A5064900186- Structural Health Monitoring Techniques
- Infrastructure Maintenance and Monitoring
- Concrete Corrosion and Durability
- Probabilistic and Robust Engineering Design
- Gait Recognition and Analysis
- Fault Detection and Control Systems
- Structural Engineering and Vibration Analysis
- Indoor and Outdoor Localization Technologies
- Aging and Gerontology Research
- Masonry and Concrete Structural Analysis
- Physical Activity and Health
- BIM and Construction Integration
- Non-Destructive Testing Techniques
- Balance, Gait, and Falls Prevention
- Anomaly Detection Techniques and Applications
- Medical Imaging and Analysis
- Wood Treatment and Properties
- Voice and Speech Disorders
- Advanced Sensor and Energy Harvesting Materials
- Face recognition and analysis
- Water Systems and Optimization
- Psychological Well-being and Life Satisfaction
- Structural Integrity and Reliability Analysis
- Video Surveillance and Tracking Methods
- Non-Invasive Vital Sign Monitoring
University of California, San Diego
2025
North Carolina State University
2024
École Polytechnique Fédérale de Lausanne
2016-2021
The Cambridge Centre for Advanced Research and Education in Singapore
2021
ETH Zurich
2019
Singapore Institute of Technology
2019
University of British Columbia
2016
University of Hawaii System
2005
Background: Liver ultrasound segmentation is challenging due to low image quality and variability. While deep learning (DL) models have been widely applied for medical segmentation, generic pre-configured may not meet the specific requirements targeted areas in liver ultrasound. Quantitative (QUS) emerging as a promising tool fat measurement; however, accurately segmenting regions of interest within images remains challenge. Methods: We introduce generalizable framework using an adaptive...
Accurate measurement-data interpretation leads to increased understanding of structural behaviour and enhanced asset-management decision making. In this paper, four data-interpretation methodologies, residual minimization, traditional Bayesian model updating, modified updating (with an $L_\infty$-norm-based Gaussian likelihood function) error-domain falsification (EDMF), a method that rejects models have unlikely differences between predictions measurements, are compared. the methodology,...
Sensor-based occupant tracking has the potential to enhance knowledge of utilization buildings. Occupancy-tracking strategies using footstep-induced floor vibrations may be beneficial for thermal-load prediction, security enhancement and care-giving without undermining privacy. Current floor-vibration-based occupant-tracking methodologies are based on data-driven techniques that do not include a physics-based model structural behavior slab. These suffer from ambiguous interpretations when...
Structural identification using physics-based models and subsequent prediction have much potential to enhance civil infrastructure asset-management decision-making. Interpreting monitoring information in the presence of multiple uncertainty sources systematic bias a model is computationally expensive task. The computational cost this task exponentially proportional number parameters updated data. In paper, novel model-class selection method proposed obtain optimal identifiable classes....
With increasing urbanization and depleting reserves of raw materials for construction, sustainable management existing infrastructure will be an important challenge in this century. Structural sensing has the potential to increase knowledge behavior improve engineering decision making asset management. Model-based methodologies such as residual minimization (RM), Bayesian model updating (BMU) error-domain falsification (EDMF) have been proposed interpret monitoring data support Application...
Occupant detection and recognition support functional goals such as security, healthcare, energy management in buildings. Typical sensing approaches, smartphones cameras, undermine the privacy of building occupants inherently affect their behavior. To overcome these drawbacks, a non-intrusive technique using floor-vibration measurements, induced by human footsteps, is outlined. Detection human-footstep impacts an essential step to estimate number occupants, recognize identities provide...
New methods are required for sustainable and economical management of bridges. Efficient can be achieved by a detailed understanding bridge behavior through monitoring model-based data interpretation. This paper presents methodology to evaluate the fatigue safety existing bridges based on conducting measurements onsite interpreting measurement using physics-based models. The combines from different nondestructive with structural models develop suitable set feasible that describe accurately...
Identification of occupant presence and location inside buildings is essential to functional goals such as security, healthcare, energy management. Floor-vibration measurements, induced by footstep impacts, provide a non-intrusive sensing method for identification, unlike cameras smartphones. Detecting the an necessary first step identification. A challenge detection ambient noise that may hide footstep-induced floor-vibration signatures. Also, spurious events door closing, chair dragging...
This paper presents a study on force transfer around openings (FTAO) in cross-laminated timber (CLT) shear walls. To elucidate the load mechanism CLT walls, this used finite-element models to five different wall configurations. The effect of uncertainty behavior connectors over its force-deformation and design was also studied. In coupled-panel wall, presence an opening decreased strength stiffness tie-rods were provided as reinforcement limit deformation between panels improve stiffness....
Monitoring and interpreting structural response using structural-identification methodologies improves understanding of civil-infrastructure behavior. New sensing devices inexpensive computation has made model-based data interpretation feasible in engineering practice. Many data-interpretation methodologies, such as Bayesian model updating residual minimization, involve strong assumptions regarding uncertainty conditions. While much research been conducted on the scientific development these...
Neuromuscular diseases pose significant health and economic challenges, necessitating innovative monitoring technologies for personalizable treatment. Existing devices detect muscular motions either indirectly from mechanoacoustic signatures on skin surface or via ultrasound waves that demand specialized adhesion. Here, we report a wireless wearable system, Laryngeal Health Monitor (LaHMo), designed to be conformally placed the neck continuously measuring movements of underlying muscles. The...
In sensed buildings, information related to occupant movement helps optimize functions such as security, energy management, and caregiving. Due privacy needs, non-intrusive sensing approaches for tracking occupants inside vibration sensors, are often preferred over intrusive strategies that involve use of cameras wearable devices. Current sensor-based occupant-localization data-driven techniques do not account structural behavior limited slabs on grade. Varying-rigidity floors inherent...
Building utilization can be enhanced by tracking occupants. Non-intrusive of occupants using floor-vibration measurements is beneficial for many smart-building applications such as energy consumption, security enhancement, and care-giving. Also, unlike cameras, vibration do not undermine privacy. Current methodologies interpreting floor vibrations are often data-driven thus, account the varying stiffness due to structural elements beams, columns walls. In this paper, characteristics...
Abstract The management of existing civil infrastructure is challenging due to evolving functional requirements, aging and climate change. Civil often has hidden reserve capacity because conservative approaches used in design during construction. Information collected through sensor measurements the potential improve knowledge structural behavior, leading better decisions related asset management. In this situation, monitoring system an important task since it directly affects quality...
This study assesses the impact of single-player and multiplayer exergaming modes on improving exercise intentions, reduction fear falling, emotional well-being among older adults, primarily from low socioeconomic status (SES) backgrounds-a group often underrepresented in exergame research.
Falls and fall-related injuries among older adults in Singapore are a serious health problem that require early intervention. In previous research, exercise interventions have been effective improving functional outcomes reducing falls for broad group of adults. However, results from multi-domain, multi-component prevention programs high fall risk the community remain equivocal. One reason these is there significant heterogeneity factors amongst which makes tailoring multicomponent complex....