An immune tolerant tumor microenvironment promotes immune evasion of lung cancer. Agents that ant... more An immune tolerant tumor microenvironment promotes immune evasion of lung cancer. Agents that antagonize immune tolerance will thus aid the fight against this devastating disease. Members of the tumor necrosis factor receptor (TNFR) family modulate the magnitude, duration and phenotype of immune responsiveness to antigens. Among these, GITR expressed on immune cells functions as a key regulator in inflammatory and immune responses. Here, we evaluate the GITR agonistic antibody (DTA-1) as a mono-therapy and in combination with therapeutic vaccination in murine lung cancer models. We found that DTA-1 treatment of tumor-bearing mice increased: (i) the frequency and activation of intratumoral natural killer (NK) cells and T lymphocytes, (ii) the antigen presenting cell (APC) activity in the tumor, and (iii) systemic T-cell specific tumor cell cytolysis. DTA-1 treatment enhanced tumor cell apoptosis as quantified by cleaved caspase-3 staining in the tumors. DTA-1 treatment increased expr...
To report penile integrity measures, including stretched penile length (SPL), from a randomized, ... more To report penile integrity measures, including stretched penile length (SPL), from a randomized, double-blind, double-dummy, placebo-controlled trial evaluating treatment with tadalafil initiated after nerve-sparing radical prostatectomy (nsRP). Patients aged ≤68 years were randomized after nsRP 1:1:1 to 9-month double-blind treatment (DBT) with tadalafil 5 mg once daily (OaD), 20-mg tadalafil on-demand ("pro-re-nata"; PRN), or placebo, followed by 6-week drug-free washout and 3-month open-label OaD treatment. Secondary outcome measures included the change in SPL from pre-nsRP to the end of DBT (analysis of covariance adjusting for treatment, country, baseline, age, and nerve-sparing score), responses to Sexual Encounter Profile (SEP) questions 1-3 (mixed models for repeated measures adjusting for treatment, country, visit, visit-treatment-interaction, age), and Standardized Morning Erection Question (Cochran-Mantel-Haenszel test adjusted for age and country). Four hundred...
Optimal control of systems with complex nonlinear behaviour such as steady state multiplicity res... more Optimal control of systems with complex nonlinear behaviour such as steady state multiplicity results in a nonlinear optimization problem that needs to be solved online at each sample time. We present an approach based on simulation, function approximation and evolutionary improvement aimed towards simplifying online optimization. Closed loop data from a suboptimal control law, such as MPC based on successive linearization, are used to obtain an approximation of the 'cost-to-go' function, which is subsequently improved through iterations of the Bellman equation. Using this offline-computed cost approximation, an infinite horizon problem is converted to an equivalent single stage problem}substantially reducing the computational burden. This approach is tested on continuous culture of microbes growing on a nutrient medium containing two substrates that exhibits steady state multiplicity. Extrapolation of the cost-to-go function approximator can lead to deterioration of online performance. Some remedies to prevent such problems caused by extrapolation are proposed. ðxÞ; calculate J iþ1 ðkÞ for the given sample points of x by solving
In many resource-constrained project scheduling problems (RCPSP), the set of candidate projects i... more In many resource-constrained project scheduling problems (RCPSP), the set of candidate projects is not fixed a priori but evolves with time. For example, while performing an initial set of projects according to a certain decision policy, a new promising project can emerge. To make an appropriate resource allocation decision for such a problem, project cancellation and resource idling decisions should complement the conventional scheduling decisions. In this study, the problem of stochastic RCPSP (sRCPSP) with dynamic project arrivals is addressed with the added flexibility of project cancellation and resource idling. To solve the problem, a Q-Learning-based approach is adopted. To use the approach, the problem is formulated as a Markov Decision Process with appropriate definitions of states, including information state and action variables. The Q-Learning approach enables us to derive an empirical state transition rules from simulation data so that analytical calculations of potentially exorbitantly complicated state transition rules can be circumvented. To maximize the advantage of using the empirically learned state transition rules, special type of actions including project cancellation and resource idling, which are difficult to incorporate into heuristics, were randomly added in the simulation. The random actions are filtered during the Q-Value iteration and properly utilized in the online decision making to maximize the total expected reward.
