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413 articles for “G. Kumar”
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Research ArticleOpen accessIn the author namesImplementing a Hybrid VMD–BiTCN–BiGRU Architecture With Intelligent Optimization for Agricultural Commodity Price Prognostication in Gujarat MarketsJignesh Hirapara, Ratnesh Kumar Namdeo, Ankit Kumar Dubey et al.In the agricultural sector, the prices of pulses require adequate forecasting to plan farming activities, store and market, and guide policy-making. However, the pulse price series is highly volatile, seasonal, nonstationary, and nonlinear, and thus conventional linear time series models are not necessarily very effective. In the suggested framework, the raw price data series is decomposed using Variational Mode Decomposition … …Journal of Computer Science, Vol. 22, Issue 7 · 1 Aug 2026 · 1,021 accessesView PDFCite
Research ArticleOpen accessIn the author namesDeveloping an Effective Churn Prediction Model for Telecommunications: Enhancing Customer Retention through Advanced Machine Learning TechniquesAshu Goyal, Anuj Gupta, Sharad Kumar et al.Customer churn poses a significant challenge for the telecommunications sector, resulting in substantial revenue losses and increased customer acquisition costs. This research creates an efficient churn prediction model that combines state-of-the-art machine learning with ensemble learning to maximize customer retention. With the IBM Telco Customer Churn dataset, several baseline models, including Gradient Boosting, AdaBoost, Logistic Regression, Random Forest, and Support … …Journal of Computer Science, Vol. 22, Issue 1 · 3 Feb 2026 · 3,164 accessesView PDFCite
Research ArticleOpen accessIn the author namesFew-shot Fine-tuning of BERT Multilingual for Hindi Word Sense DisambiguationShailendra Kumar Patel, Rakesh Kumar, Anuj Kumar SirohiWord Sense Disambiguation (WSD) is a fundamental task in Natural Language Processing (NLP), addressing the challenge of identifying correct word meanings in context. This task is particularly complex for morphologically rich and resource-limited languages like Hindi, which exhibit significant lexical ambiguity compounded by limited availability of annotated corpora. To address these challenges, we propose a supervised approach combining the multilingual … …Journal of Computer Science, Vol. 21, Issue 11 · 26 Dec 2025 · 2,250 accessesView PDFCite
Research ArticleOpen accessIn the author namesAn Active Learning Ensemble Framework for Tropical Crop Yield PredictionAmol Bhilare, Debabrata Swain, Megh Patel et al.Agriculture always has great importance among all different sectors, not only in the world but also in India. It has a significant impact on food security and largely controls the economy. At present, technological advancements have significantly enhanced agricultural productivity, but it can still be further improved by the integration of new cutting-edge techniques like Artificial intelligence. Among the factors … …Journal of Computer Science, Vol. 22, Issue 9 · 11 Sep 2026 · 819 accessesView PDFCite
Research ArticleOpen accessIn the author namesChronic Lung Disease Identification in Chest CT Scans Through Hybrid Deep Transfer Learning FrameworkGarima Jain, Amit Kumar Goel, Rahul KumarAccurate and timely diagnosis is essential for successful treatment of chronic pulmonary conditions, particularly lung tumours. To capture more complicated pathological characteristics, diagnostic algorithms based on current data sets are restricted to using older databases and single branch systems. This research introduces a new solution: A hybrid deep learning model applied to a recently released quantitative database of CT scans … …Journal of Computer Science, Vol. 22, Issue 8 · 9 Sep 2026 · 651 accessesView PDFCite
Research ArticleOpen accessIn the author namesExplainable MedAttn-ResNet50 for Automated Kidney Tumor Classification from CT Images With Grad-CAM VisualizationD. Vetrithangam, Pramod Kumar, Shilpasree S. et al.Kidney tumor classification from CT imaging remains challenging due to CT-specific intensity variations, tumor heterogeneity, and limited clinically meaningful interpretability in existing deep learning models. To address these limitations, we propose an Explainable MedAttn-ResNet50 framework that integrates radiology-driven preprocessing, multi-scale feature extraction, and medical attention mechanisms within a unified architecture. The preprocessing pipeline applies radiology-inspired intensity normalization, contrast enhancement, and … …Journal of Computer Science, Vol. 22, Issue 8 · 13 Aug 2026 · 1,120 accessesView PDFCite
Research ArticleOpen accessIn the author namesA Machine Learning-Based Sentiment Analysis of Article 370 Tweets to Support Government Policy DecisionsSubhasis Mohapatra, Sudhir Kumar Mohapatra, Sweta Samantaray et al.This study proposes a robust sentiment analysis framework to evaluate public opinion on the abrogation of Article 370 using Twitter data. The methodology begins with tweet collection through the Twitter API, followed by systematic preprocessing. Sentiment labels were generated using the Text Blob lexicon-based polarity scoring approach to facilitate the construction of a large-scale sentiment dataset. Features are extracted, and … …Journal of Computer Science, Vol. 22, Issue 6 · 2 Jul 2026 · 914 accessesView PDFCite
Research ArticleOpen accessIn the author namesEffects of Dietary Emamectin Benzoate at Recommended and Overdose Levels on the Pathophysiological Responses and Tolerability of Oreochromis niloticus at Fry StageJasmine Singha, Thangapalam Jawahar Abraham, Satyen Kumar Panda, Prasanna Kumar PatilEmamectin Benzoate (EB) has been recommended as a feed additive for the control of fish ectoparasites. This investigation examined the impact of dietary EB on physiological responses, antioxidant defence mechanisms, and histopathological changes in key organs, and on the kinetics of residue deposition and elimination in the muscle of Oreochromis niloticus fry. Fry were administered EB feeds at 50 µg … …American Journal of Pharmacology and Toxicology, Vol. 20, Issue 1 · 1 Jul 2026 · 1,469 accessesView PDFCite
Research ArticleOpen accessIn the author namesMedFusion: A Unified Multimodal Framework for Visual Question Answering and Explainable Medical RecommendationSatyajit Mahapatra, Jibitesh Mishra, Kumar Janardan Patra et al.In clinical decision-making, the ability to ask visual questions about medical images and receive accurate, personalized, and interpretable recommendations can significantly enhance practitioner support systems. This paper presents MedFusion, a unified multimodal framework that integrates Visual Question Answering (VQA), personalized medical recommendation, and explainability within a single architecture. The proposed model employs co-attention–based visual–textual fusion augmented with retrieval-enhanced reasoning to … …Journal of Computer Science, Vol. 22, Issue 5 · 20 May 2026 · 1,360 accessesView PDFCite
Review ArticleOpen accessIn the author namesA Systematic Review of Adversarial Attacks: ML Techniques, Classification and CountermeasuresBhavesh Kumar Sharma, Sanatan Ratna, Rajiv KumarMachine Learning (ML) and Deep Learning (DL)-based technologies have made significant strides in areas such as computer vision, natural language processing, and autonomous systems. Yet they have been applied in high-stake applications, and have been found to be fragile through adversarial attacks-, maliciously crafted small distortions that fool models into making mistakes. From the pioneering work by Szegedy et al. … …Journal of Computer Science, Vol. 22, Issue 5 · 19 May 2026 · 1,497 accessesView PDFCite