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An optimal planning model of the sectional switch and tie line for the distribution network is proposed considering the tradeoff between the system reliability and economy. First, the fault incidence matrices are established for the distribution network, and the explicit analytical expression of the system reliability index is realized by the algebraic operation of the fault incidence matrices and fault parameter vectors. Then, the 0–1 integer quadratically constrained optimization model is established for the sectional switch configuration considering the capacity constraint of the tie line. Finally, the sectional switches and tie lines are optimized jointly to ensure the economic investment and maximize the system reliability. The distribution network in Taiwan Power Company is used to verify the applicability of the proposed optimization method. Compared with the intelligent optimization algorithm, the mathematical programming method in this paper can always find the global optimal switch configuration quickly. In addition, the influence of the tie line capacity constraints on the sectional switch configuration is also considered, which can provide practical reference for the power network planners in the optimization design of the distribution network. [ABSTRACT FROM AUTHOR]

The annual output value of Taiwan’s wafer foundry and IC packaging test ranks first worldwide. The electronics industry has a complete industrial ecological chain in the supply chain system of global information and communication technology. In order to increase market competitiveness and increase the operational flexibility, manufacturing process outsourcing has become a trend in the business model of the electronics industry. The quality of the outsourcing affects the quality and function of the final product, the outsourcer selection is crucial to ensure the quality of the final product. This article takes the wire bonding process as an example, and proposes a fuzzy selection model of quality-based IC packaging process outsourcers. Then, this article selects the six standard deviation indicator that can fully reflect the process yield and quality level as the evaluation tool. Since the indicator contains unknown parameter, in order to improve the accuracy of estimation and overcome the uncertainty of measurement data, this paper applies mathematical programming to derive the confidence interval of six sigma quality index, and proposes a confidence-interval-based fuzzy testing meth as a green outsourcer selection tool to reduce the risk of misjudgment due to sampling errors and improve the accuracy of the selection. [ABSTRACT FROM AUTHOR]

In the semiconductor manufacturing industry the development of single index assessing the equipment health condition is urgent, and thus the dashboard can be used for monitoring thousands of equipment. This paper proposes a novel equipment health index (EHI) framework and a Hotelling T-squared index (HTI) to monitor equipment and support preventive maintenance in real time in the semiconductor manufacturing industry. The EHI framework consists of data preprocessing, statistical process control, analytic hierarchy process, and a comprehensive single index representing the health condition of equipment. It considers different types of the univariate control charts for each status variable identification (SVID), and aggregates the scores corresponding to the control charts throughout the hierarchical structure. The HTI considers the correlation among the selected SVIDs and builds a multivariate index by using Hotelling T-squared statistic. An empirical study of Taiwan’s leading semiconductor assembly manufacturer finds that both the EHI and the HTI supported monitoring thousands of pieces of equipment in real time. In practice, firms can rapidly troubleshoot the root causes of failures by the decomposition of EHI. [ABSTRACT FROM AUTHOR]

In this paper, we present a new method to forecast the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) using fuzzy time series and automatically generated weights of multiple factors. The proposed method uses the variation magnitudes of adjacent historical data to generate fuzzy variation groups of the main factor (i.e., the TAIEX) and the elementary secondary factors (i.e., the Dow Jones, the NASDAQ and the M1B), respectively. Based on the variation magnitudes of the main factor TAIEX and the elementary secondary factors of a particular trading day, it constructs the occurrence vector of the main factor and the occurrence vectors of the elementary secondary factors on the trading day, respectively. By calculating the correlation coefficients between the numerical data series of the main factor and the numerical data series of each elementary secondary factor, respectively, it calculates the relevance degree between the forecasted variation of the main factor and the forecasted variation of each elementary secondary factor. Based on the correlation coefficients between the numerical data series of the main factor and the numerical data series of each elementary secondary factor on a trading day, it automatically generates the weights of the occurrence vector of the main factor and the occurrence vector of each elementary secondary factor on the trading day, respectively. Then, it calculates the forecasted variation of the main factor and the forecasted variation of each elementary secondary factor on the trading day, respectively, to obtain the final forecasted variation on the trading day. Finally, based on the closing index of the TAIEX on the trading day and the final forecasted variation on the trading day, it generates the forecasted value of the next trading day. The experimental results show that the proposed method outperforms the existing methods. [ABSTRACT FROM PUBLISHER]

