{"id":44,"date":"2025-07-24T23:52:28","date_gmt":"2025-07-25T04:52:28","guid":{"rendered":"https:\/\/research.ece.ncsu.edu\/impress\/?page_id=44"},"modified":"2025-07-26T22:42:20","modified_gmt":"2025-07-27T03:42:20","slug":"journals","status":"publish","type":"page","link":"https:\/\/research.ece.ncsu.edu\/impress\/publications\/journals\/","title":{"rendered":"Journal Papers"},"content":{"rendered":"\n
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2025<\/h3>\n\n\n\n

58. Automated Detection of Seafloor Gas Seeps in Multibeam Echosounder Data With an Attention-Guided Convolutional Neural Network<\/a><\/strong>
      S. M. Manjur, V. Senyurek, R. Kalski, S. Gupta, A. Skarke and A. C. Gurbuz<\/strong>
      IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing<\/em>, vol. 18, pp. 5633-5645, 2025,<\/p>\n\n\n\n

57. DREAM-CFA: joint learning of binary color filter array and demosaicing<\/a><\/strong>
      Cemre \u00d6mer Ayna, <\/em>Bahadir Kursat Gunturk, <\/em>Ali Cafer Gurbuz<\/strong>
      <\/em>Journal of Electronic Imaging, Vol. 34, Issue 2, 023063 (April 2025).<\/p>\n\n\n\n

56. Integrating UAS-Based GNSS-R, LiDAR, and Multispectral Data for Soil Moisture Estimation: Summary of Results From a Three-Year-Long Field Campaign,<\/a><\/strong>
     Farhad,M, Senyurek, V.; Rafi, M. A. S.; Baray, S. B.; McCraine, C.; Hathcock, L. A.; Adeli, A.; Yanbo, H.; Gurbuz, Ali C.<\/strong>; Kurum, M.
    IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing,<\/em> vol. 18, pp. 16896-16915, 2025<\/p>\n\n\n\n

2024<\/h3>\n\n\n\n

55. Beam Coefficient Prediction for Antenna Arrays Using Physics-Aware Convolutional Neural Networks<\/a><\/strong>
      G. D. King, M. Asaduzzaman Towfiq, A. C. Gurbuz<\/strong> and B. A. Cetiner
      <\/em> IEEE Access<\/em>, vol. 12, pp. 176908-176919, 2024, doi: 10.1109\/ACCESS.2024.3491828<\/p>\n\n\n\n

54. Best Linear Unbiased Estimators for Fusion of Multiple CYGNSS Soil Moisture Products<\/a><\/strong>
      M. M. Nabi, V. Senyurek, M. Kurum and A. C. Gurbuz<\/strong>
      IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing<\/em>, doi: 10.1109\/JSTARS.2024.3443100<\/p>\n\n\n\n

53. HRSpecNET: A Deep Learning-Based High-Resolution Radar Micro-Doppler Signature Reconstruction for Improved HAR<\/a><\/strong>
      S. Biswas, A. Manavi Alam and A. C. Gurbuz<\/strong>
      IEEE Transactions on Radar Systems<\/em>, vol. 2, pp. 484-497, 2024<\/p>\n\n\n\n

52. SDR-Based Dual Polarized L-Band Microwave Radiometer Operating From Small UAS Platforms,<\/a><\/strong>
      M. M. Farhad, A. M. Alam, S. Biswas, M. A. S. Rafi, A. C. Gurbuz<\/strong> and M. Kurum
      IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing<\/em>, vol. 17, pp. 9389-9402, 2024<\/p>\n\n\n\n

51. Emerging Trends in Autonomous Vehicle Perception: Multimodal Fusion for 3D Object Detection   <\/a><\/strong>
      Alaba, Simegnew Yihunie, Ali C. Gurbuz<\/strong>, and John E. Ball.
     World Electric Vehicle Journal<\/em> 15, no. 1: 20.  2024. <\/p>\n\n\n\n