This paper deals with a new scheme for the prediction of a ball bearing's remaining useful life b... more This paper deals with a new scheme for the prediction of a ball bearing's remaining useful life based on self-organizing map (SOM) and back propagation neural network methods. One of the key components needed for effective bearing life prediction is the set-up of an appropriate degradation indicator from a bearing's incipient defect stage to its final failure. This new method is different from the others that have been used in the past, in that it uses the minimum quantisation error (MQE) indicator derived from SOM, which is trained by six vibration features, including a new designed degradation index for performance degradation assessment. Then, using this indicator, back propagation neural networks focusing on the degradation periods can be trained. Thanks to weight application to failure times (WAFT) technology, a useful life prediction model for ball bearings has been developed successfully. Finally, a set of accelerated bearing run-to-failure experiments is carried out, with the experimental results showing that the new proposed methods are greatly superior to those, based on L10 bearing life prediction, currently being used.
Sequential imperfect preventive maintenance policy leads to a decreasing sequence of maintenance ... more Sequential imperfect preventive maintenance policy leads to a decreasing sequence of maintenance intervals which is practical in engineering while CBPM (condition based predictive maintenance) techniques provide the assessment and prediction of the system condition based on the data collected through continuous monitoring.
De-noising and extraction of the weak signature are crucial to fault prognostics in which case fe... more De-noising and extraction of the weak signature are crucial to fault prognostics in which case features are often very weak and masked by noise. The wavelet transform has been widely used in signal de-noising due to its extraordinary time-frequency representation capability. In this paper, the performance of wavelet decomposition-based de-noising and wavelet filter-based de-noising methods are compared based on signals from mechanical defects. The comparison result reveals that wavelet filter is more suitable and reliable to detect a weak signature of mechanical impulse-like defect signals, whereas the wavelet decomposition de-noising method can achieve satisfactory results on smooth signal detection. In order to select optimal parameters for the wavelet filter, a two-step optimization process is proposed. Minimal Shannon entropy is used to optimize the Morlet wavelet shape factor. A periodicity detection method based on singular value decomposition (SVD) is used to choose the appropriate scale for the wavelet transform. The signal de-noising results from both simulated signals and experimental data are presented and both support the proposed method. r
This paper investigates the choice of function approximator for an approximate dynamic programmin... more This paper investigates the choice of function approximator for an approximate dynamic programming (ADP) based control strategy. The ADP strategy allows the user to derive an improved control policy given a simulation model and some starting control policy (or alternatively, closed-loop identification data), while circumventing the Ôcurse-of-dimensionalityÕ of the traditional dynamic programming approach. In ADP, one fits a function approximator to state vs. Ôcost-to-goÕ data and solves the Bellman equation with the approximator in an iterative manner. A proper choice and design of function approximator is critical for convergence of the iteration and the quality of final learned control policy, because an approximation error can grow quickly in the loop of optimization and function approximation. Typical classes of approximators used in related approaches are parameterized global approximators (e.g. artificial neural networks) and nonparametric local averagers (e.g. k-nearest neighbor). In this paper, we assert on the basis of some case studies and a theoretical result that a certain type of local averagers should be preferred over global approximators as the former ensures monotonic convergence of the iteration. However, a converged cost-to-go function does not necessarily lead to a stable control policy on-line due to the problem of over-extrapolation. To cope with this difficulty, we propose that a penalty term be included in the objective function in each minimization to discourage the optimizer from finding a solution in the regions of state space where the local data density is inadequately low. A nonparametric density estimator, which can be naturally combined with a local averager, is employed for this purpose.