The ultimate goal of an electric utility is to create maximum profit while maintaining reliability and security of the power supply. The operation and control of power system is sensitive to system demand. Therefore, improvements in load-forecasting accuracy will lead to cost savings and enhance system security. Due to Taiwan's distinct climate characteristics, it is difficult to obtain satisfactory load-forecasting results by treating the whole island as a single region. In addition, weather factors, such as temperature, relative humidity, and the Heat Index (HI) (a human-perceived equivalent temperature) may also affect load-consumption patterns. This paper proposes a multiregion short-term load-forecasting methodology, taking into account the HI to improve load-forecasting accuracy in Taiwan Power Company's (Taipower's) system. The results show that adopting the HI as a parameter can effectively improve the accuracy if the temperature of the region under investigation is above 27 ^\circ\C (80 ^ \circ\F). By considering both the load/weather diversity and the HI, further improvements to the load forecasting for the Taipower system during summer can be achieved. [ABSTRACT FROM AUTHOR]

This paper analyses productivity growth in 16 of Taiwan's manufacturing industries during the period 1978–1992. The non-parametric Data Envelopment Analysis approach is used to compute Malmquist productivity indexes. These are decomposed into efficiency change and technical change. The latter is further decomposed into an output bias, an input bias and a magnitude component. In addition, the direction of input bias is identified. Empirical results indicate that the sector's TFP increased at a rate of 2.89% per annum, which could be ascribed to a technical progress (2.56%) and an efficiency improvement (0.33%). [ABSTRACT FROM AUTHOR]

Taking into account only financial factors does not provide complete information on performance. This paper takes into consideration of both financial and non-financial performances when evaluating 35 sampled publicly traded commercial banks in Taiwan. The performance of banks is measured using an indexing method consisting of financial and non-financial measures. Banks are classified into two categories according either to the year founded, or to the type of major stockholders of a bank when founded. The results show that privatized government-owned/old banks are larger than private/new banks, respectively. Moreover, privatized government-owned banks have significantly higher financial performance index than private banks but both types of banks are not significantly different from each other in non-financial performance index. New and old banks are not significantly different from each other in both financial and non-financial performance indexes. With relatively large scale, higher profitability and better management, banks will perform relatively better among competitors in the following year. Furthermore, non-financial factors are important predictors of future financial and total performance indexes, though individual factor may not be consistently significant. More branch offices, better capital structure and solvency, and higher rates of growth in deposits and loans all result in more profits, and lead to higher customer satisfaction and more efficient management. Providing better technology to customers is an efficient way in promoting customer services, which in turn produces more profits and results in efficient management. CEOs, on average, have plans for better management and more profits. Among the factors that have direct and positive impacts on profitability, increasing the efficiency of management is the most efficient way. On the contrary, adding more branch offices contributes the least profits. Therefore, to increase bank profits, CEOs should aim to improve bank management, capital structure and solvency, rather than to add more branch offices. [ABSTRACT FROM AUTHOR]

Because of climate changes, natural disasters are becoming more serious. For instance, the intensity of typhoons has been increasing in recent years. Typhoons and other natural disasters have high-impact low-probability characteristics. Thus, procedures for preparing for natural disasters and increasing power system resilience are important issues. This article proposes an all-inclusive process for system operators to make decisions for enhancing power system resilience and economic value during a severe weather event. This process first considers the typhoon track, the fragility curve and the recovery time of transmission lines. After collecting these data, system simulations and a calculated resilience index are implemented according to cases with and without disaster prevention. Next, the probability threshold and calculated economic value index are obtained based on numerical weather prediction wind speeds and the cost-loss ratio. Finally, the two indexes are considered in combination to obtain the highest resilience with the greatest benefit. The proposed process helps system operators make decisions for appropriate preventive actions at the least cost. An actual Taiwan power system and a severe weather event are used as an example to demonstrate the proposed decision analysis. The simulation results indicate the feasibility of the proposed method, which can reduce potential risks caused by extreme weather events with the maximum economic benefits. [ABSTRACT FROM AUTHOR]

