Probabilistic Multi-Scale Modeling of Interdependencies between Critical Infrastructure Systems for Resilience

Johansen, C., and Tien, I., “Probabilistic Multi-Scale Modeling of Interdependencies between Critical Infrastructure Systems for Resilience,” Sustainable and Resilient Infrastructure, 2017

Click for full text of paper (pdf): Johansen and Tien, Probabilistic Multi-Scale Modeling of Interdependencies between Critical Infrastructure Systems for Resilience

Abstract — The prevalence of aging infrastructure and an increase in cascading failures have highlighted the need to focus on building strong, interdependent infrastructure read more…

Reliability Assessment of Critical Infrastructure Using Bayesian Networks

Tien, I., and Der Kiureghian, A., “Reliability Assessment of Critical Infrastructure Using Bayesian Networks,” ASCE Journal of Infrastructure Systems, Vol. 23, No. 4, December 2017

Click for full text of paper (pdf): Tien and Der Kiureghian, Reliability Assessment of Critical Infrastructure Using Bayesian Networks

Abstract — The authors present a Bayesian network (BN)-based approach for modeling and reliability assessment of infrastructure systems. The BN is a powerful framework read more…

Algorithms for Bayesian Network Modeling, Inference, and Reliability Assessment for Multistate Flow Networks

Tong, Y., and Tien, I., “Algorithms for Bayesian Network Modeling, Inference, and Reliability Assessment for Multistate Flow Networks,” ASCE Journal of Computing in Civil Engineering, Vol. 31, No. 5, September 2017

Click for full text of paper (pdf): Tong and Tien, Algorithms for Bayesian Network Modeling, Inference, and Reliability Assessment for Multistate Flow Networks

Abstract — The Bayesian network (BN) is a useful tool for the modeling and reliability assessment of civil infrastructure systems. For a system comprising many read more…

Framework for Probabilistic Assessment of Maximum Nonlinear Structural Response Based on Sensor Measurements: Discretization and Estimation

Saini, A., and Tien, I., “Framework for Probabilistic Assessment of Maximum Nonlinear Structural Response Based on Sensor Measurements: Discretization and Estimation,” ASCE Journal of Engineering Mechanics, Vol. 143, No. 9, September 2017

Click for full text of paper (pdf): Saini and Tien, Framework for Probabilistic Assessment of Maximum Nonlinear Structural Response Based on Sensor Measurements: Discretization and Estimation

Abstract — A probabilistic framework to draw real-time inferences on the maximum response of an uncertain nonlinear structural system under stochastic excitation based on read more…

Impacts of Climate Change on the Assessment of Long-Term Structural Reliability

ASCEJRiskUncertainty

Saini, A., and Tien, I., “Impacts of Climate Change on the Assessment of Long-Term Structural Reliability,” ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Vol. 3, No. 3, September 2017

Click for full text of paper (pdf): Saini and Tien, Impacts of Climate Change on the Assessment of Long-Term Structural Reliability

Abstract — Global climate change has triggered studies across various science and engineering fields. This study demonstrates the need to account for climate change in assessing read more…

Metrics for Evaluating and Improving Community Resilience

ASCEJInfSys

Johansen, C., Horney, J., and Tien, I., “Metrics for Evaluating and Improving Community Resilience,” ASCE Journal of Infrastructure Systems, Vol. 23, No. 2, June 2017

Click for full text of paper (pdf): Johansen, Horney, and Tien, Metrics for Evaluating and Improving Community Resilience

Abstract — The growing risk of natural and artificial or manufactured hazards combined with a lack of community preparedness have revealed the necessity for comprehensive read more…

Algorithms for Bayesian Network Modeling and Reliability Assessment of Infrastructure Systems

RESSTien, I., and Der Kiureghian, A., “Algorithms for Bayesian Network Modeling and Reliability Assessment of Infrastructure Systems,” Reliability Engineering and System Safety, Vol. 156, pp. 134-147, December 2016

Click for full text of paper (pdf): Tien and Der Kiureghian, Algorithms for Bayesian Network Modeling and Reliability Assessment of Infrastructure Systems

Abstract — Novel algorithms are developed to enable the modeling of large, complex infrastructure systems as Bayesian networks (BNs). These include a compression read more…

Probabilistic Framework for Assessing Maximum Structural Response Based on Sensor Measurements

StructuralSafety

Tien, I., Pozzi, M., and Der Kiureghian, A., “Probabilistic Framework for Assessing Maximum Structural Response Based on Sensor Measurements,” Structural Safety, Vol. 61, pp. 43-56, July 2016