In today's global competitive marketplace, there is intense pressure for manufacturing industries... more In today's global competitive marketplace, there is intense pressure for manufacturing industries to continuously reduce and eliminate costly, unscheduled downtime and unexpected breakdowns. With the advent of Internet and tether-free technologies, companies necessitate dramatic changes in transforming traditional ''fail and fix (FAF)'' maintenance practices to a ''predict and prevent (PAP)'' e-maintenance methodology. Emaintenance addresses the fundamental needs of predictive intelligence tools to monitor the degradation rather than detecting the faults in a networked environment and, ultimately to optimize asset utilization in the facility. This paper introduces the emerging field of e-maintenance and its critical elements. Furthermore, performance assessment and prediction tools are introduced for continuous assessment and prediction of a particular product's performance, ultimately enable proactive maintenance to prevent machine from breakdowns. Recent advances on intelligent prognostic technologies and tools are discussed. Several case studies are introduced to validate these developed technologies and tools. #
We propose two approximate dynamic programming (ADP)-based strategies for control of nonlinear pr... more We propose two approximate dynamic programming (ADP)-based strategies for control of nonlinear processes using input-output data. In the first strategy, which we term 'J -learning,' one builds an empirical nonlinear model using closed-loop test data and performs dynamic programming with it to derive an improved control policy. In the second strategy, called 'Q-learning,' one tries to learn an improved control policy in a model-less manner. Compared to the conventional model predictive control approach, the new approach offers some practical advantages in using nonlinear empirical models for process control. Besides the potential reduction in the on-line computational burden, it offers a convenient way to control the degree of model extrapolation in the calculation of optimal control moves. One major difficulty associated with using an empirical model within the multi-step predictive control setting is that the model can be excessively extrapolated into regions of the state space where identification data were scarce or nonexistent, leading to performances far worse than predicted by the model. Within the proposed ADP-based strategies, this problem is handled by imposing a penalty term designed on the basis of local data distribution. A CSTR example is provided to illustrate the proposed approaches.
Proceedings of the SIGCHI conference on Human factors in computing systems - CHI '00, 2000
We introduce HandSCAPE, an orientation-aware digital tape measure, as an input device for digitiz... more We introduce HandSCAPE, an orientation-aware digital tape measure, as an input device for digitizing field measurements, and visualizing the volume of the resulting vectors with computer graphics. Using embedded orientation-sensing hardware, HandSCAPE captures relevant vectors on each linear measurements and transmits this data wirelessly to a remote computer in real-time. To guide us in design, we have closely studied the intended users, their tasks, and the physical workplaces to extract the needs from real worlds. In this paper, we first describe the potential utility of HandSCAPE for three on-site application areas: archeological surveys, interior design, and storage space allocation. We then describe the overall system which includes orientation sensing, vector calculation, and primitive modeling. With exploratory usage results, we conclude our paper for interface design issues and future developments.
In response to the problem of adolescent smoking and limited appropriate cessation resources, thi... more In response to the problem of adolescent smoking and limited appropriate cessation resources, this study examined the pattern and structure of the American Lung Association, Why Do You Smoke? (WDS) to determine its appropriateness for use in youth smoking cessation programs. The WDS is used to help smokers identify primary motivations for using tobacco and is comprised of eight subscales, each with three items representing primary smoking motivations ("Stimulation," "Handling," "Pleasure," "Crutch," "Psychological," "Habit," "Peer," and "Independence"). Study participants were all minors enrolled in a tobacco cessation program (n = 251). The pattern and structure of this self-assessment was examined using a correlated multiple group component factor analysis as a confirmatory approach. Findings show that the level of endorsement (as evidenced by subscale means and standard deviations) was relatively larg...
Proceedings of the American Thoracic Society, 2008
Worldwide over 1 million people die due to lung cancer each year. It is estimated that cigarette ... more Worldwide over 1 million people die due to lung cancer each year. It is estimated that cigarette smoking explains almost 90% of lung cancer risk in men and 70 to 80% in women. Clinically evident lung cancers have multiple genetic and epigenetic abnormalities. These abnormalities may result in activation of oncogenes and inactivation of tumor-suppressor genes. Chronic inflammation, which is known to promote cancer, may result both from smoking and from genetic abnormalities. These mediators in turn may be responsible for increased macrophage recruitment, delayed neutrophil clearance, and increase in reactive oxygen species (ROS). Thus, the pulmonary environment presents a unique milieu in which lung carcinogenesis proceeds in complicity with the host cellular network. The pulmonary diseases that are associated with the greatest risk for lung cancer are characterized by abundant and deregulated inflammation. Pulmonary disorders such as chronic obstructive pulmonary disease (COPD)/emph...
