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Dissemination

Selected from 2014
*mentored Ph.D students/RAs/Interns;**co-mentored; +co-first author/corresponding

2020
  1. S Bruendl*, H. Fang+, Making the Switch to 5G and 60GHz in mHealth applications using USRP hardware, IEEE Internet Computing. doi: 10.1109/MIC.2019.2962797
  2. CS Mahabal**, H Wang, H Fang, A New Spectrum Selection Scheme for mmWAVE Based Wireless Body Area Networks (WBANs). IEEE ICC 2020. Accepted
  3. J Rumbut*, H Fang+, S Carreiro, D Smelson, B Chapman, E Boyer, H Wang. Harmonizing wearable biosensor data streams to test polydrug detection. In 2020 International Conference on Computing, Networking and Communications (ICNC): Cloud Computing and Big Data. Accepted.
  4. MD N Anjum, H Wang, H Fang. Coverage Analysis of Random UAV Networks Using Percolation Theory. In 2020 International Conference on Computing, Networking and Communications (ICNC): Network Algorithms and Performance Evaluation. Accepted.
2019
  1. H Fang. Data analytics for longitudinal biomedical data. Encyclopedia of Wireless Networks. Accepted
  2. H Wang, M Daneshmand, H Fang. Artificial Intelligence (AI) Driven Wireless Body Area Networks: Challenges and Directions. IEEE ICII2019.Accepted
  3. S.Bruendl*, H Fang+. 60 GHz in WBAN and mm-Wave Technologies. Encyclopedia of Wireless Networks. Accepted.
  4. Rumbut, J*.Fang, H+. Carreiro S, Singh D., Wang, H, Boyer E. Detecting Kratom Intoxication in Wearable Biosensor Data. Accepted, IEEE/ACM CHASE 2019
  5. VS Gurugubelli*, Fang H+, Wang, H. (2019) Neuro-Fuzzy classifier for behavioral intervention data 2019 International Conference on Computing, Networking and Communications (ICNC): Cloud Computing and Big Data. IEEE ICNC2019 DOI: 10.1109/ICCNC.2019.8685574
  6. Z. Li** H. Fang, H. Wang, M. Daneshmand, (2019)"A Data-Centric Cognitive Gateway with Distributed MIMO for Future Smart Homes,"IEEE Wireless Communication Magazine, 26(3), 40-46 10.1109/MWC.2019.1800358
  7. MD N Anjum, H Wang, HFang, "Prospects of 60 GHz mmWave WBAN: A PHY-MAC Joint Approach," IEEE Transactions on Vehicular Technology. Accepted.
2018
  1. Fang H, Invited talk, MIFuzzy for incomplete longitudinal data pattern recognition, Department of Biomedical Data Science, Geisel School of Medicine, Dartmouth College, New Hampshire.
  2. VS Gurugubelli*, Li Z**, H Wang, H Fang+.(2018) eFCM: An Enhanced Fuzzy C-Means Algorithm for Longitudinal Intervention Data', IEEE ICNC2018. DOI: 10.1109/ICCNC.2018.8390419. PMCID: PMC6428443 NIHMSID: NIHMS973824; PMID: 30906794
  3. VS Gurugubelli*, Li, Z**, Wang, H, Fang H+, (2018) A Computational Efficient Fuzzy Clustering Algorithm for Big Incomplete Longitudinal Trial Data 2018 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE). IEEE/ACM CHASE 2018.
  4. T. Jiang, H. Fang,  H. Wang,(2018) "Blockchain-based Internet of Vehicles: Distributed Network Architecture and Performance Analysis," in IEEE Internet of Things Journal, 2018. 10.1109/JIOT.2018.2874398
  5. M.S. Mahmud**, H. Wang, H. Fang, "SensoRing: An Integrated Wearable System for Continuous Measurement of Physiological Biomarkers” Accepted, IEEE ICC2018
2017
  1. SS Kim, H Fang+, K Bernstein, Z Zhang, J DiFranza, D ZieDonis, J Allison, Acculturation, Depression, and Smoking Cessation: a trajectory pattern recognition approach. Tob Induc Dis, 2017, doi:  10.1186/s12971-017-0135-x, PMCID: PMC5525352
  2. Zhou, L**, Wang H, H.Fang+, " Group-Based Cooperation on Symmetric Key Generation for Wireless Body Area Networks," in IEEE Internet of Things Journal, 2017, 4(6): 1955-1963 doi: 10.1109/JIOT.2017.2761700. https://ieeexplore.ieee.org/document/8063866/
  3. Haijia Wang*, Zitong Su*, H. Fang+. Simulating Normal and Abnormal ECG Signals in Children Age 0-16. 2017 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE), Accepted. DOI: 10.1109/CHASE.2017.103
  4. M. S. Mahmud, H. Wang, A. M. Esfar-E-Alam, H. Fang, "A Wireless Health Monitoring System Using Mobile Phone Accessories," IEEE Internet of Things Journal, 2017, accepted, doi: 10.1109/JIOT.2016.2645125
  5. Fang, H. MIFuzzy Clustering for Incomplete Longitudinal Data in Smart Health. Smart Health (Elsevier Journal). 1–2, pp. 50-65. DOI: 10.1016/j.smhl.2017.04.002. NIHMSID: 906898
  6. Fang, H., Z. Zhang*. An Enhanced Visualization Method to Aid Behavioral Trajectory Patten Recognition Infrastructure for Big Longitudinal Data. IEEE Transaction on Big Data. 2017, Accepted. DOI: 10.1109/TBDATA.2017.2653815. NIHMSID: 907513 