50. Microwave Radiometer Calibration Using Deep Learning With Reduced Reference Information and 2-D Spectral Features<\/a><\/strong>
      A. M. Alam, M. Kurum, M. Ogut and A. C. Gurbuz<\/strong>,
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing<\/em>, vol. 17, pp. 748-765, 2024,<\/p>\n\n\n\n

2023<\/h3>\n\n\n\n

49. Learning-Based Optimization of Hyperspectral Band Selection for Classification<\/a>
       <\/strong>C. O. Ayna, R. Mdrafi, Qian Du, and A. C. Gurbuz
       <\/strong>Remote Sensing<\/em> 15, no. 18: 4460 2023. <\/p>\n\n\n\n

\u200b48.  CV-SincNet: Learning Complex Sinc Filters from Raw Radar Data for Computationally Efficient Human Motion Recognition<\/strong><\/a>
       S. Biswas, C. O. Ayna, S.Z. Gurbuz, A.C. Gurbuz<\/strong>, 
  IEEE Transactions on Radar Systems,  <\/em>vol. 1, pp. 493-504, 2023<\/p>\n\n\n\n

47.  A Ubiquitous GNSS-R Methodology to Estimate Surface Reflectivity Using Spinning Smartphone Onboard a  Small UAS<\/strong><\/a>
       M. M. Farhad, M. Kurum and A. C. Gurbuz<\/strong>
       IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 16, pp. 6568-6578, 2023.<\/em><\/p>\n\n\n\n

46.  Quasi-Global Assessment of Deep Learning-Based CYGNSS Soil Moisture Retrieval<\/strong><\/a>
       M. M. Nabi, V. Senyurek, F. Lei, M. Kurum and A. C. Gurbuz<\/strong>
       IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 16, pp. 5629-5644, 2023.<\/em><\/p>\n\n\n\n

45. \u200b  Boosting multi-target recognition performance with multi-input multi-output radar-based angular subspace   projection and multi-view deep neural network<\/a><\/strong>
        E. Kurtoglu, S. Biswas, A. C. Gurbuz<\/strong>, and S.Z. Gurbuz
        IET Radar Sonar Navigation 17(7), 1115\u20131128, 2023.<\/em><\/p>\n\n\n\n

\u200b44.  Closing the Wearable Gap: Foot\u2013ankle kinematic modeling via deep learning models based on a smart sock  wearable<\/a><\/strong>
        S. Davarzani, et.al. 
        Wearable Technologies, 4, E4, 2023. doi:10.1017\/wtc.2023.3<\/em><\/p>\n\n\n\n

2022<\/h3>\n\n\n\n

43.  Radio Frequency Interference Detection for SMAP Radiometer Using Convolutional Neural Networks<\/strong><\/a>
       A. M. Alam, M. Kurum and A. C. Gurbuz<\/strong>
       IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 10099-10112, 2022.<\/em>
\u200b
 42. Deep Learning-Based Soil Moisture Retrieval in CONUS Using CYGNSS Delay\u2013Doppler Maps<\/strong><\/a>
       M. M. Nabi, V. Senyurek, A. C. Gurbuz <\/strong>and M. Kurum
       IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 6867-6881, 2022.<\/em><\/p>\n\n\n\n

41.  Fusion of Reflected GPS Signals With Multispectral Imagery to Estimate Soil Moisture at Subfield Scale From Small UAS<\/a><\/strong>
      V. Senyurek, M. M. Farhad, A. C. Gurbuz<\/strong>, M. Kurum and A. Adeli
      IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 6843-6855, 2022.<\/em><\/p>\n\n\n\n

40. A Quasi-Global Machine Learning-based Soil Moisture at High Spatio-Temporal Scales using CYGNSS and SMAP Observati<\/strong><\/a>
      F . Lei, V. Senyurek, M. Kurum, A. Gurbuz,<\/strong> D. R. Boyd, R. Moorhead, W.T. Crow, and O. Eroglu
      Remote Sensing of Environment, Volume 276, July 2022, 113041. doi.org\/10.1016\/j.rse.2022.113041.<\/em><\/p>\n\n\n\n