Determining operative risk in patients undergoing aortic surgery is a difficult process, as multi... more Determining operative risk in patients undergoing aortic surgery is a difficult process, as multiple variables converge to affect overall mortality. Patient frailty is certainly a contributing factor, but is difficult to measure, with surgeons often relying on subjective or intuitive influences. We sought to use core muscle size as an objective measure of frailty, and determine its utility as a predictor of survival after abdominal aortic aneurysm (AAA) repair. Four hundred seventy-nine patients underwent elective open AAA repair between 2000 and 2008. Two hundred sixty-two patients (54.7%) had preoperative computed tomography (CT) scans available for analysis. Cross-sectional areas of the psoas muscles at the level of the L4 vertebra were measured. The covariate-adjusted effect of psoas area on postoperative mortality was assessed using Cox regression. Of the 262 patients, there were 55 deaths and the mean length of follow-up was 2.3 years. Cox regression revealed a significant ass...
Obesity is a known risk factor for surgical site infection (SSI). Our hypothesis is that morphome... more Obesity is a known risk factor for surgical site infection (SSI). Our hypothesis is that morphometric measures of midline subcutaneous fat will be associated with increased risk of SSI and will predict SSI better than conventional measures of obesity. We identified 655 patients who underwent midline laparotomy (2006 to 2009) using the Michigan Surgical Quality Collaborative database. Using novel, semiautomated analytic morphometric techniques, the thickness of subcutaneous fat along the linea alba was measured between T12 and L4. To adjust for variations in patient size, subcutaneous fat was normalized to the distance between the vertebrae and anterior skin. Logistic regression analyses were used to identify factors independently associated with the incidence of SSI. Overall, SSIs were observed in 12.5% (n = 82) of the population. Logistic regression revealed that patients with increased subcutaneous fat had significantly greater odds of developing a superficial incisional SSI (odds...
2008 International Conference on Prognostics and Health Management, 2008
This paper presents a similarity-based approach for estimating the Remaining Useful Life (RUL) in... more This paper presents a similarity-based approach for estimating the Remaining Useful Life (RUL) in prognostics. The approach is especially suitable for situations in which abundant run-to-failure data for an engineered system are available. Data from multiple units of the same system are used to create a library of degradation patterns. When estimating the RUL of a test unit, the data from it will be matched to those patterns in the library and the actual life of those matched units will be used as the basis of estimation. This approach is used to tackle the data challenge problem defined by the 2008 PHM Data Challenge Competition, in which, run-to-failure data of an unspecified engineered system are provided and the RUL of a set of test units will be estimated. Results show that the similarity-based approach is very effective in performing RUL estimation.
Parents represent a key ecological component in influencing their child's physical activity. ... more Parents represent a key ecological component in influencing their child's physical activity. The aim of this exploratory study was to assess the relationship between maternal acculturation and physical activity in Hispanic children. 102 Hispanic mothers (mean age 36.2 yrs; +SD 7.3 yrs) and their children (mean age 10.0 yrs, +SD 0.8 yrs) participated. Most of the mothers (74%) were foreign-born, with 62% classified as low acculturated and 38% high acculturated. Demographic, acculturation, and anthropometric measures were completed by mothers and children. Physical activity was measured using accelerometers. Relationships between maternal acculturation and demographic variables and children's physical activity were examined using chi-square, Analysis of Variance, and simple regression. Children had higher physical activity levels than their mothers (t(49) = -7.87, P < .0001). Significant correlations between maternal and child's physical activity levels were observed in...
... Feibai Zhu Mohamed AbuAli Jay Lee NSF I/UCRC Center for Intelligent Maintenance Systems (IMS)... more ... Feibai Zhu Mohamed AbuAli Jay Lee NSF I/UCRC Center for Intelligent Maintenance Systems (IMS) College of ... Figure 9. Testbed and DAQ Setup [5] ... References: 1. Lee, J., et al., A systematic approach for predictive maintenance service design: methodology and applications. ...
