Prioritizing the Factor Weights Affecting Tourism Performance by FAHP

The allocation of limited resources to effectively promote tourism is one of the most important issues in the tourism industry, especially in tough economic times. This paper seeks to investigate the relative importance of the key factors affecting tourism performance by applying the fuzzy analytic hierarchy process (FAHP) method. Specifically, the paper identifies the factors and sub-factors of the hierarchical structure from the literature relating to tourism performance. The framework based on the AHP method is then proposed to determine the relative weights of the factors and sub-factors in contributing to tourism performance. An application case related to the Vietnamese context is used to illustrate the proposed framework. The results of this study consolidated the tourism theory and suggested recommendations and solutions for the Vietnamese tourism industry. The proposed framework could be used by a group of decision-makers to achieve a consensus, as well as deal with uncertainty in the decision-making process. The findings of the study may serve as a tool for assistance for planners in improving the efficiency of tourism performance

Bacteremic community-acquired pneumonia due to Klebsiella pneumoniae: Clinical and microbiological characteristics in Taiwan, 2001-2008

<p>Abstract</p> <p>Background</p> <p><it>Klebsiella pneumoniae </it>is the major cause of community-acquired pyogenic infections in Taiwan. This retrospective study evaluated the clinical and microbiological characteristics of bacteremic community-acquired pneumonia due to <it>K. pneumoniae </it>in Taiwanese adults.</p> <p>Methods</p> <p>The clinical characteristics of bacteremic community-acquired pneumonia (CAP) in adults due to <it>K. pneumoniae </it>were compared to those of adults with bacteremic CAP due to <it>Streptococcus pneumoniae </it>at a tertiary medical center in Taiwan from 2001-2008. Risk factors for mortality of bacteremic CAP due to <it>K. pneumoniae </it>were analyzed. All clinical isolates of <it>K. pneumoniae </it>were examined for capsular serotypes, hypermucoviscosity phenotype, aerobactin and <it>rmpA </it>gene.</p> <p>Results</p> <p><it>K. pneumoniae </it>was the dominant cause of bacteremic CAP and was associated with a more fulminant course and a worse prognosis than bacteremic CAP due to <it>Streptococcus pneumoniae</it>. Initial presentation with septic shock and respiratory failure were independent risk factors for both early and total mortality. Serotype K1 and K2 comprised around half of all isolates. There were no significant differences in the clinical characteristics of patients with bacteremic CAP due to K1/K2 and non-K1/K2 isolates. Hypermucoviscosity phenotype as well as the aerobactin and <it>rmpA </it>genes were highly prevalent in the <it>K. pneumoniae </it>isolates.</p> <p>Conclusions</p> <p><it>K. pneumoniae </it>continued to be the dominant cause of bacteremic CAP in Taiwanese adults during 2001-2008. Initial presentation with septic shock and respiratory failure were independent risk factors for both early and total mortality from <it>K. pneumoniae </it>bacteremic CAP. Serotypes K1/K2 comprised around half of all isolates, but did not predispose patients to a poor clinical outcome. Physicians should be aware of the poor prognosis of any patient with bacteremic <it>K. pneumoniae </it>CAP and monitor these patients more closely.</p

An expert consensus for the management of chronic hepatitis B in Asian Americans.

BACKGROUND: Hepatitis B virus (HBV) infection is common with major clinical consequences. In Asian Americans, the HBsAg carrier rate ranges from 2% to 16% which approximates the rates from their countries of origin. Similarly, HBV is the most important cause of cirrhosis, hepatocellular carcinoma (HCC) and liver related deaths in HBsAg positive Asians worldwide. AIM: To generate recommendations for the management of Asian Americans infected with HBV. METHODS: These guidelines are based on relevant data derived from medical reports on HBV from Asian countries as well as from studies in the HBsAg positive Asian Americans. The guidelines herein differ from other recommendations in the treatment of both HBeAg positive and negative chronic hepatitis B (CHB), in the approach to HCC surveillance, and in the management of HBV in pregnant women. RESULTS: Asian American patients, HBeAg positive or negative, with HBV DNA levels \u3e2000 IU/mL (\u3e10 CONCLUSIONS: Application of the recommendations made based on a review of the relevant literature and the opinion of a panel of Asian American physicians with expertise in HBV treatment will inform physicians and improve patient outcomes

