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Hypertension in childhood and adolescence is associated with adult cardiovascular morbidity and mortality. However, the reported prevalence of pediatric hypertension varies considerably. We conducted a pioneer nationwide population-based study to investigate the prevalence of hypertension among children and adolescents. Pediatric patients who had been diagnosed with hypertension between 2000 and 2013 were selected from the National Health Insurance Research Database in Taiwan. Other metabolic syndrome-related diseases that would increase cardiovascular risk, including diabetes mellitus (DM), hyperlipidemia, and obesity, were also retrieved for further evaluation. In total, 10,364 children and adolescents diagnosed with hypertension were identified. The prevalence of pediatric hypertension in Taiwan ranged from 0.19 to 0.38 per 1000 children and adolescents between 2000 and 2013. Essential hypertension was most commonly coded (90.6%), which was much more than secondary hypertension (14.3%). Children and adolescents with hypertension were often associated with DM, hyperlipidemia, and obesity, with the odds ratios as 14.05 (95% confidence interval (CI) 11.74–16.81, p

Nonvalvular atrial fibrillation (NVAF) and carotid stenosis are important risk factors for stroke. Carotid angioplasty and stent placement (CAS) is recommended for patients with symptomatic high-grade carotid stenosis. The optimal medical management for patients with NVAF after CAS remains unclear. We aimed to clarify this issue using real-world data from the Taiwanese National Health Insurance Research Database (NHIRD). In total, 2116 consecutive NVAF patients who received CAS between January 1, 2010, and December 31, 2016, from NHIRD were divided into groups based on post-procedure medication as follows: only antiplatelet agent (OAP, n = 587); only anticoagulation agent (OAC, n = 477); dual antiplatelet agents (DAP, n = 49); and a combination of antiplatelet and anticoagulation agents (CAPAC, n = 304). Mortality, vascular events, and major bleeding episodes were compared after matching with the Charlson comorbidity index and CHA2DS2-VASc score. The CAPAC and the OAC groups had lower mortality rates than the OAP group (P = 0.0219), with no statistical differences in major bleeding, ischemic stroke, or vascular events. Conclusively, OAC therapy after CAS appears suitable for NVAF patients. CAPAC therapy might be considered as initial therapy or when there is concern about vascular events.

Background: Low-dose aspirin (100 mg) is widely used in preventing cardiovascular disease in chronic kidney disease (CKD) because its benefits outweighs the harm, however, its effect on clinical outcomes in patients with predialysis advanced CKD is still unclear. This study aimed to assess the effect of aspirin use on clinical outcomes in such group. Methods: Patients were selected from a nationwide diabetes database from January 2009 to June 2017, and divided into two groups, a case group with aspirin use (n = 3021) and a control group without aspirin use (n = 9063), by propensity score matching with a 1:3 ratio. The Cox regression model was used to estimate the hazard ratio (HR). Moreover, machine learning method feature selection was used to assess the importance of parameters in the clinical outcomes. Results: In a mean follow-up of 1.54 years, aspirin use was associated with higher risk for entering dialysis (HR, 1.15 [95%CI, 1.10–1.21]) and death before entering dialysis (1.46 [1.25–1.71]), which were also supported by feature selection. The renal effect of aspirin use was consistent across patient subgroups. Nonusers and aspirin users did not show a significant difference, except for gastrointestinal bleeding (1.05 [0.96–1.15]), intracranial hemorrhage events (1.23 [0.98–1.55]), or ischemic stroke (1.15 [0.98–1.55]). Conclusions: Patients with predialysis advanced CKD and anemia who received aspirin exhibited higher risk of entering dialysis and death before entering dialysis by 15% and 46%, respectively.

Most patients face expensive healthcare management after coronary artery bypass grafting (CABG) surgery, which brings a substantial financial burden to the government. The National Health Insurance Research Database (NHIRD) is a complete database containing over 99% of individuals’ medical information in Taiwan. Our research used the latest data that selected patients who accepted their first CABG surgery between January 2014 and December 2017 (n = 12,945) to predict which factors will affect medical expenses, and built the prediction model using different machine learning algorithms. After analysis, our result showed that the surgical expenditure (X4) and 1-year medical expenditure before the CABG operation (X14), and the number of hemodialysis (X15), were the key factors affecting the 1-year medical expenses of CABG patients after discharge. Furthermore, the XGBoost and SVR methods are both the best predictive models. Thus, our research suggests enhancing the healthcare management for patients with kidney-related diseases to avoid costly complications. We provide helpful information for medical management, which may decrease health insurance burdens in the future.

