Publications

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2016

  • T.C. Havens, D.T. Anderson, K. Stone, J. Becker, and A.J. Pinar (2016). Computational Intelligence in Forward Looking Explosive Hazard Detection. In R. Abielmona et al. (Eds.), Recent Advances in Computational Intelligence in Defense and Security (pp. 13-44). Berlin: Springer.
  • H. Deilamsalehy, T.C. Havens, P. Lautala, E. Medici, and J. Davis. An automatic train car wheel flat spot detection method using thermal camera imagery. Accepted, J. Rail and Rapid Transit. doi: 10.1177/0954409716638703.
  • D. Kumar, J.C. Bezdek, M. Palaniswami, S. Rajasegarar, C. Leckie, and T.C. Havens. A hybrid approach to clustering in big data. Accepted, IEEE Trans. Systems, Man, and Cybernetics. doi:10.1109/TCYB.2015.2477416.
  • H. Sweidan and T.C. Havens. Coverage optimization in a terrain-aware wireless sensor network. Accepted, IEEE Conf. Evolutionary Computation.
  • J. Manela and T.C. Havens. Histogram particle swarm optimization (HistPSO): evolving non-parametric acceleration distributions. Accepted, IEEE Conf. Evolutionary Computation.
  • L. Tomlin, D.T. Anderson, C. Wagner, T.C. Havens, and J.M. Keller. Fuzzy integral for rule aggregation in fuzzy inference systems. Accepted, Int. Conf. Info. Proc. and Management of Uncertainty.
  • H. Deilamsalehy, T.C. Havens, and P. Lautala (2016). Detection of sliding wheels and hot bearings using wayside thermal cameras. Accepted, Proc. Joint Rail Conference.
  • A. Pinar, T.C. Havens, J. Rice, M. Masarik, J. Burns, and B. Thelen. A comparison of robust principal component analysis techniques for buried object detection in downward looking GPR and EMI sensor data. Accepted, SPIE DSS.
  • J. Rice, A. Pinar, T.C. Havens, and T.J. Schulz. Spatiotemporal features for buried hazard detection. Accepted, SPIE DSS.
  • A. Webb, T.C. Havens, and T.J. Schulz. Spectral diversity for ground clutter mitigation in forward-looking GPR. Accepted, SPIE DSS.
  • M.P. Masarik, J. Burns, B.T. Thelen, J. Kelly, and T.C. Havens. Enhanced buried UXO detection via GPR/EMI data fusion. Accepted, SPIE DSS.
  • S.R. Price, B. Murray, L. Hu, D.T. Anderson, T.C. Havens, R.H. Luke, and J.M. Keller. Multiple kernel based feature and decision level fusion of iECO features for forward looking EHD in infrared imagery. Accepted, SPIE DSS.
  • J.L. Dowdy, D.T. Anderson, R.H. Luke, J.E. Ball, T.C. Havens, and J.M. Keller. Fusion of spatial frequency domain features using GAMKLp for side-attack explosive ballistic detection in synthetic aperture acoustics. Accepted, SPIE DSS.

