This paper proposes a pulse skipping based combined frequency and duty ratio control for a series resonant converter which is targeted for voltage regulator applications. The proposed pulse skipping control combines d...
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This article introduces a novel model for low-quality pedestrian trajectory prediction, the social nonstationary transformers (NSTransformers), that merges the strengths of NSTransformers and spatiotemporal graph tran...
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This study examines how Predictive Analytics may alter company decision-making by employing sophisticated data-driven insights to improve strategic decisions. The report examines predictive analytics' methods, alg...
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In this paper, a new scheme is proposed to stabilize a class of nonlinear systems within a designated time, mainly motivated by two unsolved problems: the singularity caused by infinity control magnitudes at the presc...
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Knee Osteoarthritis (OA) is a prevalent musculoskeletal disorder that affects the knee joint that causes pain, stiffness, and reduced mobility. It is also known as "Degenerative Joint Disease" and is caused ...
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Knee Osteoarthritis (OA) is a prevalent musculoskeletal disorder that affects the knee joint that causes pain, stiffness, and reduced mobility. It is also known as "Degenerative Joint Disease" and is caused by the degeneration of cartilage in the knee joint, leading to bone-on-bone contact and further damage. Knee OA is prevalent in the population, affecting around 22% to 39% of people in India, and there is currently no treatment available that can halt the progression of the disease. Therefore, early diagnosis and management of symptoms are essential to reduce its impact on an individual’s quality of life. To address this issue, have introduced a framework that leverages ConvNeXt architecture, a modernization of ResNets (ResNet-50) architecture towards Hierarchical Transformers (Swin Transformers), to provide accurate identification and classification of knee osteoarthritis. The classification of knee osteoarthritis was done using the Kellgren and Lawrence (KL) graded X-ray images. These images of the damaged knees are preprocessed and augmented, creating a scaled, enhanced, and varied version of the features, thus making the data fitter and more significant for classification. The performance estimation of the proposed strategy is conducted on the Osteoarthritis Initiative (OAI), a research project focused on knee osteoarthritis that works in partnership with NIH and other private industries to develop a public domain dataset that can facilitate research and evaluation. It involves training the prepared data using various hyper-tuned versions of ConvNeXt. The different fine-tuned results of the ConvNeXt models on each KL Grade are evaluated against the other state-of-the-art models and vision transformers. The comparative assessment of widely used performance measures shows that the proposed approach outperforms the conventional models by generating the highest score for all the KL grades. Lastly, an approach is employed to statistically confirm the validity of t
As sustainability/sustainable development (S/SD) is still considered the buzzword in manufacturing environments, particularly after showing up and joining Industry 4.0 (I4.0), S/SD is prescribed to be embraced as one ...
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Currently, researchers are concentrating their attention on design for manufacturing, design for assembly, design for cost and design for quality, design for complexity, design for reconfiguration, design for sustaina...
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We propose an ASIC architecture for key switching in RNS-CKKS Homomorphic Encryption scheme. With the pipeline design, the frequent RAM access is avoided and high throughput is achieved. This key switching design is a...
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Resonant converters are widely used for voltage regulator applications. The basic converters i.e., Series resonant Converter (SRC) and Parallel Resonant Converter (PRC) are having some merits and limitations. These ar...
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Quantifying the number of individuals in images or videos to estimate crowd density is a challenging yet crucial task with significant implications for fields such as urban planning and public *** counting has attract...
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Quantifying the number of individuals in images or videos to estimate crowd density is a challenging yet crucial task with significant implications for fields such as urban planning and public *** counting has attracted considerable attention in the field of computer vision,leading to the development of numerous advanced models and *** approaches vary in terms of supervision techniques,network architectures,and model ***,most crowd counting methods rely on fully supervised learning,which has proven to be ***,this approach presents challenges in real-world scenarios,where labeled data and ground-truth annotations are often *** a result,there is an increasing need to explore unsupervised and semi-supervised methods to effectively address crowd counting tasks in practical *** paper offers a comprehensive review of crowd counting models,with a particular focus on semi-supervised and unsupervised approaches based on their supervision *** summarize and critically analyze the key methods in these two categories,highlighting their strengths and ***,we provide a comparative analysis of prominent crowd counting methods using widely adopted benchmark *** believe that this survey will offer valuable insights and guide future advancements in crowd counting technology.
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