Research has failed to resolve the dilemma experienced by localized prostate cancer patients who must choose between radical prostatectomy (RP) and external beam radiotherapy (RT). Because the Charlson Comorbidity Index (CCI) is a measurable factor that affects survival events, this research seeks to validate the potential of the CCI to improve the accuracy of various prediction models. Thus, we employed the Cox proportional hazard model and machine learning methods, including random forest (RF) and support vector machine (SVM), to model the data of medical records in the National Health Insurance Research Database (NHIRD). In total, 8581 individuals were enrolled, of whom 4879 had received RP and 3702 had received RT. Patients in the RT group were older and exhibited higher CCI scores and higher incidences of some CCI items. Moderate-to-severe liver disease, dementia, congestive heart failure, chronic pulmonary disease, and cerebrovascular disease all increase the risk of overall death in the Cox hazard model. The CCI-reinforced SVM and RF models are 85.18% and 81.76% accurate, respectively, whereas the SVM and RF models without the use of the CCI are relatively less accurate, at 75.81% and 74.83%, respectively. Therefore, CCI and some of its items are useful predictors of overall and prostate-cancer-specific survival and could constitute valuable features for machine-learning modeling.

Secondary hormone therapy, abiraterone and enzalutamide, has improved outcomes for metastatic castration-resistant prostate cancer (mCRPC) and prolonged patients’ lives significantly. Various studies have compared the cancer-related outcomes, adverse effects, and drug-induced comorbidities in patients with mCRPC who are treated with abiraterone or enzalutamide. However, few studies have explored associations between survival and comorbidities or comprehensive analyzed newly developed comorbidities during and after secondary hormone therapy. We attempted to clarify whether the Charlson comorbidity index (CCI) overall or itemized is predictive for overall survival, and we compared newly developed comorbidities between abiraterone and enzalutamide groups. We extracted data about expenses and comorbidities for patients who have mCRPC, received abiraterone and enzalutamide and met pre-examination operation criteria between September 2016 and December 2017 from the Taiwan National Health Insurance database. A total of 1153 patients with mCRPC who received abiraterone (n = 782) or enzalutamide (n = 371) with or without previous chemotherapy were included. We used the propensity score to match confounding factors, including age, pre-existing comorbidities, and precipitating factors for comorbidity (e.g., hypertension, hyperlipidemia), to eliminate selection bias in the comparison of newly developed comorbidities. Cox regression analysis was used for overall survival. We found that enzalutamide is superior to abiraterone with regard to overall survival. Our study revealed that there is no statistically significant difference in development of new comorbidities between abiraterone and enzalutamide group. Moreover, the CCI score, rather than any single item of the CCI, was a statistically significant predictor for overall survival.

Coronary artery bypass surgery grafting (CABG) is a commonly efficient treatment for coronary artery disease patients. Even if we know the underlying disease, and advancing age is related to survival, there is no research using the one year before surgery and operation-associated factors as predicting elements. This research used different machine-learning methods to select the features and predict older adults’ survival (more than 65 years old). This nationwide population-based cohort study used the National Health Insurance Research Database (NHIRD), the largest and most complete dataset in Taiwan. We extracted the data of older patients who had received their first CABG surgery criteria between January 2008 and December 2009 (n = 3728), and we used five different machine-learning methods to select the features and predict survival rates. The results show that, without variable selection, XGBoost had the best predictive ability. Upon selecting XGBoost and adding the CHA2DS score, acute pancreatitis, and acute kidney failure for further predictive analysis, MARS had the best prediction performance, and it only needed 10 variables. This study’s advantages are that it is innovative and useful for clinical decision making, and machine learning could achieve better prediction with fewer variables. If we could predict patients’ survival risk before a CABG operation, early prevention and disease management would be possible.

The health effects associated with fine particulate matter (PM2.5) have attracted considerable public attention in recent decades. It has been verified that PM2.5 can damage the respiratory and cardiovascular systems and cause various diseases. While the association between diseases and PM2.5 has been widely studied, this work aims to analyze the association between PM2.5 and hospital visit rates for respiratory diseases in Taiwan. To this end, a disease mapping model that considers spatial effects is applied to estimate the association. The results show that there is a positive association between hospital visit rates and the PM2.5 concentrations in the Taiwanese population in 2012 after controlling for other variables, such as smoking rates and the number of hospitals in each region. This finding indicates that control of PM2.5 could decrease hospital visit rates for respiratory diseases in Taiwan.

