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| 1 | Resource management with hoses:Point-to-cloud services for virtual private networks显示文摘 | N G Duffield Pawan Goyal | 2002 | IEEE/ACM Transactions on Networking2002，10，5： | 1 |
| 2 | A rare case of pulmonary alveolar hemorrhage with cardiomyopathy 显示文摘 | Gopi Khilnani Pawan Tiwari Alpesh Goyal | 2012 | Chest2012，142，4： | 1 |
| 3 | Generalized guaranteed rate scheduling algorithms: a framework 显示文摘 | Goyal Pawan Vin Harrick | 1997 | IEEE/ACM Transactions on Networking1997，5，4： | 1 |
| 4 | CrysXPP:An explainable property predictor for crystalline materials显示文摘We present a deep-learning framework,CrysXPP,to allow rapid and accurate prediction of electronic,magnetic,and elastic properties of a wide range of materials.CrysXPP lowers the need for large property tagged datasets by intelligently designing an autoencoder,CrysAE.The important structural and chemical properties captured by CrysAE from a large amount of available crystal graphs data helped in achieving low prediction errors.Moreover,we design a feature selector that helps to interpret the model’s prediction.Most notably,when given a small amount of experimental data,CrysXPP is consistently able to outperform conventional DFT.A detailed ablation study establishes the importance of different design steps.We release the large pre-trained model CrysAE.We believe by fine-tuning the model with a small amount of property-tagged data,researchers can achieve superior performance on various applications with a restricted data source. | Kishalay Das Bidisha Samanta Pawan Goyal Seung-Cheol Lee Satadeep Bhattacharjee Niloy Ganguly | 2022 | npj Computational Materials2022，，1： | 1 |
| 5 | A context-based word indexing model for document summariza-tion 显示文摘 | Pawan Goyal Laxmidhar Behera Thomas Martin McGinnity | 2013 | IEEE Transactions on Knowledge and Data Enginee- ring2013，25，8： | 1 |
| 6 | A novel neighborhood based document smoothing model for information retrieval显示文摘 | Pawan Goyal Laxmidhar Behera T. M. McGinnity | 2013 | Information Retrieval2013，，3： | 1 |
| 7 | Malignant peripheral nerve sheath tumor of proximal third tibia显示文摘A 16-year-old man had aswelling over the anterior aspect of the proximal third of the tibia for 1 year, which was peanut size initially and progressively increased to its present size of 10 cm × 8 cm. He underwent fine needle aspiration cytology(FNAC) twice during this period and reported aspindle cell sarcoma. Malignant peripheral nerve sheath tumor(MPNST) is a malignancy of the connective tissue surrounding the nerves. Previously, MPNST was also known as neurofibrosarcoma, malignant schwannoma, andneurogenic sarcoma. We are reporting this case for its rarity and peculiar mode of presentation. FNAC/core biopsy can be used as an effective tool to achievethe correct pathological diagnosis. | Arunkumar Rao Sachin B Ingle Pawan Rajurkar Vishav Goyal Nikhil Dokrimare | 2015 | World Journal of Clinical Oncology2015，6，5： | 1 |
| 8 | A model on the biological treatment of saline wastewater显示文摘 | Ashish Goyal Pawan Sharma | 2017 | International Journal of Biomathematics2017，10，2： | 0 |
| 9 | An artificial neural network for surrogate modeling of stress fields in viscoplastic polycrystalline materials显示文摘The purpose of this work is the development of a trained artificial neural network for surrogate modeling of the mechanical response of elasto-viscoplastic grain microstructures.To this end,a U-Net-based convolutional neural network(CNN)is trained using results for the von Mises stress field from the numerical solution of initial-boundary-value problems(IBVPs)for mechanical equilibrium in such microstructures subject to quasi-static uniaxial extension.The resulting trained CNN(tCNN)accurately reproduces the von Mises stress field about 500 times faster than numerical solutions of the corresponding IBVP based on spectral methods.Application of the tCNN to test cases based on microstructure morphologies and boundary conditions not contained in the training dataset is also investigated and discussed. | Mohammad S.Khorrami Jaber R.Mianroodi Nima H.Siboni Pawan Goyal Bob Svendsen Peter Benner Dierk Raabe | 2023 | npj Computational Materials2023，，1： | 0 |
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