  7. Wang H, Mahmud MS, Fang H, Wang C. Wireless Health. Springer. 2017. ISBN 978-3-319-47946-0.
  8. J. Wang* , Fang H+, B. Li and H. Wang, "Evaluate clustering performance and computational efficiency for PSO based fuzzy clustering methods in processing big imbalanced data," 2017 IEEE International Conference on Communications (ICC), Paris, 2017, pp. 1-6.doi: 10.1109/ICC.2017.7996802
  9. Wang CJ,* Fang H+ , Carreiro S, Wang H., Boyer E. A New Mining Method to Detect Real Time Substance Use Events from Wearable Biosensor Data Stream. Proceedings of International Conference on Computing, Networking and Communications: Social Computing and Semantic Data Mining, pp. 465-470. ICNC2017. NIHMSID: 907527
2016
  1. Fang, H, Zhang Z,*  Ash, A, Houston, T, Allison, J, Validating Engagement Trajectory Patterns in Mining Big Longitudinal Web Trial Data, 9th Annual Conference on the Science of Dissemination and Implementation. Washington, DC. 2016.
  2. Wang CJ,* Fang H+ , Carreiro S, Wang H., Boyer E. Detecting Real-time Substane Use from Wearable Biosensor Data Stream. Section on Statistical Learning and Data Mining. Joint Statistical Meetings, American Statistical Association. Chicago, IL, 2016.
  3. Zhang Z,* Fang H+ , Wang H. A New MI-based Visualization Aided Validation Index for Mining Big Longitudinal Web Trial Data. IEEE Access.4:2272-2280. DOI: 10.1109/ACCESS.2016.2569074. NIHMSID: 790905. PMID: 27482473. PMCID: PMC4963037.
  4. Zhang Z,* Fang H+ . Multiple- vs Non- or Single-Imputation based Fuzzy Clustering for Incomplete Longitudinal Behaviroal Intervention Data. Proceedings of 2016 IEEE first conference on Connected Health: Applications, Systems and Engineering Technologies (NIH & NSF jointly sponsored).  DOI: 10.1109/CHASE.2016.19. 
  5. Zhang Z,* Fang H,+ Wang H. Multiple Imputation based Clustering Validation (MIV) for Big Longitudinal Trial Data with Missing Values in eHealth. Journal of Medical System. 40 (6):1-9. DOI: 10.1007/s10916-016-0499-0. PMID: 27126063. PMCID: PMC4881752.
  6. Fang, H, Zhang Z,* Zhang J, Houston, T, Ash, A, Allison, J, Identifying & Visualizing Participants’ Engagement Trajectory Patterns in Large-Scale Web Behavioral Intervention, Society of Behavioral Medicine, Washington D.C.
  7. Carreiro, S, Wittbold, M., Premananda, I, Fang, H, Boyer, E. Non-Invasive Biosensors to Detect Physiologic Changes During Opioid Use, Society of Behavioral Medicine, Washington D.C. 
  8. Wang CJ,* Fang H,+ Wang, H. ESammon: A Computationally Enhanced Sammon Mapping based on Data Density.  Proceedings of International Conference on Computing, Networking and Communications, ICNC2016. 1-5. DOI: 10.1109/ICCNC.2016.7440696. PMID: 27668263. PMCID: PMC5033056
  9. Fang H, Wang H, Wang C, Daneshmand, M. Using Probabilistic Approach to Joint Clustering and Statistical Inference: Big Investment Data. IEEE BigData 2015. 2916 - 2918, DOI: 10.1109/BigData.2015.7364121.
  10. Wang CJ,* Fang H,+ Wang C, Daneshmand M, Wang H. A Novel Initialization Method for Particle Swarm Optimization-based FCM in Big Biomedical Data. IEEE BigData 2015. 2942 – 2944, DOI: 10.1109/BigData.2015.7364130.
  11. Zhang Z,* Fang H,+ Wang H. Visualization aided Engagement pattern validation for big longitudinal web behavior intervention data.  17th international Conference on E-health Networking, Application& Services. (IEEE Healthcom’15). 475-478, DOI: 10.1109/HealthCom.2015.7454549.