The Taiwan Humanities Citation Index (THCI) is Taiwan's effort to construct a search, research, and evaluation tool for research in the arts and humanities. This article describes the design, framework, features, and policies and rules of the THCI. Citation analysis has been regarded as a systematic way to investigate research developments and trends. Since the Arts & Humanities Citation Index (A&HCI) indexes mostly English journals, the THCI could become an auxiliary citation index of the A&HCI for Taiwanese researchers. [ABSTRACT FROM AUTHOR]

This paper discusses the evaluation of university libraries from two standpoints, namely, total measure and ratio measure, and the 24 university libraries in Taiwan are adopted for empirical study. The total measure is based on the services and total resources, including collections, personnel, expenditures, and buildings that a university library is providing for its patrons. The total amount of these five factors weighted by their importance is calculated for each library for comparison. It is a measure of the size of a library in an aggregated sense. The ratio measure, which takes into account the clients sharing the resources and services, measures the extent that a library satisfies the standards. In both cases, the data envelopment analysis methodology is utilized. To prevent the ignorance of some factors in calculating the index for comparison, the assurance region concept is applied. Good libraries should have high indices in both measures. The empirical results show that only the libraries of National Taiwan University, National Cheng Kung University, National Cheng Chi University, and National Chung Cheng University provide sufficient resources and services for their clients. [ABSTRACT FROM AUTHOR]

The penetration of renewable energy is gradually increasing. Therefore, power system flexibility, which is required to maintain system security and to cope with renewable generation uncertainty, becomes more important. Various technologies, such as flexible generators, demand management, energy storage, network reconfiguration, and even efficient system operations, are capable of improving power system flexibility. Nevertheless, among them, flexible generation resources can provide a direct way to enhance the power system flexibility. This article first applies the fuzzy analytic hierarchy process to calculate the flexibility index of generation resources. Then, the process of unit scheduling is implemented under various operation scenarios to investigate the relationship between the generation flexibility and the cost of unit scheduling. Finally, the required flexibility and the corresponding capacity of flexible generators under a specified penetration of renewable power generation are investigated under different operation scenarios. [ABSTRACT FROM AUTHOR]

Erectile dysfunction (ED) affects millions of men worldwide. Men with ED generally complain failure to attain or maintain an adequate erection during sexual activity. The prevalence of ED is strongly correlated with age, affecting about 40% of men at age 40 and nearly 70% at age 70. A variety of chronic diseases, including diabetes, ischemic heart disease, congestive heart failure, hypertension, depression, chronic renal failure, obstructive sleep apnea, prostate disease, gout, and sleep disorder, were reported to be associated with ED. In this study, data retrieved from a subset of the National Health Insurance Research Database of Taiwan were used for designing the clinical decision support system (CDSS) for predicting ED incidences in men. The positive cases were male patients aged 20-65 who were diagnosed with ED between January 2000 and December 2010 confirmed by at least three outpatient visits or at least one inpatient visit, while the negative cases were randomly selected from the database without a history of ED and were frequency (1:1), age, and index year matched with the ED patients. Data of a total of 2832 ED patients and 2832 non-ED patients, each consisting of 41 features including index age, 10 comorbidities, and 30 other comorbidity-related variables, were retrieved for designing the predictive models. Integrated genetic algorithm and support vector machine was adopted to design the CDSSs with two experiments of independent training and testing (ITT) conducted to verify their effectiveness. In the 1st ITT experiment, data extracted from January 2000 till December 2005 (61.51%, 1742 positive cases and 1742 negative cases) were used for training and validating and the data retrieved from January 2006 till December 2010 were used for testing (38.49%), whereas in the 2nd ITT experiment, data in the training set (77.78%) were extracted from January 2000 till Deceber 2007 and those in the testing set (22.22%) were retrieved afterward. Tenfold cross validation and three different objective functions were adopted for obtaining the optimal models with best predictive performance in the training phase. The testing results show that the CDSSs achieved a predictive performance with accuracy, sensitivity, specificity, g-mean, and area under ROC curve of 74.72%–76.65%, 72.33%–83.76%, 69.54%–77.10%, 0.7468–0.7632, and 0.766–0.817, respectively. In conclusion, the CDSSs designed based on cost-sensitive objective functions as well as salient comorbidity-related features achieve satisfactory predictive performance for predicting ED incidences. [ABSTRACT FROM AUTHOR]