Click for full text of paper (pdf): Tien et al, Probabilistic Framework for Assessing Maximum Structural Response Based on Sensor Measurements

Abstract — A probabilistic framework for Bayesian inference combined with extreme values of Gaussian processes is proposed to assess the maximum of the response of an read more…

Detection of Damage and Failure Events of Critical Public Infrastructure Using Social Sensor Big Data

IoTBD2016-logoTien, I., Musaev, A., Benas, D., Ghadi, A., Goodman, S., and Pu, C., “Detection of Damage and Failure Events of Critical Public Infrastructure Using Social Sensor Big Data,” Proceedings of the International Conference on Internet of Things and Big Data (IoTBD 2016), Rome, Italy, pp. 435-440, April 23-25, 2016

Click for full text of paper (pdf): Tien et al, Detection of Damage and Failure Events of Critical Public Infrastructure Using Social Sensor Big Data

Abstract — Public infrastructure systems provide many of the services that are critical to the health, functioning, and security of society. Many of these infrastructures, however, lack continuous physical sensor read more…

Compression and Inference Algorithms for Bayesian Network Modeling of Infrastructure Systems

ICASP-logoTien, I., and Der Kiureghian, A., “Compression and Inference Algorithms for Bayesian Network Modeling of Infrastructure Systems,” In T. Haukaas, ed., Proceedings of the 12th International Conference on Applications of Statistics and Probability in Civil Engineering, Vancouver, Canada, July 12-15, 2015

Click for full text of paper (pdf): Tien and Der Kiureghian, Compression and Inference Algorithms for Bayesian Network Modeling of Infrastructure Systems

Abstract — The Bayesian network (BN) is an ideal tool for modeling and assessing the reliability of civil infrastructure, particularly when the information about the system and its components is uncertain and read more…

A Dynamic Bayesian Network Framework for Risk Assessment of Systems Based on Sensor Measurements

ICASP-logoTien, I., Pozzi, M., and Der Kiureghian, A., “A Dynamic Bayesian Network Framework for Risk Assessment of Systems Based on Sensor Measurements,” In T. Haukaas, ed., Proceedings of the 12th International Conference on Applications of Statistics and Probability in Civil Engineering, Vancouver, Canada, July 12-15, 2015

Click for full text of paper (pdf): Tien et al, A Dynamic Bayesian Network Framework for Risk Assessment of Systems Based on Sensor Measurements

Abstract — In this paper, a framework based the dynamic Bayesian network (DBN) is proposed to dynamically monitor the response of structures to hazards. The methodology enables the probabilistic analysis of read more…

Bayesian Network Methods for Modeling and Reliability Assessment of Infrastructure Systems

SEITien, I., “Bayesian Network Methods for Modeling and Reliability Assessment of Infrastructure Systems,” ASCE Structural Engineering Institute Structures Congress, Portland, OR, April 23-25, 2015

A Compression Algorithm for Inference in Bayesian Network Models of Infrastructure Systems

Tien, I., and Der Kiureghian, A., “A Compression Algorithm for Inference in Bayesian Network Models of Infrastructure Systems,” ASCE Engineering Mechanics Institute Conference, Evanston, IL, August 4-7, 2013

Compression Algorithm for Bayesian Network Modeling of Binary Systems

Tien, I., and Der Kiureghian, A., “Compression Algorithm for Bayesian Network Modeling of Binary Systems,” In G. Deodatis, B. Ellingwood, and D. Frangopol, eds., Safety, Reliability, Risk and Life-Cycle Performance of Structures and Infrastructures, New York: CRC Press, pp. 3075-3081, June 2013

Click for full text of paper (pdf): Tien and Der Kiureghian, Compression Algorithm for Bayesian Network Modeling of Binary Systems

Abstract — A Bayesian network (BN) is a useful tool for analyzing the reliability of systems. The BN framework is limited, however, by the size and complexity of the system that can be tractably modeled. Each node in read more…

Inference on Maximum Structural Response Based on Measured Accelerations Using Dynamic Bayesian Network

Tien, I., Pozzi, M., and Der Kiureghian, A., “Inference on Maximum Structural Response Based on Measured Accelerations Using Dynamic Bayesian Network,” In G. Deodatis, B. Ellingwood, and D. Frangopol, eds. Safety, Reliability, Risk and Life-Cycle Performance of Structures and Infrastructures, New York: CRC Press, pp. 2481-2488, June 2013

Click for full text of paper (pdf): Tien et al, Inference on Maximum Structural Response Based on Measured Accelerations Using Dynamic Bayesian Network