39.  ASL Trigger Recognition in Mixed Activity\/Signing Sequences for RF Sensor-Based User Interfaces<\/strong><\/a>
     .  E. Kurtoglu, A. C. Gurbuz<\/strong>, E. A. Malaia, D. Griffin, C. Crawford and S. Z. Gurbuz
       IEEE Transactions on Human-Machine Systems, vol. 52, no. 4, pp. 699-712, Aug. 2022<\/em><\/p>\n\n\n\n

38.  Effect of Kinematics and Fluency in Adversarial Synthetic Data Generation for ASL Recognition With RF Sensors<\/a>
 <\/strong>      M. M. Rahman, E. A. Malaia, A. C. Gurbuz<\/strong>, D. J. Griffin, C. Crawford and S. Z. Gurbuz
       IEEE Transactions on Aerospace and Electronic Systems, vol. 58, no. 4, pp. 2732-2745, Aug. 2022<\/em><\/p>\n\n\n\n

37.   Multi-Frequency RF Sensor Fusion for Word-Level Fluent ASL Recognition<\/strong><\/a>
       S. Z. Gurbuz, M. M. Rahman; E. Kurtoglu, A. C. Gurbuz;<\/strong>; E. A. Malaia; D. J. Griffin; C. Crawford
       IEEE Sensors Journal, vol. 22, no. 12, pp. 11373-11381, 15 June15, 2022<\/em><\/p>\n\n\n\n

36.  Complexity in Sign Languages: Linguistic and Dimensional Analysis of Information Transfer in Dynamic Visual<\/strong> Comm<\/a>
       E.A. Malaia, J.D. Borneman, E. Kurtoglu, S.Z. Gurbuz, D. Griffin, C. Crawford and A. C. Gurbuz<\/strong>
       Linguistic Vanguard, 2022, DOI: 10.1515\/lingvan-2021-0005<\/em><\/p>\n\n\n\n

2021<\/h3>\n\n\n\n

35.  Assessment of Interpolation Errors of CYGNSS Soil Moisture Estimations<\/strong><\/a>
       V. Senyurek, A. C. Gurbuz<\/strong>, M. Kurum
       IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing, vol. 14, pp. 9815 – 9825, 2021.<\/em><\/p>\n\n\n\n

34.  Robust estimation of the number of coherent radar signal sources using deep learning<\/strong><\/a>
       J. Rogers, J. E. Ball, , A. C. Gurbuz;<\/strong>
       IET Radar, Sonar & Navigation, Vol 15, No 5, pp. 431-440, 2021<\/em><\/p>\n\n\n\n

33.   American Sign Language Recognition Using RF Sensing<\/strong><\/a>
        S. Z. Gurbuz, A. C. Gurbuz;<\/strong> E. A. Malaia; D. J. Griffin; C. Crawford; M. M. Rahman; E. Kurtoglu, R. Aksu, T. Macks, R. Mdrafi
        IEEE Sensors Journal, vol. 21, no. 3, pp. 3763-3775, 1 Feb.1, 2021<\/em><\/p>\n\n\n\n

32.   Integration of Smartphones into Small Unmanned Aircraft Systems to Sense Water in Soil by Using Reflected GPS Signals<\/strong><\/a>
        M. Kurum, M. M. Farhad and A. C. Gurbuz;<\/strong>,
        IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 1048-1059, 2021<\/em><\/p>\n\n\n\n

2020<\/h3>\n\n\n\n

31.  Attention-Based Domain Adaptation Using Residual Network for Hyperspectral Image Classification<\/strong><\/a>
       R. Mdrafi, Q. Du, A. C. Gurbuz<\/strong>, B. Tang, L. Ma and N. H. Younan,
       IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 13, pp. 6424-6433, 2020<\/em><\/p>\n\n\n\n

30.  Evaluations of a Machine Learning-based CYGNSS Soil Moisture Estimates against SMAP Observations<\/strong><\/a>
       Senyurek, V.; Lei, F.; Boyd, D.; Kurum, M.; Gurbuz, Ali C.<\/strong>; Moorhead, R.
       Remote Sensing, 2020, 12(21), 3480; https:\/\/doi.org\/10.3390\/rs12213480<\/em><\/p>\n\n\n\n

