold *** notion of Integer wavelet transforms is to ensure that all coefficients of the cover images are used during embedding with an increase in *** scrambling the cover image,Arnold transform adds security to the information that gets embedded and also allows embedding more information in each *** hybrid combination of Integer wavelet transform and Arnold transform results to build a more efficient and secure *** proposed method employs a set of keys to ensure that information cannot be decoded by an *** experimental results show that it aids in the development of a more secure storage system and withstand few tampering attacks The suggested technique is tested on many image formats,including medical *** performance metrics proves that the retrieved cover image and hidden image are both *** System is proven to withstand rotation attack as well.
The concept of a medical intelligent system has steadily garnered attention as modern technology advances. An intelligent medical system is a medical system that develops a certain amount of intelligence and performs ...
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Text Summarization models facilitate biomedical clinicians and researchers in acquiring informative data from enormous domain-specific literature within less time and *** and selecting the most informative sentences f...
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Text Summarization models facilitate biomedical clinicians and researchers in acquiring informative data from enormous domain-specific literature within less time and *** and selecting the most informative sentences from biomedical articles is always *** study aims to develop a dual-mode biomedical text summarization model to achieve enhanced coverage and *** research also includes checking the fitment of appropriate graph ranking techniques for improved performance of the summarization *** input biomedical text is mapped as a graph where meaningful sentences are evaluated as the central node and the critical associations between *** proposed framework utilizes the top k similarity technique in a combination of UMLS and a sampled probability-based clustering method which aids in unearthing relevant meanings of the biomedical domain-specific word vectors and finding the best possible associations between crucial *** quality of the framework is assessed via different parameters like information retention,coverage,readability,cohesion,and ROUGE scores in clustering and non-clustering *** significant benefits of the suggested technique are capturing crucial biomedical information with increased coverage and reasonable memory *** configurable settings of combined parameters reduce execution time,enhance memory utilization,and extract relevant information outperforming other biomedical baseline *** improvement of 17%is achieved when the proposed model is checked against similar biomedical text summarizers.
In this paper, machine learning based method for the estimation of solar radiation in earth surface is presented. To design the machine learning model, multispectral (visible and infrared) satellite images of the very...
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Clinical gait analysis plays a vital role in diagnosis and monitoring neurological and musculoskeletal injuries. Qualitative gait assessment depends on subjective observations, manual measurements, and specialized equ...
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ISBN:
(纸本)9798350364866;9798350364873
Clinical gait analysis plays a vital role in diagnosis and monitoring neurological and musculoskeletal injuries. Qualitative gait assessment depends on subjective observations, manual measurements, and specialized equipment. Recently machine learning and deep learning based models have demonstrated significant accuracy in gait analysis. But dynamic feature extraction is always a challenging problem in temporal gait data analysis. After extracting dynamic features, a Fully-connected Neural Network (FNN) is employed to classify of gait abnormalities using GaitRec standard dataset. The proposed multi-modal features based classification model achieves 96.22% accuracy and it outperforms state-of-the-art methods.
The AI-Enhanced Learning Assistant Platform is a revolutionary system designed to enhance learning, with cutting-edge features like question and answer generation, answer evaluation, identification of weak areas, recu...
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In the recent era of technology, the internet of things (IoT) plays a tremendous role in enhancing the quality of human life through smart devices and sensing the real-world environment. IoT aims to interconnect anyth...
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The pandemic creates a more complicated providence of medical assistance and diagnosis procedures. In the world, Covid-19, Severe Acute Respiratory Syndrome Coronavirus-2 (SARS Cov-2), and plague are widely known...
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The pandemic creates a more complicated providence of medical assistance and diagnosis procedures. In the world, Covid-19, Severe Acute Respiratory Syndrome Coronavirus-2 (SARS Cov-2), and plague are widely known pandemic disease desperations. Due to the recent COVID-19 pandemic tragedies, various medical diagnosis models and intelligent computing solutions are proposed for medical applications. In this era of computer-based medical environment, conventional clinical solutions are surpassed by many Machine Learning and Deep Learning-based COVID-19 diagnosis models. Anyhow, many existing models are developing lab-based diagnosis environments. Notably, the Gated Recurrent Unit-based Respiratory Data Analysis (GRU-RE), Intelligent Unmanned Aerial Vehicle-based Covid Data Analysis (Thermal Images) (I-UVAC), and Convolutional Neural Network-based computer Tomography Image Analysis (CNN-CT) are enriched with lightweight image data analysis techniques for obtaining mass pandemic data at real-time conditions. However, the existing models directly deal with bulk images (thermal data and respiratory data) to diagnose the symptoms of COVID-19. Against these works, the proposed spectacle thermal image data analysis model creates an easy and effective way of disease diagnosis deployment strategies. Particularly, the mass detection of disease symptoms needs a more lightweight equipment setup. In this proposed model, each patient's thermal data is collected via the spectacles of medical staff, and the data are analyzed with the help of a complex set of capsule network functions. Comparatively, the conventional capsule network functions are enriched in this proposed model using adequate sampling and data reduction solutions. In this way, the proposed model works effectively for mass thermal data diagnosis applications. In the experimental platform, the proposed and existing models are analyzed in various dimensions (metrics). The comparative results obtained in the experiments just
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