Abstract — A dynamic Bayesian network (DBN) is a useful tool for analyzing uncertain systems that evolve with time. As such, it is useful in structural health monitoring applications where measurements can be read more…

Using a Wireless Inertial Sensor System to Characterize Gait Abnormalities in Parkinson’s Disease

Tien, I., and Aminoff, M., “Using a Wireless Inertial Sensor System to Characterize Gait Abnormalities in Parkinson’s Disease,” Movement Disorders, Vol. 27, Issue Supplement S1, pp. S142, June 2012

Impact of Online Marketing Channels on Customer Purchase Visits: Aggregate- and Individual-Level Models

Tien, I., and Jamal, Z., “Impact of Online Marketing Channels on Customer Purchase Visits: Aggregate- and Individual-Level Models,” HP Labs Technical Report, August 2011

Characterization of Gait Abnormalities in Parkinson’s Disease Using a Wireless Inertial Sensor System

Tien, I., Glaser, S., and Aminoff, M., “Characterization of Gait Abnormalities in Parkinson’s Disease Using a Wireless Inertial Sensor System,” 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Buenos Aires, Argentina, pp. 3353-3356, August 31-September 4, 2010

Click for full text of paper (pdf): Tien et al, Characterization of Gait Abnormalities in Parkinson’s Disease Using a Wireless Inertial Sensor System

Abstract — Gait analysis is important in diagnosing and evaluating certain neurological diseases such as Parkinson’s disease (PD). In this paper, we show the ability of our wireless inertial sensor system to read more…

Results of Using a Wireless Inertial Measuring System to Quantify Gait Motions in Control Subjects

Tien, I., Glaser, S., Bajcsy, R., Goodin, D., and Aminoff, M., “Results of Using a Wireless Inertial Measuring System to Quantify Gait Motions in Control Subjects,” IEEE Transactions on Information Technology in Biomedicine, Vol. 14, No. 4, pp. 904-915, July 2010

Click for full text of paper (pdf): Tien et al, Results of Using a Wireless Inertial Measuring System to Quantify Gait Motions in Control Subjects

Abstract — Gait analysis is important for the diagnosis of many neurological diseases such as Parkinson’s. The discovery and interpretation of minor gait abnormalities can aid in early diagnosis. We have used an read more…

Structural Health Monitoring and Evaluation of Human Gait to Assist in the Diagnosis of Parkinson’s Disease

Tien, I., and Glaser, S., “Structural Health Monitoring and Evaluation of Human Gait to Assist in the Diagnosis of Parkinson’s Disease,” Proceedings, 7th International Workshop on Structural Health Monitoring, Stanford, CA, September 9-11, 2009

Click for full text of paper (pdf): Tien and Glaser, Structural Health Monitoring and Evaluation of Human Gait to Assist in the Diagnosis of Parkinson’s Disease

Abstract — The human body is a complex structure, and its structural health can be monitored using sensors. A system using wireless inertial measurement units for data acquisition and the monitoring of human read more…

Detecting and Quantifying Gait Abnormalities in Parkinson’s Patients Using Wireless Inertial Measurement Units

Tien, I., “Detecting and Quantifying Gait Abnormalities in Parkinson’s Patients Using Wireless Inertial Measurement Units,” Center for Information Technology Research in the Interest of Society Open House, Berkeley EECS Annual Research Symposium, Berkeley, CA, February 2009

Quantifying Diagnosis of Neurological Conditions

Tien, I., “Quantifying Diagnosis of Neurological Conditions,” Scientific Colloquium for Healthcare, Engineering and Medicine, UC Davis Medical Center, Davis, CA, May 2008

Quantifying Diagnosis of Neurological Conditions

Tien, I., “Quantifying Diagnosis of Neurological Conditions,” Center for Information Technology Research in the Interest of Society Open House, Berkeley EECS Annual Research Symposium, February 2008

Designing for Designers: Lessons Learned from Schools of Architecture

 

Cranz, G., Wendover, J., Tien, I., Gillem, M., and Norman, J., “Chapter 9: A Post-Occupancy Evaluation of the Temporary Home of the College of Environmental Design on the UC Berkeley Campus,” Designing for Designers: Lessons Learned from Schools of Architecture, Fairchild Books, September 2007

Post-Occupancy Evaluation of the San Francisco Public Library

Cranz, G., and Tien, I., “Post-Occupancy Evaluation of the San Francisco Public Library,” Annual Conference of the Association for Applied and Clinical Sociology, San Jose, CA, October 26-28, 2006