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pro vyhledávání: '"P. Bharath Kumar"'
The applicability domain refers to the range of data for which the prediction of the predictive model is expected to be reliable and accurate and using a model outside its applicability domain can lead to incorrect results. The ability to define the
Externí odkaz:
http://arxiv.org/abs/2411.00920
Autor:
Subbaih, Kalpa, Bolla, Bharath Kumar
The surge of e-commerce reviews has presented a challenge in manually annotating the vast volume of reviews to comprehend their underlying aspects and sentiments. This research focused on leveraging weakly supervised learning to tackle aspect categor
Externí odkaz:
http://arxiv.org/abs/2312.15526
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract Breast cancer remains a leading cause of mortality among women worldwide, with drug resistance driven by transcription factors and mutations posing significant challenges. To address this, we present ResisenseNet, a predictive model for drug
Externí odkaz:
https://doaj.org/article/29576b4f395840f3b8fc9ad5e03e713a
Publikováno v:
Electronic Journal of Plant Breeding, Vol 15, Iss 3, Pp 782-793 (2024)
Combining ability and heterosis was investigated in mustard hybrids obtained from 7 × 7 half diallel cross. Twenty one F1s along with seven parents were evaluated in Randomized Complete Block Design. The combined analysis of variance revealed very s
Externí odkaz:
https://doaj.org/article/d6b57db3e8be462e92d80aecbf322183
Publikováno v:
Discover Internet of Things, Vol 4, Iss 1, Pp 1-30 (2024)
Abstract The global population is rapidly increasing, so there is a critical requirement to satisfy the food production demand. Conventional methods of agriculture are inadequate to meet building demand which leads to declining farming sector and ada
Externí odkaz:
https://doaj.org/article/ccebcbede8704797832c41854b5aa32a
Time series forecasting has seen many methods attempted over the past few decades, including traditional technical analysis, algorithmic statistical models, and more recent machine learning and artificial intelligence approaches. Recently, neural net
Externí odkaz:
http://arxiv.org/abs/2306.13931
The present study aimed to address the issue of imbalanced data in classification tasks and evaluated the suitability of SMOTE, ADASYN, and GAN techniques in generating synthetic data to address the class imbalance and improve the performance of clas
Externí odkaz:
http://arxiv.org/abs/2306.13929
Autor:
C. Sangeetha, Malathi Anil Kumar, Aparna Bathalapalli, K Bharath Kumar, G Malashree, Vijayakumar M Heggeri
Publikováno v:
Acta Medica International, Vol 11, Iss 2, Pp 120-125 (2024)
Introduction: Supraclavicular approaches serve as a common method for administering regional anesthesia in upper limb procedures. In improving the impact with a length of pain relief, medical professionals frequently include additional substances suc
Externí odkaz:
https://doaj.org/article/ebc21dc694b74fe898d937d185d8bd73
When arranging objects with robotic arms, the quality of the end result strongly depends on the achievable placement accuracy. However, even the most advanced robotic systems are prone to positioning errors that can occur at different steps of the ma
Externí odkaz:
http://arxiv.org/abs/2302.07795
Autor:
Meghna Jiwanmall, Jerry Joseph Joel, Aparna Williams, Stephen Amarjeet Jiwanmall, Bharath Kumar, Ekta Rai
Publikováno v:
Current Medical Issues, Vol 22, Iss 2, Pp 87-96 (2024)
Background: Numerous studies have reported the prevalence of psychological issues in anesthesia professionals during stressful situations like the COVID-19 pandemic; however, there are limited data exploring the coping strategies and work satisfactio
Externí odkaz:
https://doaj.org/article/c24eda3f9dc940318943b002b6fdcd06