2015
  1. Wang, C.J,* Fang, H., Wang, H. A Computationally Enhanced Fuzzy Clustering Method for Big Biomedical Data. Section on Statistical Learning and Data Mining, Joint Statistical Meeting, American Statistical Association. Seattle, WA. 
  2. Fang, H, Wittbold, M., Zhang, J., Weng, S, Carreiro, S, Mullins, R, Boyer, E. Describing Real-time Substance-use Detection from Big Biosensor Data: A Case study of Cocaine Users, Health Behavior Methods and Measures paper session, Society of Behavioral Medicine, San Antonio, TX. (Abstract Citation Award)
  3. Fang, H, Zhang, Z.*, Wang, C.J.*, Wang, H., Ma, Y. Using Visualization-aided Trajectory Pattern Validation in a Longitudinal Dietary Data. Health Behavior Methods and Measures paper session , Society of Behavioral Medicine, San Antonio, TX. 
  4. Fang H., Kim, S., Zhang, Z.*, DiFranza, J., Ziedonis, D., Allison, J. A Visualization-aided Trajectory Pattern Recognition Approach to Smoking and Depression among Asian Americans. Society for Research on Nicotine and Tobacco, Philadelphia, PA.
  5. Fang H., Allison, J. Zhang, Z.*, Ash, A. A new look at behavioral interventions: Trajectory pattern recognition approach. 7th Annual Conference on the Science of Dissemination and Implementation, Bethesda, MD
  6. Zhang Z *, Wang H., Wang C., Fang H., "Cluster-based Epidemic Control Through Smartphone-based Body Area Network," IEEE Transactions on Parallel and Distributed Systems (TPDS), March 2015, 26(3), PMID: 25741173.
  7. Zhang Z*, Wang H., Wang C., Fang H., Modeling Epidemics Spreading on Social Contact Networks. IEEE Transactions on Emerging Topics in Computing. doi:10.1109/TETC.2015.2398353. 2015, 3(3), 410-419.
  8. Wang CJ*, Fang H+, Wang H. DAG-searched and Density-based Initial Centroid Location Method for fuzzy clustering of big biomedical data. BICT2014. Feb, 2015, DOI: 10.4108/icst.bict.2014.257932. 
  9. Fang H, Zhang Z*, Wang CJ*, Wang H. A Survey on Big Data Research. 2015. IEEE Network Magazine, 29 (5): 6-9. DOI: 10.1109/MNET.2015.7293298. PMID:26504265.
  10. Carreiro S, Fang H+, Zhang, J, Wittbold K, Weng S, Mullins R, Smelson D, Boyer EW. iMStrong: Deployment of a biosensor system to detect cocaine use. Journal of Medical System. 39(12):186. doi: 10.1007/s10916-015-0337-9. PMID: 26490144.
2014
  1. Fang H., Invited Session Chair, Big Data in Smart Health: Models, Algorithms and Network. Institute of Mathematical Statistics & Section on Statistical Computing. Joint Statistical Meetings, American Statistical Association. Boston, MA, 2014
  2. Fang H., Zhang, Z.*, Huang, J*, Wang, CJ, Wang H. Validating patterns for longitudinal trial data. Section on Statistics in Epidemiology. Joint Statistical Meeting, American Statistical Association. Boston, MA, 2014
  3. Fang H. Zhang, Z.*, Wang H. An enhanced projection pursuit method to aid pattern recognition for longitudinal data. Section on Statistical Learning and Data Mining. Joint Statistical Meeting, American Statistical Association. Boston, MA, 2014
  4. Fang, H., Allison, J. Barton, B., Pagoto, S., Zhang, Z,  Olendzki, G., Ma Y. Pattern Recognition Approach for Behavioral Interventions: An Application to a Dietary Trial, Philadelphia, Society of Behavioral Medicine. Ann Behav Med. 2014, in press.
  5. Fang H., Kim, S., DiFranza, J., Zhang, Z., Ziedonis, D., Allison, J. Pattern recognition approach to culturally-tailored behavioral interventions for smoking cessation: Dose and Timing. Society for Research on Nicotine and Tobacco, Seattle, WA, 2014.
  6. Kim S, Kwon, S., Fang H, Shelley, D., Ziedonis D. A Culturally Adapted Smoking Cessation Intervention for Korean Americans: A Mediating Effect of Perceived Family Norm toward Quitting. Journal of Immigrant and Minority Health. J Immigr Minor Health. 2014 May 31. [Epub ahead of print]. PMID: 24878686.
  7. Kim S, Fang H, Mckee S, Ziedonis D, Prospective Evaluation of Factors Predicting Nicotine withdrawal Symptoms among Korean Americans. Journal of Smoking Cession. Sept, 2014. DOI: http://dx.doi.org/10.1017/jsc.2014.20. Cambridge University Press.