An immune tolerant tumor microenvironment promotes immune evasion of lung cancer. Agents that ant... more An immune tolerant tumor microenvironment promotes immune evasion of lung cancer. Agents that antagonize immune tolerance will thus aid the fight against this devastating disease. Members of the tumor necrosis factor receptor (TNFR) family modulate the magnitude, duration and phenotype of immune responsiveness to antigens. Among these, GITR expressed on immune cells functions as a key regulator in inflammatory and immune responses. Here, we evaluate the GITR agonistic antibody (DTA-1) as a mono-therapy and in combination with therapeutic vaccination in murine lung cancer models. We found that DTA-1 treatment of tumor-bearing mice increased: (i) the frequency and activation of intratumoral natural killer (NK) cells and T lymphocytes, (ii) the antigen presenting cell (APC) activity in the tumor, and (iii) systemic T-cell specific tumor cell cytolysis. DTA-1 treatment enhanced tumor cell apoptosis as quantified by cleaved caspase-3 staining in the tumors. DTA-1 treatment increased expr...
To report penile integrity measures, including stretched penile length (SPL), from a randomized, ... more To report penile integrity measures, including stretched penile length (SPL), from a randomized, double-blind, double-dummy, placebo-controlled trial evaluating treatment with tadalafil initiated after nerve-sparing radical prostatectomy (nsRP). Patients aged ≤68 years were randomized after nsRP 1:1:1 to 9-month double-blind treatment (DBT) with tadalafil 5 mg once daily (OaD), 20-mg tadalafil on-demand ("pro-re-nata"; PRN), or placebo, followed by 6-week drug-free washout and 3-month open-label OaD treatment. Secondary outcome measures included the change in SPL from pre-nsRP to the end of DBT (analysis of covariance adjusting for treatment, country, baseline, age, and nerve-sparing score), responses to Sexual Encounter Profile (SEP) questions 1-3 (mixed models for repeated measures adjusting for treatment, country, visit, visit-treatment-interaction, age), and Standardized Morning Erection Question (Cochran-Mantel-Haenszel test adjusted for age and country). Four hundred...
Optimal control of systems with complex nonlinear behaviour such as steady state multiplicity res... more Optimal control of systems with complex nonlinear behaviour such as steady state multiplicity results in a nonlinear optimization problem that needs to be solved online at each sample time. We present an approach based on simulation, function approximation and evolutionary improvement aimed towards simplifying online optimization. Closed loop data from a suboptimal control law, such as MPC based on successive linearization, are used to obtain an approximation of the 'cost-to-go' function, which is subsequently improved through iterations of the Bellman equation. Using this offline-computed cost approximation, an infinite horizon problem is converted to an equivalent single stage problem}substantially reducing the computational burden. This approach is tested on continuous culture of microbes growing on a nutrient medium containing two substrates that exhibits steady state multiplicity. Extrapolation of the cost-to-go function approximator can lead to deterioration of online performance. Some remedies to prevent such problems caused by extrapolation are proposed. ðxÞ; calculate J iþ1 ðkÞ for the given sample points of x by solving
In many resource-constrained project scheduling problems (RCPSP), the set of candidate projects i... more In many resource-constrained project scheduling problems (RCPSP), the set of candidate projects is not fixed a priori but evolves with time. For example, while performing an initial set of projects according to a certain decision policy, a new promising project can emerge. To make an appropriate resource allocation decision for such a problem, project cancellation and resource idling decisions should complement the conventional scheduling decisions. In this study, the problem of stochastic RCPSP (sRCPSP) with dynamic project arrivals is addressed with the added flexibility of project cancellation and resource idling. To solve the problem, a Q-Learning-based approach is adopted. To use the approach, the problem is formulated as a Markov Decision Process with appropriate definitions of states, including information state and action variables. The Q-Learning approach enables us to derive an empirical state transition rules from simulation data so that analytical calculations of potentially exorbitantly complicated state transition rules can be circumvented. To maximize the advantage of using the empirically learned state transition rules, special type of actions including project cancellation and resource idling, which are difficult to incorporate into heuristics, were randomly added in the simulation. The random actions are filtered during the Q-Value iteration and properly utilized in the online decision making to maximize the total expected reward.