29.  SCoBi Multilayer: A Signals of Opportunity Reflectometry Model for Multilayer Dielectric Reflections<\/strong><\/a>
        D. R. Boyd, A. C. Gurbuz<\/strong> , M. Kurum, J. L. Garrison,B. R. Nold, J. R. Piepmeier, M. Vega, R. Bindlish
        Remote Sensing, 2020, 12(21), 3480; https:\/\/doi.org\/10.3390\/rs12213480<\/em><\/p>\n\n\n\n

28.  Cramer\u2013Rao Lower Bound for SoOp-R-Based Root-Zone Soil Moisture Remote Sensing<\/strong><\/a>
       D. R. Boyd, A. C. Gurbuz<\/strong> , M. Kurum, J. L. Garrison,B. R. Nold, J. R. Piepmeier, M. Vega, R. Bindlish
       IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 13, pp. 6101-6114, 2020<\/em><\/p>\n\n\n\n

27.   Cognitive Radar Target Detection and Tracking with Multifunctional Reconfigurable Antennas<\/strong><\/a>
A. C. Gurbuz<\/strong>, R. Mdrafi, B. A. Cetiner
       IEEE Aerospace and Electronic Systems Magazine, vol. 35, no. 6, pp. 64-76, 1 June 2020,<\/em><\/p>\n\n\n\n

26.    Machine Learning-Based CYGNSS Soil Moisture Estimates over ISMN sites in CONUS<\/strong><\/a>
       V. Senyurek, F. Lei, D. Boyd, M. Kurum, A. C. <\/strong>Gurbuz<\/strong>, R. Moorhead
       Remote Sensing, 2020, 12, 1168.<\/em>
\u200b
25.   Joint Learning of Measurement Matrix and Signal Reconstruction via Deep Learning<\/strong><\/a>
       R. Mdrafi, Ali C. Gurbuz<\/strong>
       IEEE Transactions on Computational Imaging, vol. 6, pp. 818-829, 2020,<\/em><\/p>\n\n\n\n

24.  Off-Grid Aware Channel and Covariance Estimation in mmWave Networks<\/strong><\/a>
       C. K. Anjinappa, Ali C. Gurbuz<\/strong>, Y. Yapici, I. Guvenc
       IEEE Transactions on Communications, vol. 68, no. 6, pp. 3908-3921, June 2020<\/em><\/p>\n\n\n\n

23.  CRLB based mode selection and enhanced DOA estimation for multifunctional reconfigurable arrays<\/a><\/strong>
Ali C. Gurbuz<\/strong>, Bedri A. Cetiner
       Physical Communication, Vol. 38, 100894, 2020.<\/em><\/p>\n\n\n\n

2007-2019<\/h3>\n\n\n\n

22. An Internet-Inspired Proportional Fair EV Charging Control Method<\/a><\/strong>
      E. Ucer, M. C. Kisacikoglu, M. Yuksel and A. C. Gurbuz
      IEEE Systems Journal, vol. 13, no. 4, pp. 4292-4302, Dec. 2019.<\/em><\/p>\n\n\n\n

21.  High Spatio-Temporal Resolution CYGNSS Soil Moisture Estimates Using Artificial Neural Networks<\/strong><\/a>
      O. Eroglu, M. Kurum , D. Boyd, and A. C. Gurbuz
      MDPI Remote Sensing, vol. 11, no. 19, pp.1-32, 2019.<\/em><\/p>\n\n\n\n

20. Autofocused Spotlight SAR Image Reconstruction of Off-Grid Sparse Scenes<\/a><\/strong>
      S. Camlica, A. C. Gurbuz and O. Arikan
      IEEE Transactions on Aerospace and Electronic Systems, vol. 53, no. 4, pp. 1880-1892, Aug. 2017.<\/em><\/p>\n\n\n\n

19.  Compressive Sensing based Robust Off-the-Grid Stretch Processing<\/strong><\/a>
      I. Ilhan, A. C. Gurbuz and O. Arikan
      IET Radar, Sonar Navigation, vol. 11, p. 1730-1735, 2017.<\/em><\/p>\n\n\n\n

