Rapid Identification of Virtual CNC Drives

Virtual manufacturing has gained considerable importance in the last decade. To obtain reliable predictions in a virtual environment, the factors that influence the outcome of a manufacturing operation need to be carefully modeled and integrated in a simulation platform. The dynamic behavior of the Computer Numerical Control (CNC) system, which has a profound influence on the final part geometry and tolerance integrity, is among these factors. Classical CNC drive identification techniques are usually time consuming and need to be performed by an engineer qualified in dynamics and control theory. These techniques require the servo loop or the trajectory interpolator to be disconnected in order to inject the necessary identification signals, causing downtime to the machine. Hence, these techniques are usually not practical for constructing virtual models of existing CNC machine tools in a manufacturing environment. This thesis presents an alternative strategy for constructing virtual drive models with minimal intervention and downtime to the machinery. The proposed technique, named “rapid identification”, consists of executing a short G-code experiment and collecting input/output data using the motion capture feature available on most CNC controllers. The data is then processed to reverse engineer the equivalent tracking and disturbance transfer functions and friction characteristics of the machine. It is shown that virtual drive models constructed this way can be used to predict the real machine’s contouring performance for large class of drive systems, controlled with different control techniques. In the proposed scheme, the excitation is delivered by smoothly interpolated motion commands. Hence, convergence of parameters to their true values is not guaranteed. When the real system contains pole-zero cancellations, namely due to feedforward control action, this also results in a loss of identifiability. In order to guarantee the stability of the identified drive models, the pole locations are constrained with frequency and damping ratio limits. Hence, the rapid identification task is cast as a constrained minimization problem. Two solution strategies have been developed. In the first approach, Lagrange Multipliers (LM) technique is applied, which yields successful estimation results. However, implementation of LM is computationally intensive and requires the use of a dedicated symbolic solver. This limits the portability for industrial implementation. In the second approach, a Genetic Algorithm (GA) search technique is developed, which is a more practical but slightly approximate alternative. The GA allows parameter bounds to be incorporated in a natural manner and converges to 2-3% vicinity of the LM solution in one-tenth of the computation time. The GA solution can be easily ported to different computation platforms. Both LM and GA identification techniques were validated in simulations and experiments conducted on virtual and real machine tool drives. It is shown that although the parameters estimated using the rapid identification scheme do not always match their true values, the key tracking and disturbance rejection characteristics of the drives are successfully captured in the frequency range of the CNC motion commands. Therefore, the drive models constructed with rapid identification can be used to predict the contouring accuracy of real machine tools in a virtual process planning environment. This thesis presents an alternative strategy for constructing virtual drive models with minimal intervention and downtime to the machinery. The proposed technique, named “rapid identification”, consists of executing a short G-code experiment and collecting input/output data using the motion capture feature available on most CNC controllers. The data is then processed to reverse engineer the equivalent tracking and disturbance transfer functions and friction characteristics of the machine. It is shown that virtual drive models constructed this way can be used to predict the real machine’s contouring performance for large class of drive systems, controlled with different control techniques. In the proposed scheme, the excitation is delivered by smoothly interpolated motion commands. Hence, convergence of parameters to their true values is not guaranteed. When the real system contains pole-zero cancellations, namely due to feedforward control action, this also results in a loss of identifiability. In order to guarantee the stability of the identified drive models, the pole locations are constrained with frequency and damping ratio limits. Hence, the rapid identification task is cast as a constrained minimization problem. Two solution strategies have been developed. In the first approach, Lagrange Multipliers (LM) technique is applied, which yields successful estimation results. However, implementation of LM is computationally intensive and requires the use of a dedicated symbolic solver. This limits the portability for industrial implementation. In the second approach, a Genetic Algorithm (GA) search technique is developed, which is a more practical but slightly approximate alternative. The GA allows parameter bounds to be incorporated in a natural manner and converges to 2-3% vicinity of the LM solution in one-tenth of the computation time. The GA solution can be easily ported to different computation platforms. Both LM and GA identification techniques were validated in simulations and experiments conducted on virtual and real machine tool drives. It is shown that although the parameters estimated using the rapid identification scheme do not always match their true values, the key tracking and disturbance rejection characteristics of the drives are successfully captured in the frequency range of the CNC motion commands. Therefore, the drive models constructed with rapid identification can be used to predict the contouring accuracy of real machine tools in a virtual process planning environment