Due to the impact of globalization, the competition between enterprises has become fierce and led the supply chains of many industries to be reorganized. One of the consequences is that the operation of many small and medium enterprises (SMs) had become very difficult. Hence, many of SMEs in Taiwan have gone bankrupt and some of them have moved to other places where they have lower production costs, in order to survive, this not only hollowed out the industries but also disconnected the supply chains in their mother countries. Because Taiwan’s SMEs are generally poor in innovation, this study explored the implementation of the theory of inventive problem-solving (TRIZ) with alignment of new product development (NPD) and supply chain management (SCM) to strengthen the innovation and productivity of new products, so that SMEs can refer to its use to aid sustainable business operation. We considered an SME in Taiwan as a case to study and investigate the strategies that it employed to achieve survival and sustainability. By examining the practical applications of the NPD of the case company, which was based on the TRIZ and NPD SCM alignment, we found that value-added products may be created despite unfavorable industry environments, by implementing and coordinating the TRIZ and three product-related variables, namely innovating, modularity, and variety. This study explored practical alternatives for SMEs to develop various value-added products that meet customers’ changing requirements and succeed in competitive markets to achieve a sustainable business operation. Considering SMEs are crucially important to the economic equality and development of countries and that SMEs may only survive for a short time when operating in changing supply chain environments, this study can be used as a reference for the management of SMEs and future academic research in related fields.

Background The relationship between sleep duration and physical fitness is one aspect of sleep health. Potential factors associated with sleep duration interfere with physical fitness performance, but the impact trends on physical fitness indicators remain unclear. Methods This study examined associations between sleep duration and physical fitness among young to middle-aged adults in Taiwan. A total of 42,781 Taiwanese adults aged 23–45 participated in the National Physical Fitness Examination Survey 2013 (NPFES-2013) in Taiwan between October 2013 and March 2014. A standardized structural questionnaire was used to record participants’ sleep duration, which was stratified as short ( Results By using analysis of covariance (ANCOVA), after sex grouping and age adjustment, we observed that sleep duration was significantly associated with obesity, functional fitness, and self-perception of health. The sleep duration for low obesity-related values (BMI, WHtR, and WHR) for men was 7–9 h/d, and that for women was 7–8 h/d. Sleeping more than 8 h/d showed poor functional fitness performances (BS and SR). For both sexes, sleep duration of 8–9 h/d was the optimal sleep duration for self-perceptions of health. Conclusions Our research found that there were wide and different associations of sleep duration with physical fitness and self-perception of health among Taiwanese adults aged 23–45, and there were differences in these associated manifestations between men and women. This study could be of great importance in regional public health management in Taiwan, and provide inspirations for clinical research on physical fitness.

The safety and health of homeless people are important social issues. Metabolic syndrome (MetS) is a sub-health-risk phenomenon that has been severely aggravated worldwide in recent years. The purpose of this study was to investigate the prevalence and risk factors of MetS among the homeless in Taipei City, Taiwan. In this study, a convenience sampling was conducted at homeless counseling agencies in Taipei City from April 2018 to September 2018. A total of 297 homeless participants were recruited, from whom clinical indicators and questionnaire information were collected. Through statistical verification, analysis of variance (ANOVA), and logistic regression, we found the following main conclusions for homeless adults in Taipei: (1) The prevalence of MetS was estimated to be 53%, with 50% meeting four or more diagnostic conditions. (2) Dyslipidemia (high-density lipoprotein (HDL) deficiency and elevated triglyceride (TG)) showed the strongest association with the prevalence of MetS, more than 83% of people with HDL deficiency or hypertriglyceridemia had MetS. For the patient groups meeting more MetS diagnostic conditions, the values of high-density lipoprotein cholesterol (HDL-C), TG, and total cholesterol (TC) increased significantly. (3) The deterioration of MetS was significantly related to the high prevalence of hyperlipidemia (HL). (4) The homeless who were divorced, separated or widowed were more likely to suffer from MetS.

We evaluated the risk of dementia in patients with nasopharyngeal cancer (NPC) after undergoing radiation therapy (RT).Between January 1, 2000, and December 31, 2015, 594 patients newly diagnosed with NPC and treated with RT (NPC cohort) were identified from the Longitudinal Health Insurance Database (LHID) for this nationwide population-based matched cohort study. LHID is a subset of the National Health Insurance Research Database of Taiwan. We selected 2376 controls (non-NPC comparison cohort) using a four-fold propensity score-matched by sex, age, comorbidities, education level, tobacco abuse, and index date (the date when the patient received first RT). After adjusting for confounding factors, Fine and Gray's competing risk analysis compared dementia development between the NPC study cohort and non-NPC comparison cohort over the observation period from 2000 to 2015.Dementia development was 6.57% (39 of 594) and 4.42% (105 of 2376) in the NPC study cohort and non-NPC comparison cohort, respectively. Patients with NPC receiving RT were more likely to develop dementia than the comparison cohort, with a crude hazard ratio (HR) of 1.63 [95% confidence interval (CI) = 1.25-2.13, P 0.001]. After adjusting for age, sex, education level, tobacco abuse, comorbidity, geographic area, urbanization level of the residence, and care level, the adjusted HR was 1.91 (95% CI = 1.42-2.51, P 0.001).Patients with NPC receiving RT had a 1.91-fold higher risk of dementia than the non-NPC comparison controls.