This paper deals with a new scheme for the prediction of a ball bearing's remaining useful life b... more This paper deals with a new scheme for the prediction of a ball bearing's remaining useful life based on self-organizing map (SOM) and back propagation neural network methods. One of the key components needed for effective bearing life prediction is the set-up of an appropriate degradation indicator from a bearing's incipient defect stage to its final failure. This new method is different from the others that have been used in the past, in that it uses the minimum quantisation error (MQE) indicator derived from SOM, which is trained by six vibration features, including a new designed degradation index for performance degradation assessment. Then, using this indicator, back propagation neural networks focusing on the degradation periods can be trained. Thanks to weight application to failure times (WAFT) technology, a useful life prediction model for ball bearings has been developed successfully. Finally, a set of accelerated bearing run-to-failure experiments is carried out, with the experimental results showing that the new proposed methods are greatly superior to those, based on L10 bearing life prediction, currently being used.
Sequential imperfect preventive maintenance policy leads to a decreasing sequence of maintenance ... more Sequential imperfect preventive maintenance policy leads to a decreasing sequence of maintenance intervals which is practical in engineering while CBPM (condition based predictive maintenance) techniques provide the assessment and prediction of the system condition based on the data collected through continuous monitoring.
De-noising and extraction of the weak signature are crucial to fault prognostics in which case fe... more De-noising and extraction of the weak signature are crucial to fault prognostics in which case features are often very weak and masked by noise. The wavelet transform has been widely used in signal de-noising due to its extraordinary time-frequency representation capability. In this paper, the performance of wavelet decomposition-based de-noising and wavelet filter-based de-noising methods are compared based on signals from mechanical defects. The comparison result reveals that wavelet filter is more suitable and reliable to detect a weak signature of mechanical impulse-like defect signals, whereas the wavelet decomposition de-noising method can achieve satisfactory results on smooth signal detection. In order to select optimal parameters for the wavelet filter, a two-step optimization process is proposed. Minimal Shannon entropy is used to optimize the Morlet wavelet shape factor. A periodicity detection method based on singular value decomposition (SVD) is used to choose the appropriate scale for the wavelet transform. The signal de-noising results from both simulated signals and experimental data are presented and both support the proposed method. r
This paper investigates the choice of function approximator for an approximate dynamic programmin... more This paper investigates the choice of function approximator for an approximate dynamic programming (ADP) based control strategy. The ADP strategy allows the user to derive an improved control policy given a simulation model and some starting control policy (or alternatively, closed-loop identification data), while circumventing the Ôcurse-of-dimensionalityÕ of the traditional dynamic programming approach. In ADP, one fits a function approximator to state vs. Ôcost-to-goÕ data and solves the Bellman equation with the approximator in an iterative manner. A proper choice and design of function approximator is critical for convergence of the iteration and the quality of final learned control policy, because an approximation error can grow quickly in the loop of optimization and function approximation. Typical classes of approximators used in related approaches are parameterized global approximators (e.g. artificial neural networks) and nonparametric local averagers (e.g. k-nearest neighbor). In this paper, we assert on the basis of some case studies and a theoretical result that a certain type of local averagers should be preferred over global approximators as the former ensures monotonic convergence of the iteration. However, a converged cost-to-go function does not necessarily lead to a stable control policy on-line due to the problem of over-extrapolation. To cope with this difficulty, we propose that a penalty term be included in the objective function in each minimization to discourage the optimizer from finding a solution in the regions of state space where the local data density is inadequately low. A nonparametric density estimator, which can be naturally combined with a local averager, is employed for this purpose.