A study of the structure and performance of the real estate development industry in Hong Kong

Includes bibliographical references (p. 105-110).Thesis (B.Sc)--University of Hong Kong, 2008.published_or_final_versio

Can the Testing Effect for General Knowledge Facts Be Influenced by Distraction due to Divided Attention or Experimentally Induced Anxious Mood?

Studies on testing effect have showed that a practice test on study materials leads to better performance in a final test than restudying the materials for the same amount of time. Two experiments were conducted to test how distraction, as triggered by divided attention or experimentally induced anxious mood in the practice phase, could modulate the benefit of testing (vs. restudying) on the learning of interesting and boring general knowledge facts. Two individual difference factors (trait test anxiety and working memory (WM) capacity) were measured. Under divided attention, participants restudied or recalled the missing information in visually presented general knowledge facts, while judging whether auditorily presented items were from a pre-specified category. To experimentally induce anxious mood, we instructed participants to view and interpret negative pictures with anxious music background before and during the practice phase. Immediate and two-day delayed tests were given. Regardless of item type (interesting or boring) or retention interval, the testing effect was not significantly affected by divided (vs. full) attention or anxious (vs. neutral) mood. These results remained unchanged after taking into account the influences of participants’ trait test anxiety and WM capacity. However, when analyses were restricted to the study materials that had been learnt in the divided attention condition while participants accurately responded to the concurrent distracting task, the testing effect was stronger in the divided attention condition than in the full attention condition. Contrary to previous studies (e.g., Tse and Pu, 2012), there was no WM capacity × trait test anxiety interaction in the overall testing effect. Theoretical and practical implications of these findings are discussed

Validation of a Novel Traditional Chinese Medicine Pulse Diagnostic Model Using an Artificial Neural Network

In view of lacking a quantifiable traditional Chinese medicine (TCM) pulse diagnostic model, a novel TCM pulse diagnostic model was introduced to quantify the pulse diagnosis. Content validation was performed with a panel of TCM doctors. Criterion validation was tested with essential hypertension. The gold standard was brachial blood pressure measured by a sphygmomanometer. Two hundred and sixty subjects were recruited (139 in the normotensive group and 121 in the hypertensive group). A TCM doctor palpated pulses at left and right cun, guan, and chi points, and quantified pulse qualities according to eight elements (depth, rate, regularity, width, length, smoothness, stiffness, and strength) on a visual analog scale. An artificial neural network was used to develop a pulse diagnostic model differentiating essential hypertension from normotension. Accuracy, specificity, and sensitivity were compared among various diagnostic models. About 80% accuracy was attained among all models. Their specificity and sensitivity varied, ranging from 70% to nearly 90%. It suggested that the novel TCM pulse diagnostic model was valid in terms of its content and diagnostic ability

Association between antibiotic consumption and colon and rectal cancer development in older individuals: A territory‐wide study