Background: Although a shared decision-making (SDM) process integrates patient values and evidence-based medicine, patients’ anxiety and decision conflicts remain. Thus, we propose a new decision-making model integrating a machine-learning algorithm to investigate its feasibility for reducing anxiety, decision conflicts, and increasing satisfaction after making a decision.Methods: We enrolled participants willing to undergo the SDM process for a prostate-specific antigen (PSA) blood test and obtained data including age, PSA knowledge, if they have a friend with prostate cancer, perceptive risk of prostate cancer, International Prostate Symptom Score and Importance for Physiological and Psychological Impact in PSA Testing scores, personal values, and their final decisions, including “Accept” PSA blood test or “Not now,” to build the dataset for training the following machine-learning models: multilayer perceptron neural network, random forest (RF), extreme gradient boosting, support vector machine, and deep learning neural network. Uniform parameter tuning and model comparison were implemented. The best model was used for a randomized controlled trial (RCT), in which we measured the effects of personalized suggestions generated by the machine-learning model on anxiety, decision satisfaction, and decision conflicts.Results: RF was the best algorithm for building models with our dataset from 507 subjects (mean AUC: 0.8801, mean ACC: 0.8313, Max ACC: 0.8933). Therefore, we used the RF model for RCT with 185 and 182 subjects in the machine-learning suggestion group (MLSG) and control group (CG), respectively. The MLSG patients were calmer, more content, and less worrisome than those in the CG. They also experienced higher decision satisfaction and less decision conflict, including more decision support, advice, assurance of decision, ease of decision-making, and adherence to decision. Moreover, participants who were suggested “Accept” by the model were more likely to make “Accept” their final decision than the CG participants (50.75% vs 24.18%, χ2 = 16.07, p < 0.000). The “Not now” suggestion followed a similar trend.Conclusions: A highly accurate machine-learning model was constructed using our methods. Personalized suggestions generated from this model yielded increased satisfaction and reduced anxiety and decision conflict. Patients tended to take machine-learning suggestions as their final decision.Trial name: Shared Decision Making: Decision Tree and Artificial Neural Network Assisted Decision Aid for PSA ScreeningTrial registration: ChiCTR, ChiCTR2000034126. Registered 25 June 2020 – Retrospectively registered, http://www.chictr.org.cn/ChiCTR2000034126

Background and purpose Pattern differentiation is a critical element of the prescription process for Traditional Chinese Medicine (TCM) practitioners. Application of advanced machine learning techniques will enhance the effectiveness of TCM in clinical practice. The aim of this study is to explore the relationships between clinical features and TCM patterns in breast cancer patients. Methods The dataset of breast cancer patients receiving TCM treatment was recruited from a single medical center. We utilized a neural network model to standardize terminologies and address TCM pattern differentiation in breast cancer cases. Cluster analysis was applied to classify the clinical features in the breast cancer patient dataset. To evaluate the performance of the proposed method, we further compared the TCM patterns to therapeutic principles of Chinese herbal medication in Taiwan. Results A total of 2,738 breast cancer cases were recruited and standardized. They were divided into 5 groups according to clinical features via cluster analysis. The pattern differentiation model revealed that liver-gallbladder dampness-heat was the primary TCM pattern identified in patients. The main therapeutic goals of the top 10 Chinese herbal medicines prescribed for breast cancer patients were to clear heat, drain dampness, and detoxify. These results demonstrated that the neural network successfully identified patterns from a dataset similar to the prescriptions of TCM clinical practitioners. Conclusion This is the first study using machine-learning methodology to standardize and analyze TCM electronic medical records. The patterns revealed by the analyses were highly correlated with the therapeutic principles of TCM practitioners. Machine learning technology could assist TCM practitioners to comprehensively differentiate patterns and identify effective Chinese herbal medicine treatments in clinical practice.

