FY 2021 Publications

Refereed Publications

Ibrahim, M., Gauch, S., Salman, O., & Alqahtani, M. (2021). An automated method to enrich consumer health vocabularies using GloVe word embeddings and an auxiliary lexical resource. PeerJ. Computer science7, e668. https://doi.org/10.7717/peerj-cs.668

Wu, X., Kolar, A., Chung, J., Jin, D., Zhong, T., Kettimuthu, R., & Suchara, M. (2021). SeQUeNCe: a customizable discrete-event simulator of quantum networks. Quantum Science & Technology, 6. DOI: 10.1088/2058-9565/ac22f6 

Hannon, C., Yan, J., & Jin, D. (2021). Distributed Virtual Time-Based Synchronization for Simulation of Cyber-Physical Systems. ACM Transactions on Modeling and Computer Simulation (TOMACS), 31, 1 - 24. DOI: 10.1145/3446237. 

Getty, N., Brettin, T., Jin, D., Stevens, R., & Xia, F. (2021). Deep medical image analysis with representation learning and neuromorphic computing. Interface focus11(1), 20190122. https://doi.org/10.1098/rsfs.2019.0122

Vo, K., Yamazaki, K., Truong, S., Tran, M.-T., Sugimoto, A., & Le, N. (2021). ABN: Agent-aware boundary networks for temporal action proposal generation. IEEE Access, 9, 126431–126445. https://doi.org/10.1109/access.2021.3110973

Le, N., Rathour, V. S., Yamazaki, K., Luu, K., & Savvides, M. (2021). Deep Reinforcement Learning in computer vision: A comprehensive survey. Artificial Intelligence Review, 55(4), 2733–2819. https://doi.org/10.1007/s10462-021-10061-9

Zhou, S. K., Le, N., Luu, K., V Nguyen, H., & Ayache, N. (2021). Deep Reinforcement Learning in medical imaging: A literature review. Medical Image Analysis, 73, 102193. https://doi.org/10.1016/j.media.2021.102193

Vu, D.-Q., Le, N., & Wang, J.-C. (2021). Teaching yourself: A self-knowledge distillation approach to action recognition. IEEE Access, 9, 105711–105723. https://doi.org/10.1109/access.2021.3099856

Le, N., Bui, T., Vo-Ho, V.-K., Yamazaki, K., & Luu, K. (2021). Narrow band active contour attention model for medical segmentation. Diagnostics, 11(8), 1393. https://doi.org/10.3390/diagnostics11081393

Truong, T.-D., Duong, C. N., Tran, M.-T., Le, N., & Luu, K. (2021). Fast flow reconstruction via robust invertible n × N Convolution. Future Internet, 13(7), 179. https://doi.org/10.3390/fi13070179

Le, N., Sorensen, J., Bui, T., Choudhary, A., Luu, K., & Nguyen, H. (2021). Enhance portable radiograph for fast and high accurate COVID-19 monitoring. Diagnostics, 11(6), 1080. https://doi.org/10.3390/diagnostics11061080

Li, A., Du, W., & Li, Q. (2018). Privacy-preserving outsourcing of large-scale nonlinear programming to the cloud. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 569–587. https://doi.org/10.1007/978-3-030-01701-9_31

Jalata, I. K., Truong, T.-D., Allen, J. L., Seo, H.-S., & Luu, K. (2021). Movement analysis for neurological and musculoskeletal disorders using graph convolutional neural network. Future Internet, 13(8), 194. https://doi.org/10.3390/fi13080194

Li, X., Liu, J., Baron, J., Luu, K., & Patterson, E. (2021). Evaluating effects of focal length and viewing angle in a comparison of recent face landmark and alignment methods. EURASIP Journal on Image and Video Processing, 2021(1). https://doi.org/10.1186/s13640-021-00549-3

Slavakis, K., Shetty, G., Cannelli, L., Scutari, G., Nakarmi, U., & Ying, L. (2021). Kernel regression imputation in manifolds via bi-linear modeling: The dynamic-MRI case. https://doi.org/10.36227/techrxiv.14813673.v1

Alshehri, M., Panda, B., Almakdi, S., Alazeb, A., Halawani, H., Al Mudawi, N., & Khan, R. U. (2021). A novel blockchain-based encryption model to protect fog nodes from behaviors of malicious nodes. Electronics, 10(24), 3135. https://doi.org/10.3390/electronics10243135