In today's global competitive marketplace, there is intense pressure for manufacturing industries... more In today's global competitive marketplace, there is intense pressure for manufacturing industries to continuously reduce and eliminate costly, unscheduled downtime and unexpected breakdowns. With the advent of Internet and tether-free technologies, companies necessitate dramatic changes in transforming traditional ''fail and fix (FAF)'' maintenance practices to a ''predict and prevent (PAP)'' e-maintenance methodology. Emaintenance addresses the fundamental needs of predictive intelligence tools to monitor the degradation rather than detecting the faults in a networked environment and, ultimately to optimize asset utilization in the facility. This paper introduces the emerging field of e-maintenance and its critical elements. Furthermore, performance assessment and prediction tools are introduced for continuous assessment and prediction of a particular product's performance, ultimately enable proactive maintenance to prevent machine from breakdowns. Recent advances on intelligent prognostic technologies and tools are discussed. Several case studies are introduced to validate these developed technologies and tools. #
We propose two approximate dynamic programming (ADP)-based strategies for control of nonlinear pr... more We propose two approximate dynamic programming (ADP)-based strategies for control of nonlinear processes using input-output data. In the first strategy, which we term 'J -learning,' one builds an empirical nonlinear model using closed-loop test data and performs dynamic programming with it to derive an improved control policy. In the second strategy, called 'Q-learning,' one tries to learn an improved control policy in a model-less manner. Compared to the conventional model predictive control approach, the new approach offers some practical advantages in using nonlinear empirical models for process control. Besides the potential reduction in the on-line computational burden, it offers a convenient way to control the degree of model extrapolation in the calculation of optimal control moves. One major difficulty associated with using an empirical model within the multi-step predictive control setting is that the model can be excessively extrapolated into regions of the state space where identification data were scarce or nonexistent, leading to performances far worse than predicted by the model. Within the proposed ADP-based strategies, this problem is handled by imposing a penalty term designed on the basis of local data distribution. A CSTR example is provided to illustrate the proposed approaches.
Proceedings of the SIGCHI conference on Human factors in computing systems - CHI '00, 2000
We introduce HandSCAPE, an orientation-aware digital tape measure, as an input device for digitiz... more We introduce HandSCAPE, an orientation-aware digital tape measure, as an input device for digitizing field measurements, and visualizing the volume of the resulting vectors with computer graphics. Using embedded orientation-sensing hardware, HandSCAPE captures relevant vectors on each linear measurements and transmits this data wirelessly to a remote computer in real-time. To guide us in design, we have closely studied the intended users, their tasks, and the physical workplaces to extract the needs from real worlds. In this paper, we first describe the potential utility of HandSCAPE for three on-site application areas: archeological surveys, interior design, and storage space allocation. We then describe the overall system which includes orientation sensing, vector calculation, and primitive modeling. With exploratory usage results, we conclude our paper for interface design issues and future developments.
In response to the problem of adolescent smoking and limited appropriate cessation resources, thi... more In response to the problem of adolescent smoking and limited appropriate cessation resources, this study examined the pattern and structure of the American Lung Association, Why Do You Smoke? (WDS) to determine its appropriateness for use in youth smoking cessation programs. The WDS is used to help smokers identify primary motivations for using tobacco and is comprised of eight subscales, each with three items representing primary smoking motivations ("Stimulation," "Handling," "Pleasure," "Crutch," "Psychological," "Habit," "Peer," and "Independence"). Study participants were all minors enrolled in a tobacco cessation program (n = 251). The pattern and structure of this self-assessment was examined using a correlated multiple group component factor analysis as a confirmatory approach. Findings show that the level of endorsement (as evidenced by subscale means and standard deviations) was relatively larg...
Proceedings of the American Thoracic Society, 2008
Worldwide over 1 million people die due to lung cancer each year. It is estimated that cigarette ... more Worldwide over 1 million people die due to lung cancer each year. It is estimated that cigarette smoking explains almost 90% of lung cancer risk in men and 70 to 80% in women. Clinically evident lung cancers have multiple genetic and epigenetic abnormalities. These abnormalities may result in activation of oncogenes and inactivation of tumor-suppressor genes. Chronic inflammation, which is known to promote cancer, may result both from smoking and from genetic abnormalities. These mediators in turn may be responsible for increased macrophage recruitment, delayed neutrophil clearance, and increase in reactive oxygen species (ROS). Thus, the pulmonary environment presents a unique milieu in which lung carcinogenesis proceeds in complicity with the host cellular network. The pulmonary diseases that are associated with the greatest risk for lung cancer are characterized by abundant and deregulated inflammation. Pulmonary disorders such as chronic obstructive pulmonary disease (COPD)/emph...
