Raja Das - researchr alias

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Viewing Publication 1 - 39 from 39

2026

A hybrid framework integrating Fuzzy K-means segmentation and CNN feature extraction with SVM kernel for lung cancer classificationPotharla Ramadevi, Raja Das. evs, 17(2):34, June 2026. [doi]

2025

2024

Design of a unified physics-informed neural network using interior point algorithm to study the bioconvection nanofluid flow via stretching surfacePriyanka Chandra, Raja Das. eaai, 133:108647, 2024. [doi]

Brief Announcement: Perpetual Exploration of Triangular Grid by Myopic Oblivious Robots Without ChiralityRaja Das, Pritam Goswami, Buddhadeb Sau. sss 2025: 156-160 [doi]

Perpetual Exploration of a Ring in Presence of Byzantine Black HolePritam Goswami, Adri Bhattacharya, Raja Das, Partha Sarathi Mandal 0001. opodis 2025: [doi]

A new COVID-19 classification approach based on Bayesian optimization SVM kernel using chest X-ray datasetsM. Lakshmi, Raja Das, Balakrishnama Manohar. evs, 15(4):1521-1540, August 2024. [doi]

A hybridized LSTM-ANN-RSA based deep learning models for prediction of COVID-19 cases in Eastern European countriesBalakrishnama Manohar, Raja Das, M. Lakshmi. eswa, 256:124977, 2024. [doi]

An Extensive Analysis of Machine Learning Techniques With Hyper-Parameter Tuning by Bayesian Optimized SVM Kernel for the Detection of Human Lung DiseasePotharla Ramadevi, Raja Das. access, 12:97752-97770, 2024. [doi]

A Novel QoS Prediction Model for Web Services Based on an Adaptive Neuro-Fuzzy Inference System Using COOT OptimizationJithendra Thandra, Mohammad Zubair Khan, Shaik Sharief Basha, Raja Das, A. Divya, Chiranji Lal Chowdhary, Abdulrahman Alahmadi, Ahmed H. Alahmadi. access, 12:6993-7008, 2024. [doi]

2023

Artificial neural network-based pore size prediction of alginate gel scaffold for targeted drug deliveryRaja Das, Jaykumar Bhasarkar, Amol Rastogi, Raghav Saxena, Dharmendra Kumar Bal. nca, 35(6):4683-4699, February 2023. [doi]

Artificial neural networks for prediction of COVID-19 in India by using backpropagationBalakrishnama Manohar, Raja Das. es, 40(5), June 2023. [doi]

2021

An integrated approach for prediction of radial overcut in electro discharge machining using fuzzy graph recurrent neural networkAmrut Ranjan Jena, Raja Das, D. P. Acharjya. ijes, 14(4):345-354, 2021. [doi]

2011

Multicore SDK: A Practical and Efficient Deadlock Detector for Real-World ApplicationsZhi Da Luo, Raja Das, Yao Qi. icst 2011: 309-318 [doi]

2010

Effective Static Analysis to Find Concurrency Bugs in JavaZhi Da Luo, Linda Hillis, Raja Das, Yao Qi. SCAM 2010: 135-144 [doi]

Unit testing for concurrent business codeYao Qi, Yarden Nir-Buchbinder, Eitan Farchi, Raja Das, Zhi Da Luo, Zhi Gan. ISSTA 2010: 37-47 [doi]

2009

MulticoreSDK: a practical and efficient data race detector for real-world applicationsYao Qi, Raja Das, Zhi Da Luo, Martin Trotter. ISSTA 2009: [doi]

2003

ADoc-Oriented ProgrammingSanthosh Kumaran, Prabir Nandi, Terry Heath, Kumar Bhaskaran, Raja Das. saint 2003: 334-343 [doi]

2002

Web Services Gateway: The Building Block for Business Connections and Dynamic e-BusinessZongwei Luo, Raja Das, Kumar Bhaskaran, Santhosh Kumaran, John Y. Sayah. ic 2002: 779-785

2001

An e-Business Integration & Collaboration Platform for B2B e-CommerceKumar Bhaskaran, Jen-Yao Chung, Raja Das, Terry Heath, Santhosh Kumaran, Prabir Nandi. wecwis 2001: 120-122 [doi]

Runtime and Compiler Support for Irregular ComputationsRaja Das, Yuan-Shin Hwang, Joel H. Saltz, Alan Sussman. cosps 2001: 751-778 [doi]

1998

A-Teams: An Agent Architecture for Optimization and Decision SupportJohn Rachlin, Richard Goodwin, Sesh Murthy, Rama Akkiraju, Frederick Y. Wu, Santhosh Kumaran, Raja Das. atal 1999: 261-276

1997

Programming Irregular Applications: Runtime Support, Compilation and ToolsJoel H. Saltz, Gagan Agrawal, Chialin Chang, Raja Das, Guy Edjlali, Paul Havlak, Yuan-Shin Hwang, Bongki Moon, Ravi Ponnusamy, Shamik D. Sharma, Alan Sussman, Mustafa Uysal. ac, 45:105-153, 1997.

1995

Interprocedural Partial Redundancy Elimination and its Application to Distributed Memory CompilationGagan Agrawal, Joel H. Saltz, Raja Das. PLDI 1995: 258-269

Index Array Flattening Through Program TransformationRaja Das, Paul Havlak, Joel H. Saltz, Ken Kennedy. sc 1995: 70 [doi]

Runtime and Language Support for Compiling Adaptive Irregular Programs on Distributed-memory MachinesYuan-Shin Hwang, Bongki Moon, Shamik D. Sharma, Ravi Ponnusamy, Raja Das, Joel H. Saltz. SPE, 25(6):597-621, 1995.

Implementation of a parallel unstructured Euler solver on shared- and distributed-memory architecturesDimitri J. Mavriplis, Raja Das, Joel H. Saltz, R. E. Vermeland. tjs, 8(4):329-344, 1995. [doi]

Supporting irregular distributions using data-parallel languagesRavi Ponnusamy, Yuan-Shin Hwang, Raja Das, Joel H. Saltz, Alok N. Choudhary, Geoffrey Fox. ieeecc, 3(1):12-24, 1995. [doi]

Distributed Memory Compiler Design for Sparse ProblemsJanet Wu, Raja Das, Joel H. Saltz, Harry Berryman, Seema Hiranandani. TC, 44(6):737-754, 1995.

1994

Communication Optimizations for Irregular Scientific Computations on Distributed Memory ArchitecturesRaja Das, Mustafa Uysal, Joel H. Saltz, Yuan-Shin Hwang. jpdc, 22(3):462-478, 1994.

Run-time and compile-time support for adaptive irregular problemsShamik D. Sharma, Ravi Ponnusamy, Bongki Moon, Yuan-Shin Hwang, Raja Das, Joel H. Saltz. sc 1994: 97-106 [doi]

1993

Parallelizing Molecular Dynamics Codes using the Parti Software PrimitivesRaja Das, Joel H. Saltz. ppsc 1993: 187-192

Slicing Analysis and Indirect Accesses to Distributed ArraysRaja Das, Joel H. Saltz, Reinhard von Hanxleden. lcpc 1994: 152-168

1992

1991

Unstructured Mesh Problems, PARTI Primitives, and the ARF CompilerRaja Das, Joel H. Saltz, Dimitri J. Mavriplis, Janet Wu, Harry Berryman. ppsc 1992: 570-572

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