Almakdi, S., Panda, B., Alshehri, M. S., & Alazeb, A. (2021). An efficient secure system for fetching data from the outsourced encrypted databases. IEEE Access, 9, 78474–78494. https://doi.org/10.1109/access.2021.3082139

Alazeb, A., Panda, B., Almakdi, S., & Alshehri, M. (2021). Data Integrity Preservation Schemes in smart healthcare systems that use fog computing distribution. Electronics, 10(11), 1314. https://doi.org/10.3390/electronics10111314

Hader, D., & Patitz, M. J. (2021). Geometric tiles and powers and limitations of geometric hindrance in self-assembly. Natural Computing, 20(2), 243–258. https://doi.org/10.1007/s11047-021-09846-2

Cannon, S., Demaine, E. D., Demaine, M. L., Eisenstat, S., Furcy, D., Patitz, M. J., Schweller, R., Summers, S. M., & Winslow, A. (2021). On the effects of hierarchical self-assembly for reducing program-size complexity. Theoretical Computer Science, 894, 50–78. https://doi.org/10.1016/j.tcs.2021.09.011

Al Razi, I., Le, Q., Evans, T. M., Mukherjee, S., Mantooth, H. A., & Peng, Y. (2021). PowerSynth design automation flow for hierarchical and heterogeneous 2.5-D multichip power modules. IEEE Transactions on Power Electronics, 36(8), 8919–8933. https://doi.org/10.1109/tpel.2021.3049776

Kabir, M. D. A., & Peng, Y. (2021). Holistic chiplet–package co-optimization for agile custom 2.5-D design. IEEE Transactions on Components, Packaging and Manufacturing Technology, 11(5), 715–726. https://doi.org/10.1109/tcpmt.2021.3069724

Alsaify, B. A., Thompson, D. R., Alma'aitah, A., & Di, J. (2021). Using dummy data for RFID tag and reader authentication. Digital Communications and Networks. https://doi.org/10.1016/j.dcan.2021.09.008

Yuan, S., & Wu, X. (2021). Deep Learning for Insider Threat Detection: Review, challenges and opportunities. Computers & Security, 104, 102221. https://doi.org/10.1016/j.cose.2021.102221

Du, W., & Wu, X. (2021). Enhancing personalized modeling via weighted and adversarial learning. International Journal of Data Science and Analytics, 12(1), 1–14. https://doi.org/10.1007/s41060-021-00263-3

Hu, D., Hu, C., Fan, Y., & Wu, X. (2021). Ogbac—a group based access control framework for information sharing in online social networks. IEEE Transactions on Dependable and Secure Computing, 18(1), 100–116. https://doi.org/10.1109/tdsc.2018.2875697

Feng, Y., Li, J., Jiao, L., & Wu, X. (2020). Towards learning-based, content-agnostic detection of Social Bot Traffic. IEEE Transactions on Dependable and Secure Computing, 1–1. https://doi.org/10.1109/tdsc.2020.3047399

Schwob, M. R., Zhan, J., & Dempsey, A. (2021). Modeling cell communication with time-dependent signaling hypergraphs. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 18(3), 1151–1163. https://doi.org/10.1109/tcbb.2019.2937033

Swan, M., & Zhan, J. (2021). Clustering hypergraphs via the mapequation. IEEE Access, 9, 72377–72386. https://doi.org/10.1109/access.2021.3075621

Bakare, A. B., Meshrkey, F., Lowe, B., Molder, C., Rao, R. R., Zhan, J., & Iyer, S. (2021). Mitocellphe reveals mitochondrial morphologies in single fibroblasts and clustered Stem Cells. American Journal of Physiology-Cell Physiology, 321(4). https://doi.org/10.1152/ajpcell.00231.2021

Chen, X., Chen, D. G., Zhao, Z., Zhan, J., Ji, C., & Chen, J. (2021). Artificial image objects for classification of schizophrenia with GWAS-selected snvs and Convolutional Neural Network. Patterns, 2(8), 100303. https://doi.org/10.1016/j.patter.2021.100303

Molder, C., Lowe, B., & Zhan, J. (2021). Learning medical materials from radiography images. Frontiers in Artificial Intelligence, 4. https://doi.org/10.3389/frai.2021.638299