Predicting the number of new suspected or confirmed cases of novel coronavirus disease 2019 (COVID-19) is crucial in the prevention and control of the COVID-19 outbreak. Social media search indexes (SMSI) for dry cough, fever, chest distress, coronavirus, and pneumonia were collected from 31 December 2019 to 9 February 2020. The new suspected cases of COVID-19 data were collected from 20 January 2020 to 9 February 2020. We used the lagged series of SMSI to predict new suspected COVID-19 case numbers during this period. To avoid overfitting, five methods, namely subset selection, forward selection, lasso regression, ridge regression, and elastic net, were used to estimate coefficients. We selected the optimal method to predict new suspected COVID-19 case numbers from 20 January 2020 to 9 February 2020. We further validated the optimal method for new confirmed cases of COVID-19 from 31 December 2019 to 17 February 2020. The new suspected COVID-19 case numbers correlated significantly with the lagged series of SMSI. SMSI could be detected 6&ndash, 9 days earlier than new suspected cases of COVID-19. The optimal method was the subset selection method, which had the lowest estimation error and a moderate number of predictors. The subset selection method also significantly correlated with the new confirmed COVID-19 cases after validation. SMSI findings on lag day 10 were significantly correlated with new confirmed COVID-19 cases. SMSI could be a significant predictor of the number of COVID-19 infections. SMSI could be an effective early predictor, which would enable governments&rsquo, health departments to locate potential and high-risk outbreak areas.

Accumulating evidence has shown a significant correlation between periodontal diseases and systemic diseases. In this study, we investigated the association between the frequency of tooth scaling and acute myocardial infarction (AMI). Here, a group of 7164 participants who underwent tooth scaling was compared with another group of 7164 participants without tooth scaling through propensity score matching to assess AMI risk by Cox’s proportional hazard regression. The results show that the hazard ratio of AMI from the tooth scaling group was 0.543 (0.441, 0.670) and the average expenses of AMI in the follow up period was USD 265.76, while the average expenses of AMI in follow up period for control group was USD 292.47. The tooth scaling group was further divided into two subgroups, namely A and B, to check the influence of tooth scaling frequency on AMI risk. We observed that (1) the incidence rate of AMI in the group without any tooth scaling was 3.5%, which is significantly higher than the incidence of 1.9% in the group with tooth scaling, (2) the tooth scaling group had lower total medical expenditures than those of the other group because of the high medical expenditure associated with AMI, and (3) participants who underwent tooth scaling had a lower AMI risk than those who never underwent tooth scaling had. Therefore, the results of this study demonstrate the importance of preventive medicine.

This research develops a new performance indicator for material flow effectiveness in production systems. The so-called flow value can represent the smoothness of material flow in a production system, thus can be used as real time indicator to instantly reveal the performance of a production system. A simulation study on a machining equipment manufacturing company in Taiwan validates the usefulness of using flow value as an indicator of material flow performance. This flow value is also capable of revealing areas where improvement can be made to effectively improve total system's performance in terms of material flow.

We studied the effects of physical fitness performance on happiness in Taiwanese adults. Through the MARS model, we analyzed the impact factors and found that age, smoking, sleep duration, performance of athletic ability and sedentary lifestyle significantly affected happiness

Prostate cancer is a common cancer treated with multi-modality. The combinations of modalities are numerous and complex. Clinical practice guidelines and rules have already been proven in many studies. However, the hypotheses of these studies came from physicians' and experts' experiences and observation. Association analysis, as an importance component of data mining, has been proved to be helpful for us to discover rules from big medical databases. We believe association analysis is able to help us to discover new rules between comorbidities and modalities in subjects of prostate cancer, so that employed it to analyze prostate cancer dataset derived from million people file of NHIRD. We successfully found six rules and rule 1,2,3,5,6 could be well explained with known knowledge and literatures, which were "Young prostate cancer patient who were spared from definite treatment tend to be spared from HT.", "TRUS is associated with younger age group, while TURP is associated with older Age.", "RT is associated with HT.", "CT is highly associated with RT.", "Hemiplegia, cerebrovascular disease, moderate to severe renal disease, diabetes with end organ damage is associated with TURP. Patients with TURP are associated with more comorbidity." We also discovered rule 4: "Younger patients who received HT is highly associated with previous RP.", which are still hypothesis and deserve our validation.

The global innovation of information technology fundamentally reshaped the finance technology and the flourishing development over the past decade. The high coverage of both the internet network and the mobile phone has facilitated Taiwan to become one of the most potential internet finance regions. This study aims to empirically validate the technology acceptance model (TAM 3) for exploring the key factors that influence the internet finance development. SEM was adopted to investigate both the hypothesis and the path coefficient associations among the constructs and their significance. Confirmed factor analysis for the instrument validity and reliability assessment was made. Hierarchy regression was performed to test the moderator effect of experience and voluntariness. This study result found that Taiwan finance customers had high expectations of information security and preferred high technology products with complex functions. The result demonstrated that customer’s Use Behavior was influenced by Perceived of Usefulness, not Perceived of Ease of Use. The moderator effect result in Experience had a positive moderator effect on Objective Usability to Perceived Ease of Use. This research extracted the key factors that influenced the internet finance development in Taiwan for providing both local government and internet finance developing countries guidelines while concurrently developing an internet finance development strategy.