Catch-per-unit-effort (CPUE) is often the main piece of information used in fisheries stock assessment; however, the catch and effort data that are traditionally compiled from commercial logbooks can be incomplete or unreliable due to many reasons. Pacific bluefin tuna (PBF) is a seasonal target species in the Taiwanese longline fishery. Since 2010, detailed catch information for each PBF has been made available through a catch documentation scheme. However, previously, only market landing data with a low coverage of logbooks were available. Therefore, several nontraditional procedures were performed to reconstruct catch and effort data from many alternative data sources not directly obtained from fishers for 2001–2015: (1) Estimating the catch number from the landing weight for 2001–2003, for which the catch number information was incomplete, based on Monte Carlo simulation; (2) deriving fishing days for 2007–2009 from voyage data recorder data, based on a newly developed algorithm; and (3) deriving fishing days for 2001–2006 from vessel trip information, based on linear relationships between fishing and at-sea days. Subsequently, generalized linear mixed models were developed with the delta-lognormal assumption for standardizing the CPUE calculated from the reconstructed data, and three-stage model evaluation was performed using (1) Akaike and Bayesian information criteria to determine the most favorable variable composition of standardization models, (2) overall R2 via cross-validation to compare fitting performance between area-separated and area-combined standardizations, and (3) system-based testing to explore the consistency of the standardized CPUEs with auxiliary data in the PBF stock assessment model. The last stage of evaluation revealed high consistency among the data, thus demonstrating improvements in data reconstruction for estimating the abundance index, and consequently the stock assessment. [ABSTRACT FROM AUTHOR]

In this study we adopt the two Data Envelopment Analysis (DEA) methods, including Banker-Charnes-Cooper (BCC) and Slacks-based Measure (SBM) super efficiency, to investigate whether a bank's technical efficiency index's results, incorporating account risk and not incorporating account risk, differ significantly. The information is obtained from 43 Taiwanese banks for the period 1998 to 2002. We also employ the nonradial and slacks-based Malmquist Total Factor Productivity (TFP) index to measure the impact of productivity change on the panel data. Our empirical results from the DEA approach are summarized as follows: (1) Loan quality factors have an impact on a bank's efficiency. In general, the bank with a higher degree of problem loans drops down its efficiency by incorporating account risk; however, the bank with a lower degree of problem loans increases its efficiency by incorporating account risk. (2) Super efficiency provides a good framework for ranking efficient units. (3) Based on the nonradial and slacks-based Malmquist TFP index, we find that bank productivity has increased and technical change has improved. (4) In Taiwan, bank with a higher performance will be more secure. [ABSTRACT FROM AUTHOR]

A new approach to the forecasting of construction cost indices in Taiwan is presented. Construction cost indices have always been used to assess the variations in construction labour and material costs. These indices have been traditionally based on historical statistical information in Taiwan. However, the indices fall short in forecasting the future cost trends in the construction industry. By investigating the characteristic data that make up the construction cost indices, the major determining factors were identified as (1) `the number of difference', (2) the required periods of preceding construction cost indices, (3) the weight associated with each preceding construction cost index, (4) the mean value of the series of construction cost indices that have been converted into a stationary series, and (5) the estimation of the errors between the predicted values of construction cost indices and the observed values of construction cost indices. An analytical model has been established to forecast the present and future construction cost indices based on these factors, and its feasibility tested by using the observed data of the construction cost indices obtained from the Executive Yuan of the Republic of China. The results suggest that this model is reasonably adequate in forecasting the trend values of construction cost indices in Taiwan. [ABSTRACT FROM AUTHOR]