18.  3D imaging for ground-penetrating radars via dictionary dimension reduction<\/strong><\/a>
      M. Duman; A.C. G\u00fcrb\u00fcz
      Tubitak Journal of Electrical Eng. and Computer Science, vol. 23, pp. 1242-1256, 2015.<\/em><\/p>\n\n\n\n

17.  Knowledge Exploitation for Human Micro-Doppler Classification<\/a><\/strong>
      C. Karabacak, S.Z. Gurbuz, A.C. Gurbuz, M.B. Guldogan, G. Hendeby, F. Gustafsson
      IEEE Geoscience and Remote Sensing Letters, vol.12, no.10, pp.2125-2129, Oct. 2015.<\/em><\/p>\n\n\n\n

16. SAR image reconstruction by expectation maximization based matching pursuit<\/a><\/strong>
      S. Ugur, O. Ar\u0131kan, A. C. G\u00fcrb\u00fcz
      Digital Signal Processing, vol. 37, pp. 75-84, February 2015.
\u200b<\/em>
15.  A Robust Compressive Sensing Based Technique For Reconstruction of Sparse Radar Scenes<\/a><\/strong>
      O. Teke, A. C. G\u00fcrb\u00fcz, O. Arikan
      Digital Signal Processing, vol. 27, pp. 23-32, 2014.<\/em><\/p>\n\n\n\n

14.  Perturbed Orthogonal Matching Pursuit<\/strong><\/a>
      O. Teke, A. C. G\u00fcrb\u00fcz, O. Arikan
      IEEE Transactions on Signal Processing, vol. 61, no. 24, pp. 6220-6231, December 2013.<\/em><\/p>\n\n\n\n

13.  Sparse Ground-Penetrating Radar Imaging Method for Off-the-Grid Target Problem<\/strong><\/a>
      Ali Cafer Gurbuz; Oguzhan Teke; Orhan Arikan
      J. Electron. Imaging. 22 (2), 021007 (January 31, 2013); doi: 10.1117\/1.JEI.22.2.021007<\/em><\/p>\n\n\n\n

12.  Analysis of Energy Efficiency of Compressive Sensing in Wireless Sensor Networks<\/strong><\/a>
      C Karakus, A. C. G\u00fcrb\u00fcz, B Tavli
      IEEE Sensors Journal, vol.13, no.5, pp.1999-2008, May 2013.<\/em><\/p>\n\n\n\n

11.   Bearing Estimation via Spatial Sparsity Using Compressive Sensing<\/strong><\/a>
       Ali Cafer G\u00fcrb\u00fcz, V. Cevher and J. H. McClellan
      IEEE Transactions on Aerospace and Electronic Systems, Vol 48, No 2, 2012l. 48, no. 2, pp. 1358-1369, April 2012.<\/em><\/p>\n\n\n\n

10. <\/strong>Compressive Sensing of Underground Structures using GPR<\/strong><\/a>
      Ali Cafer G\u00fcrb\u00fcz, J. H. McClellan, and W.R. Scott
      Digital Signal Processing, Volume 22, Issue 1, January 2012, Pages 66\u201373<\/em><\/p>\n\n\n\n

9. <\/strong>Ground Bounce Removal for Compressed Sensing Based GPRs<\/strong><\/a>
      Mehmet Ali \u00c7a\u011fr\u0131 Tuncer, Ali Cafer G\u00fcrb\u00fcz
      IEEE Geoscience and Remote Sensing Letters, vol. 9, No 1, pp. 23 \u2013 27, 2012<\/em><\/p>\n\n\n\n

8. <\/strong>Performance Analysis of Compressive-Sensing-Based Through-the-Wall Imaging with Effect of Unknown Parameters<\/strong><\/a>
      Muhammed Duman and Ali Cafer Gurbuz
      International Journal of Antennas and Propagation, vol. 2012, Article ID 405145, 11 pages, 2012. doi:10.1155\/2012\/405145<\/em><\/p>\n\n\n\n