The purpose of this study is to understand the relationship among leisure physical activity, sedentary lifestyle, physical fitness, and happiness in healthy elderly adults aged over 65 years old in Taiwan. Data were recruited from the National Physical Fitness Survey in Taiwan, which was proposed in the Project on the Establishment of Physical Fitness Testing Stations by the Sports Administration of the Ministry of Education. Participants were recruited from fitness testing stations set up in 22 counties and cities from October 2015 to May 2016. A total of 20,111 healthy older adults aged 65&ndash, 102 years were recruited as research participants. The fitness testing procedure was described to all participants, who were provided with a standardized structured questionnaire. Participants&rsquo, data included sex, city or county of residence, living status (living together with others or living alone), education level, and income. Physical fitness testing was conducted in accordance with The Fitness Guide for Older Adults published by the Sports Administration of the Ministry of Education. The testing involved cardiorespiratory endurance, muscle strength, muscle endurance, flexibility, balance, and body composition. The t-test was used to evaluate the differences between continuous and grade variables under the two classification variables of sex, city or county of residence, and living status. We used the MARS (multivariate adaptive regression splines) model to analyze the effects of physical fitness variables and leisure physical activity variables on happiness. Among healthy elderly adults, sex, age, living status, body mass index, and leisure physical activity habits proved to be related to happiness. Aerobic endurance (2-min step test), muscular strength and endurance (30-s arm curl and 30-s chair stand tests), flexibility (back stretch and chair sit-and-reach tests), and balance ability (8-foot up-and-go tests and one-leg stance with eyes open tests) were found to be related to happiness. The results of this study indicate that increased physical activity and intensity, as well as physical fitness performance, are associated with improved happiness.

The number of people using internet has increased due to advances in information technology, and the growth of electronic commerce (e-commerce) is increasingly growing. This study aims to investigate the factors that influence consumer intention to adopt e-commerce in Jakarta and Taipei. In this paper, additional variables such as trust, costs, social influences, various services, and control variables such as age, educational level, and gender of consumers become work extension of traditional model of technology acceptance (TAM) and the diffusion of innovation (DOI) models. By comparing consumers from both Jakarta and Taipei, this research is able to form a comparison model based on two different cultural settings. Data are collected from 192 Jakarta consumers and 184 Taipei consumers, and ANCOVA is employed to test the research model. The results show that trust, cost, social in?uence, and variety of services, perceived usefulness and trialability have significant influence to Jakarta consumer decisions to adopt e-commerce. All of variables except variety of services have significant influence to Taipei consumer decisions to adopt e-commerce. Demographic profile such as age, gender and education level have no significant influence to both cities consumers. Results from this study will be useful for online companies in formulating marketing strategy, especially for companies that will operate in Indonesian market, since Indonesia is a huge and growing market.

This paper compares the standby and parallel systems through the following analyses: reliability measures such as reliabilities, mean times to failure, and failure rates are first compared. These comparisons are reconsidered when the number of units of the two systems cannot be predefined constantly but is a random variable that can be estimated. Replacement policies in which how many number of units should be provided for replacements are compared second. When the two systems work for the same job with a random processing time, their optimal scheduling problems are compared third by employing excess and shortage costs. Finally, the standby and parallel modes are applied into data transmission system, and their mean transmission times are compared. All comparative discussions are given analytically and numerically in exponential distributions, and their potential values could be explored in future studies. This work is partially supported by the Qatar National Research Fund (grant number NPRP 4-631-2-233) and the National Science Council of Taiwan (grant number NSC 102-2221-E-030-018). Scopus

Some systems work for a job with random working times. It would be useful for such systems that they are checked at the completion of working times to detect their failures, which is called a random inspection policy. Two inspection policies, where a system is checked at periodic or successive times and also at every completion of working times, are considered. The total expected costs until the detection of failure are obtained, and when the random working time is exponential, optimal inspection policies which minimize them are derived analytically. Furthermore, the inspection policy where the system is checked only at every completion of N th working time is proposed. Finally, as one of modified random inspection models, the backup model where the system goes back to the latest checking time when it has failed is taken up and analyzed, by using the inspection policy.

This paper proposes a random and age replacement policy for an operating unit which works at random times. First, the unit is replaced before failure at a planned time T or at the completion of a working time, whichever occurs first. The expected cost rate is obtained. Next, as one extended model, the unit is replaced before failure at a number N of working times or at a planned time T. An optimal policy which minimizes the expected cost rate is discussed analytically, and its numerical example is given. Two modified models, where the unit is replaced at the first completion of the working time over time T or at number N, and it is replaced at time T or number N, whichever occurs last, are considered. Furthermore, we show that this corresponds to a cumulative damage model by replacing shock with work. Finally, one optimization problem of how much time to preset for scheduling the completion of N works is proposed.