2015

  • C. Demars, M. Roggemann, and T.C. Havens (2015), Multi-spectral detection and tracking of multiple moving targets in cluttered urban environments. Optical Engineering, 54(12), 123106.
  • T.C. Havens, D.T. Anderson, and C. Wagner (2015). Data-informed fuzzy measures for fuzzy integration of intervals and fuzzy numbers. IEEE Trans. Fuzzy Systems, 23(5), 1861-1875.
  • J. Su and T.C. Havens. Quadratic program-based modularity maximization for fuzzy community detection in social networks (2015). IEEE Trans. Fuzzy Systems, 23(5), 1356-1371.
  • A.J. Pinar, B. Wijnen, G.C. Anzalone, T.C. Havens, P.G. Sanders, and J.M. Pearce (2015). Low-cost open-source voltage and current monitor for gas metal arc weld 3-D printing. J. Sensors, 2015, paper ID 876714, 8 pages.
  • C. Wagner, S. Miller, J.M. Garibaldi, D.T. Anderson, and T.C. Havens (2015). From interval-valued data to general type-2 fuzzy sets. IEEE Trans. Fuzzy Systems, 23(2), 248-269.
  • M.A. Islam, D.T. Anderson, and T.C. Havens (2015). Multi-criteria based learning of the Choquet integral using goal programming. Proc. NAFIPS, 1-6.
  • T. Adeyeba, D.T. Anderson, and T.C. Havens (2015). Insights and characterizations of l1-norm based sparsity learning of a lexicographically encoded capacity vector for the Choquet integral. Proc. IEEE Int. Conf. Fuzzy Systems, 1-7.
  • A. Pinar, T.C. Havens, D.T. Anderson, and L. Hu (2015). Feature and decision level fusion using multiple kernel learning and fuzzy integrals. Proc. IEEE Int. Conf. Fuzzy Systems, 1-7.
  • H. Deilamsalehy, T.C. Havens, and P. Lautala (2015). Automatic method for detecting and categorizing train car wheel and bearing defects. Proc. Joint Rail Conference, no. JRC2015-5741.
  • S.R. Price, D.T. Anderson, and T.C. Havens (2015). Fusion of iECO image descriptors for buried explosive hazard detection in forward-looking infrared imagery. Proc. SPIE, 9454, 945405.
  • J. Becker, T.C. Havens, A. Pinar, and T.J. Schulz (2015). Deep belief networks for false alarm rejection in forward-looking ground-penetrating radar. Proc. SPIE, 9454, 94540W. d
  • M.P. Masarik, J. Burns, B.T. Thelen, and T.C. Havens (2015). GPR anomaly detection with robust principal component analysis. Proc. SPIE, 9454, 945414.
  • A. Webb, T.C. Havens, and T.J. Schulz (2015). An apodization approach for processing forward-looking GPR for explosive hazard detection. Proc. SPIE, 9454, 94540X.
  • A. Pinar, M. Masarik, J. Kelly, T.C. Havens, J. Burns, B. Thelen, and J. Becker (2015). Approach to explosive hazard detection using sensor fusion and multiple kernel learning with downward-looking GPR and EMI sensor data. Proc. SPIE, 9454, 94540B.

2014

  • D.T. Anderson, T.C. Havens, C. Wagner, J.M. Keller, M.F. Anderson, and D.J. Wescott. Extension of the fuzzy integral for general fuzzy set-valued information (2014). IEEE Trans. Fuzzy Systems, 22(6), 1625-1639.
  • M. Moshtaghi, J.C. Bezdek, T.C. Havens, C. Leckie, S. Karunasekera, S. Rajasegarar, and M. Palaniswami (2014). Streaming analysis in wireless sensor networks. Wireless Communications and Mobile Computing, 14(9), 905-921.
  • S. Rajasegarar, T.C. Havens, S. Karunasekera, C. Leckie, J.C. Bezdek, M. Jamriska, A. Gunatilaka, A. Skvortsov, and M. Palaniswami (2014). High resolution monitoring of atmospheric pollutants using a system of low-cost sensors. IEEE Trans. Geoscience and Remote Sensing 52(7), 3823-3832.
  • L. Hu, D.T. Anderson, T.C. Havens, and J.M. Keller (2014). Efficient and scalable nonlinear multiple kernel aggregation using the Choquet integral. CCIS, vol. 442: Proc. Int. Conf. Info. Processing and Management of Uncertainty in Knowledge-Based Systems, 206-215.
  • D.T. Anderson, S. Price, and T.C. Havens (2014). Regularization-based learning of the Choquet integral. Proc. IEEE Int. Conf. Fuzzy Systems, 2519-2526.
  • P. Bhatkhande and T.C. Havens (2014). Real time fuzzy controller for quadrotor stability control. Proc. IEEE Int. Conf. Fuzzy Systems, 913-919.
  • V. Navale and T.C. Havens (2014). Fuzzy logic controller for energy management of power split hybrid electric vehicle transmission. Proc. IEEE Int. Conf. Fuzzy Systems, 940-947.
  • J. Su and T.C. Havens (2014). Fuzzy community detection in social networks using a genetic algorithm. Proc. IEEE Int. Conf. Fuzzy Systems, 2039-2046.
  • S. Price, D.T. Anderson, C. Wagner, T.C. Havens, and J.M. Keller (2014). Indices for introspection of the Choquet integral. Studies in Fuzziness and Soft Computing, vol. 312: Proc. World Conf. Soft Computing, 261-271.
  • J. Su and T.C. Havens (2014). A generalized fuzzy t-norm formulation of fuzzy modularity for community detection in social networks. Studies in Fuzziness and Soft Computing, vol. 312: Proc. World Conf. Soft Computing, 65-76.
  • T.C. Havens, J. Becker, A. Pinar, and T.J. Schulz (2014). Multi-band sensor-fused explosive hazard detection in forward-looking ground-penetrating radar. Proc. SPIE, 9072, 90720T.

