In healthcare, remote sensing technologies are popular for smart patient health monitoring. Real-time health assessment and early intervention are possible using remote sensing data from wearable sensors and imaging e...
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Jackfruit is the national fruit of Bangladesh, and one of the most consumed fruits in India, Sri Lanka, Philippines, Indonesia, Malaysia, Australia, and many more countries. The every year due to diseases jackfruit pr...
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We propose a co-part segmentation method that takes a set of point clouds of the same category as input where neither a ground truth label nor a prior network is required. With difficulties caused by the label absence...
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Deepfake refers to an artificial intelligence-based technique to produce manipulated videos that look realistic. However, this good aspect of Deepfake sometimes pose serious threats to society as malicious intenet use...
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Artificial intelligence (AI) has emerged as a powerful tool in computational biology, where it is being used to analyze large datasets to detect difficult biological patterns. This has enabled the design of new drug m...
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Machine learning techniques have become ubiquitous both in industry and academic *** model sizes and training data volumes necessitate fast and efficient distributed training *** communications greatly simplify inter-...
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Machine learning techniques have become ubiquitous both in industry and academic *** model sizes and training data volumes necessitate fast and efficient distributed training *** communications greatly simplify inter-and intra-node data transfer and are an essential part of the distributed training process as information such as gradients must be shared between processing *** this paper,we survey the current state-of-the-art collective communication libraries(namely xCCL,including NCCL,oneCCL,RCCL,MSCCL,ACCL,and Gloo),with a focus on the industry-led ones for deep learning *** investigate the design features of these xCCLs,discuss their use cases in the industry deep learning workloads,compare their performance with industry-made benchmarks(i.e.,NCCL Tests and PARAM),and discuss key take-aways and interesting *** believe our survey sheds light on potential research directions of future designs for xCCLs.
In the intricate realm of operating systems, scheduling algorithms play a pivotal role in resource allocation and process completion, directly impacting overall system performance. The quest for an efficient and optim...
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作者：
Thakkar, DhruviGandhi, Vaibhav C.Trivedi, Dhriti
Faculty of Engineering & Technology Computer Science & Engineering Department Vadodara India
Computer Engineering Department Anand India
Computer Engineering Department Vadodara India
Nowadays, maternal health during pregnancy is a major concern, especially in rural areas where risks are increased by a lack of medical experts and poor infrastructure. The lack of effective methods for predicting mat...
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Traffic rerouting is a technique used to optimize traffic flow and reduce congestion by redirecting vehicles to alternate routes. The work done in this research focuses on a specific case scenario covering a 25 k...
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About 170 nations have been affected by the COvid VIrus Disease-19(COVID-19)*** governing bodies across the globe,a lot of stress is created by COVID-19 as there is a continuous rise in patient count testing positive,...
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About 170 nations have been affected by the COvid VIrus Disease-19(COVID-19)*** governing bodies across the globe,a lot of stress is created by COVID-19 as there is a continuous rise in patient count testing positive,and they feel challenging to tackle this *** researchers concentrate on COVID-19 data analysis using the machine learning paradigm in these *** the previous works,Long Short-Term Memory(LSTM)was used to predict future COVID-19 *** to LSTM network data,the outbreak is expected tofinish by June ***,there is a chance of an over-fitting problem in LSTM and true positive;it may not produce the required *** COVID-19 dataset has lower accuracy and a higher error rate in the existing *** proposed method has been introduced to overcome the above-mentioned *** COVID-19 prediction,a Linear Decreasing Inertia Weight-based Cat Swarm Optimization with Half Binomial Distribution based Convolutional Neural Network(LDIWCSO-HBDCNN)approach is *** this suggested research study,the COVID-19 predicting dataset is employed as an input,and the min-max normalization approach is employed to normalize *** features are selected using Linear Decreasing Inertia Weight-based Cat Swarm Optimization(LDIWCSO)algorithm,enhancing the accuracy of *** Cat Swarm Optimization(CSO)algorithm’s convergence is enhanced using inertia weight in the LDIWCSO *** is used to select the essential features using the bestfitness function *** a specified time across India,death and confirmed cases are predicted using the Half Binomial Distribution based Convolutional Neural Network(HBDCNN)technique based on selected *** demonstrated by empirical observations,the proposed system produces significant performance in terms of f-measure,recall,precision,and accuracy.
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