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| 1 | “泉城”地下水补给区脆弱性评价研究显示文摘济南市素以丰富的地下水和泉水闻名于世。然而目前的地下水过度开采和土地利用变化等因素导致了泉水景观与水环境质量降低。综合评价济南市地下水的脆弱性,有利于长期保护和管理地下水资源,促进区域可持续发展。 | 李大秋 Barnali Dixon Julie Earls Fred Bradley 刘新华 | 2007 | 环境保护2007，35，08B： | 2 |
| 2 | Recapturing Public Power: ls Investment Arbitration's Engagement of the Public Interest Contributing to the Democratic Deficit?显示文摘 | Choudhury Barnali | 2008 | Vanderbilt Journal of Transnational Law2008，，： | 1 |
| 3 | Novel feature selection algorithm using particle swarm optimization for cancer microarray data显示文摘 | Barnali S H Debahuti M A | 2012 | International Conference on Modelling Optimization and Comput- ing2012，38，： | 1 |
| 4 | A multivariate cointegrating vector auto regressive model of freight transport demand: evidence from Indian railways 显示文摘 | MUDIT KULSHRESHTHA BARNALI NAG | 2001 | Transportation Research Part A2001，，35： | 1 |
| 5 | Where to Locate in a Circular City? 显示文摘 | Barnali Gupta Lai Fu-Chuan Debashis Pal | 2004 | International Journal of Industrial Orgaziation2004，22，6： | 1 |
| 6 | Recapturing Public Power: Is Invest- ment Arbitration' s Engagement of the Public Interest Contributing to the Democratic Deficit? 显示文摘 | Barnali Choudhury | 2008 | Vanderbih Journal of Transnational Law2008，，41： | 1 |
| 7 | Odanacatib, a selective cathepsin K inhibitor to treat osteoporosis: safety, tolerability, pharmacokinetics and pharmacodynamics – results from single oral dose studies in healthy volunteers显示文摘 | S. Aubrey Stoch Stefan Zajic Julie A. Stone Deborah L. Miller Lucas Bortel Kenneth C. Lasseter Barnali Pramanik Caroline Cilissen Qi Liu Lida Liu Boyd B. Scott Deborah Panebianco Yu Ding Keith Gottesdiener John A. Wagner | 2013 | Br J Clin Pharmacol2013，，5： | 1 |
| 8 | Spatial Cournot Competition and Agglomeration in a Model of Location Choice 显示文摘 | Barnali Gupta Debashis Pal Jyotirmoy Sarkar | 1997 | Regional Science and Urban Economics1997，，27： | 1 |
| 9 | Ultrasound-based treatment approaches for intrinsic viscosity reduction of polyvinyl pyrrolidone (PVP)显示文摘 | Indrajeet A. Pawar Prathmesh J. Joshi Akshay D. Kadam Nishant B. Pande Priyanka H. Kamble Shruti P. Hinge Barnali S. Banerjee Ashish V. Mohod Parag R. Gogate | 2013 | Ultrasonics - Sonochemistry2013，，： | 1 |
| 10 | QTL mapping of yield, agronomic and quality traits in tetraploid potato (Solanum tuberosum subsp. tuberosum)显示文摘 | John E. Bradshaw Christine A. Hackett Barnaly Pande Robbie Waugh Glenn J. Bryan | | 0，，： | 1 |
| 11 | Carbon Emission Intensity of Power Consumption in India: A Detailed Study of its Indicators显示文摘 | Barnali Nag Mudit Kulshreshtha | 2000 | Energy Sources Part A: Recovery Utilization and Environmental Effects2000，，2： | 1 |
| 12 | Strontium isotopic signatures of oil-field waters: Applications for reservoir characterization显示文摘 | Roger J Barnaly Gregg C | 2004 | AAPG Bulletin2004，80，12： | 1 |
| 13 | Beyond the Alien Tort Claims Act:Alternative Approaches to Attributing Liability to Corporations for Extraterritorial Abuses显示文摘 | Barnali Choudhury | 2005 | Northwestern Journal of International Law & Business2005，，： | 1 |
| 14 | Hot mold casting process of ancient East India and Bangladesh显示文摘Ancient casting process for production of brass or bronze utensils and icons were made in hot molds using clay molded investment casting or piece mold process,as presumed by archaeologists.Piece mold process is still traditionally practiced in many parts of Eastern India and Bangladesh along with investment casting process.Incidentally,Bengal artisans are more accustomed to piece mold process unlike tribal artisans who practiced investment casting process.This piece mold casting process has been reconstructed to get the idea of metal characteristics in order to investigate ancient casting process of Bengal and Bangladesh.The characterization of ancient archaeo-metal products come to a type of cast Cu-Sn-Zn-Pb type quaternary alloy produced by a slow freezing process.Though these alloys physically differ from the traditional cast alloy of binary Cu-Zn type brass,the physical characteristics are similar to the binary cast alloy character.This investigation throws light on the similarity of the production processes by which ancient artisans probably produced cast metal products. | Barnali Mandal Prasanta Kumar Datta | 2010 | China Foundry2010，7，2： | 0 |
| 15 | Visual Object Tracking Based on Modified LeNet-5 and RCCF显示文摘The field of object tracking has recently made significant progress.Particularly,the performance results in both deep learning and correlation filters,based trackers achieved effective tracking performance.Moreover,there are still some difficulties with object tracking for example illumination and deformation(DEF).The precision and accuracy of tracking algorithms suffer from the effects of such occurrences.For this situation,finding a solution is important.This research proposes a new tracking algorithm to handle this problem.The features are extracted by using Modified LeNet-5,and the precision and accuracy are improved by developing the Real-Time Cross-modality Correlation Filtering method(RCCF).In Modified LeNet-5,the visual tracking performance is improved by adjusting the number and size of the convolution kernels in the pooling and convolution layers.The high-level,middle-level,and handcraft features are extracted from the modified LeNet-5 network.The handcraft features are used to determine the specific location of the target because the handcraft features contain more spatial information regarding the visual object.The LeNet features are more suitable for a target appearance change in object tracking.Extensive experiments were conducted by the Object Tracking Benchmarking(OTB)databases like OTB50 and OTB100.The experimental results reveal that the proposed tracker outperforms other state-of-the-art trackers under different problems.The experimental simulation is carried out in python.The overall success rate and precision of the proposed algorithm are 93.8%and 92.5%.The average running frame rate reaches 42 frames per second,which can meet the real-time requirements. | Aparna Gullapelly Barnali Gupta Banik | 2023 | Computer Systems Science & Engineering2023，46，7： | 0 |
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