Teresa Wu's research while affiliated with Arizona State University and other places

Publications (16)

Article
Understanding bubble dynamics during boiling is challenging due to the drastic changes in system parameters, such as nucleation, bubble morphology, temperature, and pressure. In this study, principal component analysis (PCA), an unsupervised dimensionality reduction algorithm, is used to extract new physical descriptors of boiling heat transfer fro...
Article
Literature on building Automatic Fault Detection and Diagnosis (AFDD) mainly focuses on simulated system data due to high expenses and difficulties of obtaining and analyzing real building data. There is a lack of validation on performances and scalabilities of data-driven AFDD approaches using simulated data and how it compares to that from real b...
Chapter
Compressed sensing (CS) has become a popular field in the last two decades to represent and reconstruct a sparse signal with much fewer samples than the signal itself. Although regular images are not sparse on their own, many can be sparsely represented in wavelet transform domain. Therefore, CS has also been widely applied to represent digital ima...
Conference Paper
Full-text available
Studies indicate that a large energy saving can be realized by applying automatic fault detection and diagnosis (AFDD) to building systems, which consumes more than 40% of the primary energy in the U.S. To enable AFDD, a baseline depicting the normal operation mode is needed to detect whether the building operation deviates from normality. Differen...
Article
Full-text available
Falls are among the most common cause of decreased mobility and independence in older adults and rank as one of the most severe public health problems with frequent fatal consequences. In the present study, gait characteristics from 171 community-dwelling older adults were evaluated to determine their predictive ability for future falls using a wea...
Article
The objectives of this study are to investigate building professionals' experience, awareness, and interest in occupant health in buildings, and to assess the impact of the COVID-19 pandemic on their opinions, as well as to compare the research on occupant health in buildings to professionals' opinions. To address these objectives, a mixed research...
Article
This paper presents the results from an international survey that investigated the impacts of the built environment on occupant well-being during the COVID-19 pandemic when most professionals were forced to work from home (WFH). The survey was comprised of 81 questions focusing on the respondent's profiles, residences, home indoor environmental qua...
Article
Image-based deep learning (DL) models are employed to enable the detection of critical heat flux (CHF) based on pool boiling experimental images. Most machine learning approaches for pool boiling to date focus on a single dataset under a certain heater surface, working fluid, and operating conditions. For new datasets collected under different cond...
Preprint
Full-text available
A comparative study between using a dynamic Bayesian network (DBN) against using a static Bayesian network (BN) for building heating ventilating, and air conditioning fault diagnosis (HVAC) is presented. Contrarily to a static BN, DBN method incorporates temporal dependencies between fault nodes between timesteps using temporal conditional probabil...
Article
Gaussian Mixture Model (GMM) is a popular clustering algorithm due to its neat statistical properties, which enable the “soft” clustering and the determination of the number of clusters. Expectation-Maximization (EM) is usually applied to estimate the GMM parameters. While promising, the inclusion of features that are not contributing to clustering...
Preprint
Compressed sensing (CS) has become a popular field in the last two decades to represent and reconstruct a sparse signal with much fewer samples than the signal itself. Although regular images are not sparse in their own, many can be sparsely represented in wavelet transform domain. Therefore, CS has also been widely applied to represent digital ima...
Article
Even before the COVID-19 pandemic, people spent on average around 90% of their time indoors. Now more than ever, with work-from-home orders in place, it is crucial that we radically rethink the design and operation of buildings. Indoor Environmental Quality (IEQ) directly affects the comfort and well-being of occupants. When IEQ is compromised, occ...
Article
This study explores self-reports of 241 older adults (aged 63–95) regarding loneliness and social disconnectedness, and the potential for information and communication technologies (ICT) and ride-hailing services to mitigate these phenomena. The samples are drawn from four older adult living communities in Maricopa County, Arizona. Lonelier older a...
Chapter
Modern imaging technique provides a fast, noninvasive means to study physiologic, metabolic, and molecular processes in the body. Imaging is the primary means in clinical cancer practice to facilitate diagnosis, prognosis, and treatment evaluation. While breast cancer contributes to 25% of morbidity in all cancer and is the second leading cause of...