7. <\/strong>Analysis of Orthogonal Matching Pursuit Based Subsurface Imaging for Compressive Ground Penetrating Radars<\/strong><\/a>
      Mehmet Ali \u00c7a\u011fr\u0131 Tuncer, Ali Cafer G\u00fcrb\u00fcz
      Tubitak Journal of Electrical Engineering and Computer Science, vol 20, no 6, pp. 979-989, 2012<\/em><\/p>\n\n\n\n

6.   Determination of Background Distribution for Ground-Penetrating Radar Data<\/strong><\/a>
      Ali Cafer G\u00fcrb\u00fcz
      IEEE Geoscience and Remote Sensing Letters, vol. 9, no, 4, pp. 544 \u2013 548, 2012<\/em><\/p>\n\n\n\n

5.   Line Detection with Adaptive Random Samples<\/strong><\/a>
      Ali Cafer G\u00fcrb\u00fcz
      Turk. J. Elec. Eng. & Comp. Sci. Volume 19, pp. 21-32, 2011 <\/em><\/p>\n\n\n\n

 4.  Detection of Linear and Planar Structures in 3D Subsurface Images by Iterative Dimension Reduction<\/strong><\/a>
      Ali Cafer G\u00fcrb\u00fcz, J. H. McClellan, and W.R. Scott
      Digital Signal Processing, vol. 20, no. 2, Pages: 391-400, March 2010. <\/em><\/p>\n\n\n\n

 3.   A Compressive Sensing Data Acquisition and Imaging Method for Stepped-Frequency GPRs<\/strong><\/a>
       Ali Cafer G\u00fcrb\u00fcz, J. H. McClellan, and W.R. Scott
      IEEE Tran. On Signal Processing, Vol. 57(7), Pages: 2640-2650 , July 2009<\/em><\/p>\n\n\n\n

 2.  Compressive Sensing for Subsurface Imaging using Ground Penetrating Radar<\/strong><\/a>
      Ali Cafer G\u00fcrb\u00fcz, J. H. McClellan, and W.R. Scott
      Signal Processing, Vol. 89(10), Pages: 1959-1972, October 2009<\/em>
       [2013 EURASIP Best Paper Award for the Signal Processing Journal]<\/strong><\/p>\n\n\n\n

 <\/strong>1.   Multistatic Ground-Penetrating Radar Experiments<\/a><\/strong>
      T. Counts, Ali. C. G\u00fcrb\u00fcz, K. Kim, W. R. Scott, Jr and J. H. McClellan
      IEEE Trans. on Geoscience and Remote Sensing, Vol. 45(8), Page(s): 2544 \u2013 2553, Aug. 2007.<\/em><\/p>\n\n\n\n

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2025 58. Automated Detection of Seafloor Gas Seeps in Multibeam Echosounder Data With an Attention-Guided Convolutional Neural Network      S. M. Manjur, V. Senyurek, R. Kalski,…<\/p>\n","protected":false},"author":152,"featured_media":0,"parent":10,"menu_order":1,"comment_status":"closed","ping_status":"closed","template":"page-fullwidth.php","meta":{"footnotes":""},"class_list":["post-44","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/research.ece.ncsu.edu\/impress\/wp-json\/wp\/v2\/pages\/44","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/research.ece.ncsu.edu\/impress\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/research.ece.ncsu.edu\/impress\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/research.ece.ncsu.edu\/impress\/wp-json\/wp\/v2\/users\/152"}],"replies":[{"embeddable":true,"href":"https:\/\/research.ece.ncsu.edu\/impress\/wp-json\/wp\/v2\/comments?post=44"}],"version-history":[{"count":8,"href":"https:\/\/research.ece.ncsu.edu\/impress\/wp-json\/wp\/v2\/pages\/44\/revisions"}],"predecessor-version":[{"id":84,"href":"https:\/\/research.ece.ncsu.edu\/impress\/wp-json\/wp\/v2\/pages\/44\/revisions\/84"}],"up":[{"embeddable":true,"href":"https:\/\/research.ece.ncsu.edu\/impress\/wp-json\/wp\/v2\/pages\/10"}],"wp:attachment":[{"href":"https:\/\/research.ece.ncsu.edu\/impress\/wp-json\/wp\/v2\/media?parent=44"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}