Determining operative risk in patients undergoing aortic surgery is a difficult process, as multi... more Determining operative risk in patients undergoing aortic surgery is a difficult process, as multiple variables converge to affect overall mortality. Patient frailty is certainly a contributing factor, but is difficult to measure, with surgeons often relying on subjective or intuitive influences. We sought to use core muscle size as an objective measure of frailty, and determine its utility as a predictor of survival after abdominal aortic aneurysm (AAA) repair. Four hundred seventy-nine patients underwent elective open AAA repair between 2000 and 2008. Two hundred sixty-two patients (54.7%) had preoperative computed tomography (CT) scans available for analysis. Cross-sectional areas of the psoas muscles at the level of the L4 vertebra were measured. The covariate-adjusted effect of psoas area on postoperative mortality was assessed using Cox regression. Of the 262 patients, there were 55 deaths and the mean length of follow-up was 2.3 years. Cox regression revealed a significant ass...
Obesity is a known risk factor for surgical site infection (SSI). Our hypothesis is that morphome... more Obesity is a known risk factor for surgical site infection (SSI). Our hypothesis is that morphometric measures of midline subcutaneous fat will be associated with increased risk of SSI and will predict SSI better than conventional measures of obesity. We identified 655 patients who underwent midline laparotomy (2006 to 2009) using the Michigan Surgical Quality Collaborative database. Using novel, semiautomated analytic morphometric techniques, the thickness of subcutaneous fat along the linea alba was measured between T12 and L4. To adjust for variations in patient size, subcutaneous fat was normalized to the distance between the vertebrae and anterior skin. Logistic regression analyses were used to identify factors independently associated with the incidence of SSI. Overall, SSIs were observed in 12.5% (n = 82) of the population. Logistic regression revealed that patients with increased subcutaneous fat had significantly greater odds of developing a superficial incisional SSI (odds...
2008 International Conference on Prognostics and Health Management, 2008
This paper presents a similarity-based approach for estimating the Remaining Useful Life (RUL) in... more This paper presents a similarity-based approach for estimating the Remaining Useful Life (RUL) in prognostics. The approach is especially suitable for situations in which abundant run-to-failure data for an engineered system are available. Data from multiple units of the same system are used to create a library of degradation patterns. When estimating the RUL of a test unit, the data from it will be matched to those patterns in the library and the actual life of those matched units will be used as the basis of estimation. This approach is used to tackle the data challenge problem defined by the 2008 PHM Data Challenge Competition, in which, run-to-failure data of an unspecified engineered system are provided and the RUL of a set of test units will be estimated. Results show that the similarity-based approach is very effective in performing RUL estimation.
Parents represent a key ecological component in influencing their child's physical activity. ... more Parents represent a key ecological component in influencing their child's physical activity. The aim of this exploratory study was to assess the relationship between maternal acculturation and physical activity in Hispanic children. 102 Hispanic mothers (mean age 36.2 yrs; +SD 7.3 yrs) and their children (mean age 10.0 yrs, +SD 0.8 yrs) participated. Most of the mothers (74%) were foreign-born, with 62% classified as low acculturated and 38% high acculturated. Demographic, acculturation, and anthropometric measures were completed by mothers and children. Physical activity was measured using accelerometers. Relationships between maternal acculturation and demographic variables and children's physical activity were examined using chi-square, Analysis of Variance, and simple regression. Children had higher physical activity levels than their mothers (t(49) = -7.87, P < .0001). Significant correlations between maternal and child's physical activity levels were observed in...
... Feibai Zhu Mohamed AbuAli Jay Lee NSF I/UCRC Center for Intelligent Maintenance Systems (IMS)... more ... Feibai Zhu Mohamed AbuAli Jay Lee NSF I/UCRC Center for Intelligent Maintenance Systems (IMS) College of ... Figure 9. Testbed and DAQ Setup [5] ... References: 1. Lee, J., et al., A systematic approach for predictive maintenance service design: methodology and applications. ...
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