This article is an extension of the periodic imperfect maintenance model in the literature. The purpose of this research is to investigate the influence on the optimal periodic maintenance policy after considering the failure replacement in the last period of preventive maintenance (PM). The specific maintenance decisions for a repairable system are: when to replace the system, when to repair the system; whether to conduct PM or keep the system operating. A partially periodic PM policy is proposed incorporating the costs of minimal repair, PM, failure replacement, and preventive replacement. The average cost rate for the proposed policy is obtained. Finally, the optimal parameters of the maintenance policy can be calculated using the cost rate function and the numerical comparisons of different policies are provided to demonstrate the effect of failure replacement.

A quasi-lumped design of a suspended stripline (SSL) bandpass filter (BPF) exhibiting high signal selectivity is proposed. In the circuit, transmission zeros were implanted to enhance the stopband signal rejection. A sample BPF having an operation band of 6.77– 7.33GHz was fabricated and measured for performance verification of the proposed design. Corresponding author: M.-H. Ho (ho@cc.ncue.edu.tw).

Face recognition has been a popular research topic in computer vision. Numerous different face recognition techniques have been developed owing to the growing number of real world applications. This study presents a face recognition method based on the stereo matching and eigenface techniques under a stereovision system. The proposed method aims to improve the performance of the 2D eigenface system by adding 3D information. 3D information (called disparity face) was derived by taking two faces of a subject simultaneously in different positions, and then the two faces were further matched using a scanlined-based asynchronous Hopfield neural network. After deriving 2D and 3D faces, we applied principal component analysis (PCA) to both faces to extract effective features for recognition. An experiment was conducted acquiring the facial images of 100 individuals. Each subject provides three pairs of faces with different expressions for training and testing. At the finals, the performance of face recognition using 2D faces, disparity faces, and a combination of the two was evaluated and compared. The experimental results reveal that a 3-5% improvement in recognition rate is achieved by using the additional depth information.

Flexibility is an important consideration when implementing an optimal policy for the maintenance and replacement of systems subject to stochastic deterioration. Repair and replacement policies are usually determined on the basis of expected costs; however, it is important to provide a means by which a given policy can be re-evaluated for a particular realization. In other words, when a machine fails, particular costs relevant at that time should be used to modify the policy if those costs vary from the expected values that were used in determining the original policy. In this paper we discuss a minimal repair/replacement problem to demonstrate the use of post-optimal analyses that are performed at the time of policy implementation.

This study developed a comprehensive model of how smartphone users search for pre-trip tourism information. Important dimensions and relationships in tourism information search (TIS) behavior were studied in 21 subjects. The data collection process included semi-structured in-depth interviewing data and field observation data. The analysis revealed 10 activities characteristic of TIS behavior: internal searches, mobile searches, saving information in the smartphones, preliminary collaborative TIS, barriers to TIS, bringing mobile search to an end, summarizing information, PC Internet search, advanced collaborative TIS, and searches via editorial communications. Such data collection was not performed in isolation. Further, 20 propositions have been developed for future testing. The results suggest that pre-trip TIS appears to consist in a diversity of search patterns with the usage of multiple information sources; in addition, it is no longer individual but collaborative behavior in the context of Web 2.0. Finally, the theoretical and practical implications of the research work are discussed, and directions for future work are suggested.

This paper discusses an optimal maintenance policy for a parallel system with periodic inspection. The system is composed of several units which have an independent and identical distribution. When the number of failed unit exceeds a threshold level, the system incurs a loss cost per unit of time from a failure to the next inspection. When the next inspection finds the failure, the system is overhauled, and the system becomes like new. Further, the system is overhauled at planned time in spite of the state of the system. Introducing the loss cost for an inspection and overhaul, the expected cost is obtained and an optimal number of inspections which minimizes the expected cost rate is derived analytically. Numerical examples are given when the failure distribution of each unit is exponential.

In this paper, the authors propose a BSF design of quasi-lumped elements realizing on the SSL structure. The building lumped elements, inductors and capacitors, are composed of various patterns of planar metallic patches which might reside on either or both sides of the SSL's central stripline. A lumped elements circuit model is developed to analyze the prototype filter's frequency response. The proposed BSF is built from alternatively cascading series circuit blocks and shunt circuit ones with each of the circuit blocks composing of an inductor and a capacitor. The lumped elements are in shunt-connection in the series modules and the filter's shunt blocks have the elements in a series-connection form. Each of the circuit blocks can individually provide a transmission zero to the filter's frequency response. A wideband BSF can be realized while multiple zero are properly arranged. The filter stopband BW is controlled by the combinations of the created transmission zeros. A wideband BSF can be realized while the multiple zeros are properly arranged. Experiments are conducted to verify the filter's performance and good agreements are observed between the circuit model simulation and the measurements.