2013

  • T.C. Havens, J.C. Bezdek, C. Leckie, K. Romamohanarao, and M. Palaniswami (2013). A soft modularity function for detecting fuzzy communities in social networks. IEEE Trans. Fuzzy Systems, 21(6), 1170-1175.
  • M. Popescu, T.C. Havens, J.C. Bezdek, and J.M. Keller (2013). A cluster validity framework based on induced partition dissimilarity. IEEE Trans. Cybernetics 43(1), 308-320.
  • Z. Zhang and T.C. Havens (2013). Scalable approximation of kernel fuzzy c-means. Proc. IEEE Int. Conf. Big Data, 161-168.
  • D. Kumar, M. Palaniswami, S. Rajasegarar, C. Leckie, J.C. Bezdek, and T.C. Havens (2013). clusiVAT: a mixed visual/numerical clustering algorithm for big data. Proc. IEEE Int. Conf. Big Data, 112-117.
  • C. Wagner, D.T. Anderson, and T.C. Havens (2013). Generalization of the fuzzy integral for discontinuous interval- and non-convex interval fuzzy set-valued inputs. Proc. IEEE Int. Conf. Fuzzy Systems, 1-8.
  • L. Hu, D.T. Anderson, and T.C. Havens (2013). Multiple kernel aggregation using fuzzy integrals. Proc. IEEE Int. Conf. Fuzzy Systems, 1-7.
  • T.C. Havens, D.T. Anderson, C. Wagner, H. Deilamsalehy, and D. Wonnacott (2013). Fuzzy integrals of intervals using a measure of generalized accord. Proc. IEEE Int. Conf. Fuzzy Systems, 1-8.
  • T.C. Havens, J.C. Bezdek, C. Leckie, and M. Palaniswami (2013). Extension of iVAT to asymmetric matrices. Proc. IEEE Int. Conf. Fuzzy Systems, 1-6.
  • T.C. Havens, J.C. Bezdek, C. Leckie, J. Chan, W. Liu, J. Bailey, K. Romamohanarao, and M. Palaniswami (2013). Clustering and visualization of fuzzy communities in social networks. Proc. IEEE Int. Conf. Fuzzy Systems, 1-7.
  • T.C. Havens, J.C. Bezdek, and M. Palaniswami (2013). Scalable single-linkage hierarchical clustering for big data. Proc. IEEE ISSNIP, 396-401.

2012

  • T.C. Havens, J.C. Bezdek, C. Leckie, L.O. Hall, and M. Palaniswami (2012). Fuzzy c-means algorithms for very large data. IEEE Trans. Fuzzy Systems, 20(6), 1130-1146.
  • T.C. Havens and J.C. Bezdek (2012). A new formulation of the coVAT algorithm for visual assessment of clustering tendency in rectangular data. Int. J. Intelligent Systems 27(6), 590-612.
  • T.C. Havens and J.C. Bezdek (2012). An efficient formulation of the improved visual assessment of tendency (iVAT) algorithm. IEEE Trans. Knowledge and Data Engineering 24(5), 813-822.
  • T.C. Havens (2012). Approximation of kernel k-means for streaming data. Int. Conf. Pattern Recognition, 509-512.
  • T.C. Havens, J.C. Bezdek, and M. Palaniswami (2012). Cluster validity for kernel fuzzy clustering. Proc. IEEE Int. Conf. Fuzzy Systems, 1-8. Best Paper Finalist
  • D.T. Anderson, T.C. Havens, C. Wagner, J.M. Keller, M. Anderson, and D. Wescott (2012). Sugeno fuzzy integral generalizations for sub-normal fuzzy set-valued inputs. Proc. IEEE Int. Conf. Fuzzy Systems, 1-8. Best Paper Award
  • S. Rajasegarar, J.C. Bezdek, M. Moshtaghi, C. Leckie, T.C. Havens, and M. Palaniswami (2012). Measures for clustering and anomaly detection in sets of higher dimensional ellipsoids. IEEE Int. Joint Conf. Neural Networks, 1-8.
  • T.C. Havens, J.M. Keller, K. Stone, K.C. Ho, T.T. Ton, D.C. Wong, and M. Soumekh (2012). Multiple kernel learning for explosive hazards detection in forward-looking ground-penetrating radar. Proc. SPIE, 8357, 83571D.
  • J. Farrell, T.C. Havens, K.C. Ho, J.M. Keller, T.T. Ton, D.C. Wong, and M. Soumekh (2012). Evaluation and improvement of spectral features for the detection of buried explosive hazards using forward-looking ground-penetrating radar. Proc. SPIE, 8357, 8357C.