Background: Antibiotics may alter colorectal cancer (CRC) risk due to gut dysbiosis. We aimed to study the specific and temporal effects of various antibiotics on CRC development in older individuals. Methods: This was a territory-wide retrospective cohort study. Subjects aged 60 years and older who did not have CRC diagnosed on screening/diagnostic colonoscopy diagnosed between 2005 and 2013 were recruited. Exclusion criteria were history of CRC, colectomy, inflammatory bowel disease, and CRC diagnosed within 6 months of index colonoscopy. Exposure was use of any antibiotics up to 5 years before colonoscopy. The primary outcomes were CRC diagnosed >6 m after colonoscopy. Covariates were patient demographics, history of colonic polyps/polypectomy, concomitant medication use (NSAIDs, COX-2 inhibitors, aspirin, and statins), and performance of endoscopy centers (colonoscopy volume and polypectomy rate). Stratified analysis was conducted according to nature of antibiotics and location of cancer. Results: Ninety seven thousand one hundred and sixty-two eligible subjects (with 1026 [1.0%] cases of CRC) were identified, 58,704 (60.4%) of whom were exposed to antibiotics before index colonoscopy. Use of antibiotics was associated with a lower risk of cancer in rectum (adjusted hazard ratio [aHR]: 0.64, 95% CI: 0.54–0.76), but a higher risk of cancer in proximal colon (aHR: 1.63, 95%CI: 1.15–2.32). These effects differed as regards the anti-anaerobic/anti-aerobic activity, narrow-/broad-spectrum, and administration route of antibiotics. Conclusions: Antibiotics had divergent effects on CRC development in older subjects, which varied according to the location of cancer, antibiotic class, and administration route

Metformin Use and Gastric Cancer Risk in Diabetic Patients After Helicobacter pylori Eradication.

BACKGROUND: Although prior studies showed metformin could reduce gastric cancer (GC) risk in patients with diabetes mellitus, they failed to adjust for Helicobacter pylori infection and glycemic control. We aimed to investigate whether metformin reduced GC risk in H. pylori-eradicated diabetic patients and its association with glycemic control. METHODS: This was a territory-wide cohort study using hospital registry database, recruiting all diabetic patients who were prescribed clarithromycin-based triple therapy for H. pylori infection from 2003 to 2012. Subjects were observed from H. pylori therapy prescription until GC diagnosis, death, or end of study (December 2015). Exclusion criteria included GC diagnosed within first year of H. pylori therapy, prior history of GC or gastrectomy, and failure of H. pylori eradication. The hazard ratio (HR) of GC with metformin (defined as at least 180-day use) was estimated by Cox model with propensity score adjustment for covariates (age, sex, comorbidities, medications [including insulin], and time-weighted average hemoglobin A1c [HbA1c]). All statistical tests were two-sided. RESULTS: During a median follow-up of 7.1 years (IQR = 4.7-9.8), 37 (0.51%) of 7266 diabetic patients developed GC at a median age of 76.4 years (IQR = 64.8-81.5 years). Metformin use was associated with a reduced GC risk (adjusted HR = 0.49, 95% CI = 0.24 to 0.98). There was a trend towards a lower GC risk with increasing duration (Ptrend = .01) and dose of metformin (Ptrend = .02). HbA1c level was not an independent risk factor for GC. CONCLUSIONS: Metformin use was associated with a lower GC risk among H. pylori-eradicated diabetic patients in a duration- and dose-response manner, which was independent of HbA1c level

Statins Were Associated with a Reduced Gastric Cancer Risk in Patients with Eradicated Helicobacter Pylori Infection: A Territory-Wide Propensity Score Matched Study.

BACKGROUND: Individuals may still develop gastric cancer even after Helicobacter pylori eradication. We aimed to investigate statin effect on gastric cancer development in H. pylori-eradicated subjects. METHODS: All adult subjects who were prescribed clarithromycin-based triple therapy between 2003 and 2012 were identified in this retrospective cohort study utilizing a territory-wide electronic healthcare database. Patients were observed from index date of H. pylori therapy, and censored at gastric cancer diagnosis, death, or December 2015 (study end date). Statin use was defined as ≥180-day use after index date. Exclusion criteria included gastric cancer diagnosed within the first year after index date, previous gastric cancer or gastrectomy, and H. pylori treatment failure. Subdistribution hazard ratio (SHR) of gastric cancer with statins was calculated by competing risk regression with propensity score (PS) analysis matching 19 variables (age, sex, comorbidities, and other drug usage, including proton pump inhibitors, nonsteroidal anti-inflammatory drugs, aspirin, cyclooxygenase-2 inhibitors, and metformin). RESULTS: During a median follow-up of 7.6 years (interquartile range = 5.1-10.3), 169 (0.27%) of 63,605 patients developed gastric cancer at an incidence rate of 3.5 per 10,000 person-years. Among 22,870 PS-matched subjects, statins were associated with a lower gastric cancer risk (SHR = 0.34; 95% confidence interval, 0.19-0.61), in a duration- and dose-response manner (P trend < 0.05). CONCLUSIONS: Statins were associated with a lower gastric cancer risk in a duration- and dose-response manner among H. pylori-eradicated patients. IMPACT: This study provides evidence on the additional benefits of statins as chemopreventive agents against gastric cancer among H. pylori-eradicated patients

