Integrating distributed energy resources (DERs) into a power system requires more advanced control mechanisms. One of the control strategies used for Volt-VAR control (VVC) is to manage voltage and reactive power. Wit...
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Anaemia, a condition characterised by reduced haemoglobin levels, exerts a significant global impact, affecting billions of individuals worldwide. According to data from the World Health Organisation (WHO), India exhi...
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Electrocardiography (ECG) is a commonly used diagnostic tool in the clinical setting for detecting cardiovascular diseases (CVDs). However, its manual interpretation can be time-consuming and prone to human error. Wit...
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This study explores the impact of hyperparameter optimization on machine learning models for predicting cardiovascular disease using data from an IoST(Internet of Sensing Things)*** distinct machine learning approache...
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This study explores the impact of hyperparameter optimization on machine learning models for predicting cardiovascular disease using data from an IoST(Internet of Sensing Things)*** distinct machine learning approaches were implemented and systematically evaluated before and after hyperparameter *** improvements were observed across various models,with SVM and Neural Networks consistently showing enhanced performance metrics such as F1-Score,recall,and *** study underscores the critical role of tailored hyperparameter tuning in optimizing these models,revealing diverse outcomes among *** Trees and Random Forests exhibited stable performance throughout the *** enhancing accuracy,hyperparameter optimization also led to increased execution *** representations and comprehensive results support the findings,confirming the hypothesis that optimizing parameters can effectively enhance predictive capabilities in cardiovascular *** research contributes to advancing the understanding and application of machine learning in healthcare,particularly in improving predictive accuracy for cardiovascular disease management and intervention strategies.
The challenge of bankruptcy prediction, critical for averting financial sector losses, is amplified by the prevalence of imbalanced datasets, which often skew prediction models. Addressing this, our study introduces t...
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This systematic literature review delves into the dynamic realm of graphical passwords, focusing on the myriad security attacks they face and the diverse countermeasures devised to mitigate these threats. The core obj...
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The fifth generation (5G) of wireless communication networks uses the advantages of Massive Multiple-Input Multiple-Output (MIMO) technologies to improve network coverage, increase data speeds, and enhance reliability...
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This work presents a new class of micromachined electrostatic actuators capable of producing output force and displacement unprecedented for MEMS electrostatic *** actuators feature submicron high aspect ratio transdu...
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This work presents a new class of micromachined electrostatic actuators capable of producing output force and displacement unprecedented for MEMS electrostatic *** actuators feature submicron high aspect ratio transduction gaps lined up in two-dimensional *** an arrangement of microscale actuator cells allows the addition of force and displacements of a large number of cells(up to 7600 in one demonstrated array),leading to displacements ranging in the hundreds of microns and several gram forces of axial *** 50μm thick actuators with horizontal dimensions in the 1-4 millimeter range,an out-of-plane displacement of up to 678μm at 46 V,a bending moment of up to 2.0μNm,i.e.,0.08 N(~8 gram-force)of axial force over a 50μm by 2 mm cross-sectional area of the actuator(800 kPa of electrostatically generated stress),and an energy density(mechanical work output per stroke per volume)up to 1.42 mJ/cm3 was demonstrated for the actuators.
The provision of rebate to needy/underprivileged sections of society has been in practice since long in government organizations. The efficacy of such provisions lies in the fact that whether this rebate reaches peopl...
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Hearing and Speech impairment can be congenital or *** and speech-impaired students often hesitate to pursue higher education in reputable institutions due to their ***,the development of automated assistive learning ...
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Hearing and Speech impairment can be congenital or *** and speech-impaired students often hesitate to pursue higher education in reputable institutions due to their ***,the development of automated assistive learning tools within the educational field has empowered disabled students to pursue higher education in any field of *** learning devices enable students to access institutional resources and facilities *** proposed assistive learning and communication tool allows hearing and speech-impaired students to interact productively with their teachers and *** tool converts the audio signals into sign language videos for the speech and hearing-impaired to follow and converts the sign language to text format for the teachers to *** educational tool for the speech and hearing-impaired is implemented by customized deep learning models such as Convolution neural networks(CNN),Residual neural Networks(ResNet),and stacked Long short-term memory(LSTM)network *** assistive learning tool is a novel framework that interprets the static and dynamic gesture actions in American Sign Language(ASL).Such communicative tools empower the speech and hearing impaired to communicate effectively in a classroom environment and foster *** deep learning models were developed and experimentally evaluated with the standard performance *** model exhibits an accuracy of 99.7% for all static gesture classification and 99% for specific vocabulary of gesture action *** two-way communicative and educational tool encourages social inclusion and a promising career for disabled students.
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