Surveillance test schedule has been studied to increase standby system availability and keep plant safety. Optimal testing schedules have been studied and developed for simple systems, such as series and parallel systems. For more complex systems, a testing policy was usually chosen among the pre-specified testing strategies based on the performance calculated by computer codes. However, it was not sure the adopted testing strategy was optimal or near optimal. This study summarized several optimal testing strategies of simple systems. Based on these previous results, some suggestions were proposed to build up testing strategies for complex systems to maximize system availability.

Different type of maintenance problems have been investigated during the past decades. With the growth in complexity of modern systems, the cost of purchasing new systems becomes higher ever than before. Surprisingly, very little attention in the literature has been paid to the failure replacement in these preventive maintenance models. However, in practice most systems incur increasingly expensive down time costs when the systems suffer the unexpected failures. The major changes to the standard maintenance model in this research are the addition of a failure replacement cost for a failed system and the reliability limit for which system has to be replaced. The overall objective of this research is to propose an efficient algorithm to obtain the optimal maintenance policy. The optimal preventive maintenance policy is investigated with incorporating the costs of minimal repair, imperfect preventive maintenance, failure replacement and preventive replacement. The specific maintenance actions for a repairable system are when to perform an imperfect preventive maintenance or to replace the system while the system is in the operating condition. In another case, the specific maintenance actions for a repairable system are whether to replace the system, or to perform a minimal repair when the system fails. The number of imperfect preventive maintenance and the control limits of the optimal maintenance policy are calculated under the expected average cost rate criterion.

For the maintenance and replacement of system subject to stochastic deterioration, flexibility is an important consideration factor. Different possible maintenance policies are discussed in this paper where the failure distribution modeled by the Weibull distribution. The total discounted cost concept is very important in decision making for the complex system such as expensive capital equipment with operating life cycle lasting for years. A modified maintenance model is proposed with incorporating the costs of operating cost, the maintenance cost of minimal repairs, failure replacements and preventive replacements. We investigate the maintenance policies by modeling the deteriorating process of a system as a Markov decision process. Under the discounted cost criterion, the optimal parameters for the control limit policy are obtained. The sensitivity analysis of these control limits is performed for the flexibility of decision making. The optimal equations of the Markov decision process are solved by using the backward recursive scheme over a set of finite planning horizons to approximate the optimal policies for the infinite planning horizons.

Preventive maintenance (PM) can slow the deterioration process of a repairable system and restore the system to a younger age or state. Many researchers focus on studying PM models for the cases of age or failure rate reduction and developing optimal PM policies. However, the PM actions, such as cleaning, adjustment, alignment, and lubrication work, may not always reduce system's age or failure rate. Instead, it may only reduce the degradation rate of the system to a certain level. Furthermore, most of the existing optimal PM policies result in very low reliability at the time of preventive replacement (PR). In practice, however, high reliability is usually required for a system to avoid failures being occurred. This paper is to develop an optimal periodic PM policy over an infinite time span by minimizing the expected cost rate with the consideration of reliability limit (Rmin,) for Weibull-failure-time systems with degradation rate reduction after each PM. The proposed optimal periodic PM policy consists of two PM models. One model has fully periodic PM time-interval for every preventive replacement cycle; the other model has partially periodic PM time-interval where the time interval between the final PM and the PR is not a constant. For specified reliability limit, the proper model is chosen by using the algorithm provided in this paper. Examples are demonstrated and the sensitivity analysis is also presented for the proposed PM models.

Some systems work for a job with random working and processing times, and are checked at periodic and random times. When a failure occurs, we execute the backup operation to the latest checking time. First, the expected costs with periodic and random backups are formulated, and comparisons between periodic and random policies are made. Next, we focus on the backup policies when the system is checked at the Nth interval of working times, two total expected costs are obtained and optimal numbers N* which minimize them are derived analytically. Finally, one modified backup model in which failures are detected only at checking times is proposed and two expected costs are obtained.

The purpose of this study was to evaluate the recurrence rate and medical expenses of acute myocardial infarction (AMI) following inpatient cardiac rehabilitation. A total of 834 patients with AMI were divided into Group 1 (with inpatient cardiac rehabilitation) and Group 2 (without inpatient cardiac rehabilitation). The results showed that Group 1 had a lower AMI recurrence rate (a 0.640-fold lower hazards ratio) than Group 2 [95% confidence interval (CI) = 0.197–1.863; p = 0.004]. Compared with the medical costs of Group 2, Group 1 also had lower medical costs (a 0.947-fold lower hazards ratio) than Group 2 (95% CI = 0.934–0.981; p = 0.042). These findings have implications for the decision making of clinicians and health policymakers attempting to provide adequate services for patients with AMI.