Citations

... While these datasets address a severe lack of publicly available benchmark datasets, they are not representative of real-world datasets. In 2022, Huang et al. [21] found that the performance of FDD strategies developed on simulated data and directly applied to real building data is less that satisfactory. In practical applications, the granularity of the data is less sufficient, the metadata is not well described, and there is a lack of well-labelled faults with multiple severity ratings. ...
... The limited invasiveness of wearable inertial sensors can significantly simplify the routine assessment of DS subjects. Human movement analysis methods, based on wearable inertial sensors, have been widely adopted to study human motion during static and dynamic conditions in different pathologies [12][13][14][15][16][17]. These have for example been used in identifying parkinsonian and ataxic features [18][19][20][21][22] allowing the quantitative assessment in outpatient settings throughout the life span, effectively integrating the information derived from qualitative observation. ...
... This is supported by investigations within the completed International Energy Agency (IEA), Energy in Buildings and Communities Programme (EBC) Annex 66 "Definition and Simulation of Occupant Behavior in Buildings" [11] and the ongoing Annex 79 "Occupant-Centric Building Design and Operation" [12]. Occupant-centric design and operation goes beyond building performance metrics to value occupant health, comfort, and productivity [13,14]. Therefore, the role of building operators has been expanded to incorporate occupant needs to reduce the negative impact occupant behavior has on building performance when their needs are not met. ...
... Machine learning (ML) has been applied to boiling studies in recent years, from detecting flow boiling regimes, the onset of film boiling, CHF, and departure from nucleate boiling, to estimating boiling heat flux, heat transfer coefficient, nucleation site density, and bubble statistics [39][40][41][42][43][44][45][46][47][48][49][50][51][52][53][54][55] . The supervised learning approaches in the past have used artificial neural networks (ANN) [ 42 , 44 , 4 8 , 4 9 , 51-55 ], support vector machines (SVM) [39] , and convolutional neural networks (CNN) [ 40 , 41 , 43 , 45 , 46 ] to perform boiling image classification based on boiling regimes. ...
... The wrapper approach differs from the filter method in that it uses a learning algorithm during the validation step, while the filter method tests particular features independently of the classification process by using a certain basic threshold [26,27]. The embedded model is applicable to the wrapper method, as the classifier is used in the selection process at the assessment level; however, the use of the classifier in the embedded method is relatively less cost-effective than in the wrapper method [28]. On the other hand, the hybrid approach sequentially uses a filter and a wrapper method, and thus the selection of features requires two iterations. ...
... Studies have started to investigate the new ventilation guidelines and their possible influence on both building occupants and its energy performance. While most of the recommendations in the studied guidelines are mostly similar, the precise ventilation rate required to limit the spread of an airborne virus, such as SARS-CoV-2, is not specified and requires more investigation (Awada et al. 2021). Although there is still no fixed suggested number for the building's ventilation in a pandemic or post-pandemic time, it is necessary to study the performance of different ventilation approaches on the infection risk. ...
... The high risk of social isolation was related to the broken relationship, such as the divorce and separation of live-in relationship, which leads to being disconnected to all forms of social connection involving family, friends, relatives, and associations (Eckhard, 2020). Correlation between social disconnectedness and loneliness were found among lonelier older adults with less supportive individuals in their lives (Talmage et al., 2020). Moreover, the relation between Social disconnectedness and loneliness is associated with psychiatric illnesses . ...
... For example, LBP features are used to compare the texture features of paper to distinguish the authenticity and reliability of valuable documents, banknotes, tickets or rare collectible cards [9,36]. LBP features also play a key role in medical image detection and cancer screening [7]. The latest literatures show that the classification method based on LBP features can achieve 96% accuracy in the detection of female breast cancer [40]. ...