Long-term proton pump inhibitors and risk of gastric cancer development after treatment for Helicobacter pylori: a population-based study.

OBJECTIVE: Proton pump inhibitors (PPIs) is associated with worsening of gastric atrophy, particularly in Helicobacter pylori (HP)-infected subjects. We determined the association between PPIs use and gastric cancer (GC) among HP-infected subjects who had received HP therapy. DESIGNS: This study was based on a territory-wide health database of Hong Kong. We identified adults who had received an outpatient prescription of clarithromycin-based triple therapy between year 2003 and 2012. Patients who failed this regimen, and those diagnosed to have GC within 12 months after HP therapy, or gastric ulcer after therapy were excluded. Prescriptions of PPIs or histamine-2 receptor antagonists (H2RA) started within 6 months before GC were excluded to avoid protopathic bias. We evaluated GC risk with PPIs by Cox proportional hazards model with propensity score adjustment. H2RA was used as a negative control exposure. RESULT: Among the 63 397 eligible subjects, 153 (0.24%) developed GC during a median follow-up of 7.6 years. PPIs use was associated with an increased GC risk (HR 2.44, 95% CI 1.42 to 4.20), while H2RA was not (HR 0.72, 95% CI 0.48 to 1.07). The risk increased with duration of PPIs use (HR 5.04, 95% CI 1.23 to 20.61; 6.65, 95% CI 1.62 to 27.26 and 8.34, 95% CI 2.02 to 34.41 for ≥1 year, ≥2 years and ≥3 years, respectively). The adjusted absolute risk difference for PPIs versus non-PPIs use was 4.29 excess GC (95% CI 1.25 to 9.54) per 10 000 person-years. CONCLUSION: Long-term use of PPIs was still associated with an increased GC risk in subjects even after HP eradication therapy

Misdiagnosis of pulmonary embolism and missed pulmonary embolism: A systematic review of the literature

Pulmonary embolism (PE) is a common and life-threatening condition. Misdiagnosis of PE is not uncommon as symptoms can overlap with other diagnoses and could cause potential harm. We conducted a systematic review to estimate rates of misdiagnosis and factors may be associated with misdiagnosis of PE. We searched MEDLINE and EMBASE for studies that evaluated the misdiagnosis of PE. The rate of misdiagnosis was pooled and results were narratively synthesized. A total of 18 studies were included which included 2,053 patients with a diagnosis of PE. Two different definitions were used for misdiagnosis of PE. The first refers to an initial diagnosis that is not PE and the patient is found to have PE. The second definition refers to patients who do not have a diagnosis of PE while they were alive and PE was subsequently found on autopsy. The pooled results across the studies suggest that in ED settings 27.5% of patients with PE are misdiagnosed initially and half of all patients in inpatient settings are misdiagnosed (53.6%). Among patients that die in intensive care who undergo autopsy 37.9% were found to have PE that was missed. The commonly diagnosed conditions instead of PE were respiratory infection, heart failure and acute coronary syndrome (ACS). Misdiagnosis in patients with an eventual diagnosis of PE is common. Clinicians should consider PE as differential diagnosis in patients who are initially suspected to have chest infection, heart failure or ACS who have negative diagnostic tests or poor response to treatment