An Approach to the Classification of Cutting Vibration on Machine Tools

Predictions of cutting vibrations are necessary for improving the operational efficiency, product quality, and safety in the machining process, since the vibration is the main factor for resulting in machine faults. “Cutting vibration” may be caused by setting incorrect parameters before machining is commenced and may affect the precision of the machined work piece. This raises the need to have an effective model that can be used to predict cutting vibrations. In this study, an artificial neural network (ANN) model to forecast and classify the cutting vibration of the intelligent machine tool is presented. The factors that may cause cutting vibrations is firstly identified and a dataset for the research purpose is constructed. Then, the applicability of the model is illustrated. Based on the results in the comparative analysis, the artificial neural network approach performed better than the others. Because the vibration can be forecasted and classified, the product quality can be managed. This work may help new workers to avoid operating machine tools incorrectly, and hence can decrease manufacturing costs. It is expected that this study can enhance the performance of machine tools in metalworking sectors

A note on solution of the capacitated single allocation hub location problem

Hub-and-spoke designs are frequently used in many types of transportation and communication networks. The challenge to academics is to develop effective solution procedures for determining the number of hubs, locating hub facilities and allocating the non-hubs to the hubs. In this note, we deal with the capacitated single allocation hub location problem (CSAHLP) in which each non-hub can only be allocated to a single hub, each hub has its capacity constraint, and the objective function includes fixed costs for establishing hubs. A problem closely related to the CSAHLP is the uncapacitated single allocation hub location problem (USAHLP). We have proposed a hybrid heuristic for solving the USAHLP with competitive results obtained. In this note, an effective procedure to allocate the non-hubs to the capacitated hubs is developed to be embedded in the previous hybrid heuristic to solve the CSAHLP. Computational results show the presented heuristic is capable of obtaining optimal solutions for almost all small-scale problems and outperforms a simulated annealing algorithm from the literature in solving the large-scale CSAHLP. It is expected that this note can provide distribution managers an effective heuristic to design hub-and-spoke networks where the volume of traffic that a hub can collect is restricted.capacitated hub location problem; CHLP; p-hub median problem; uncapacitated hub location problem; UHLP; hub-and-spoke design; hub allocation.

A Neuro-Fuzzy Approach in the Classification of Students’ Academic Performance

Classifying the student academic performance with high accuracy facilitates admission decisions and enhances educational services at educational institutions. The purpose of this paper is to present a neuro-fuzzy approach for classifying students into different groups. The neuro-fuzzy classifier used previous exam results and other related factors as input variables and labeled students based on their expected academic performance. The results showed that the proposed approach achieved a high accuracy. The results were also compared with those obtained from other well-known classification approaches, including support vector machine, Naive Bayes, neural network, and decision tree approaches. The comparative analysis indicated that the neuro-fuzzy approach performed better than the others. It is expected that this work may be used to support student admission procedures and to strengthen the services of educational institutions

Total tardiness minimization on unrelated parallel machine scheduling with auxiliary equipment constraints

This research deals with scheduling jobs on unrelated parallel machines with auxiliary equipment constraints. Each job has a due date and requires a single operation. A setup for dies is incurred if there is a switch from processing one type of job to another type. For a die type, the number of dies is limited. Due to the attributes of the machines and the fitness of dies to each, the processing time for a job depends on the machine on which the job is processed, each job being restricted to processing on certain machines. In this paper, an effective heuristic based on threshold-accepting methods, tabu lists, and improvement procedures is proposed to minimize total tardiness. An extensive experiment is conducted to evaluate the computational characteristics of the proposed heuristic. Computational experiences demonstrate that the proposed heuristic is capable of obtaining optimal solutions for small-sized problems, and significantly outperforms an ATCS procedure and a simulated annealing method for problems in larger sizes.Setup Threshold-accepting method Total tardiness Unrelated parallel machine

Forecasting Hoabinh Reservoir’s Incoming Flow: An Application of Neural Networks with the Cuckoo Search Algorithm

The accuracy of reservoir flow forecasting has the most significant influence on the assurance of stability and annual operations of hydro-constructions. For instance, accurate forecasting on the ebb and flow of Vietnam’s Hoabinh Reservoir can aid in the preparation and prevention of lowland flooding and drought, as well as regulating electric energy. This raises the need to propose a model that accurately forecasts the incoming flow of the Hoabinh Reservoir. In this study, a solution to this problem based on neural network with the Cuckoo Search (CS) algorithm is presented. In particular, we used hydrographic data and predicted total incoming flows of the Hoabinh Reservoir over a period of 10 days. The Cuckoo Search algorithm was utilized to train the feedforward neural network (FNN) for prediction. The algorithm optimized the weights between layers and biases of the neuron network. Different forecasting models for the three scenarios were developed. The constructed models have shown high forecasting performance based on the performance indices calculated. These results were also compared with those obtained from the neural networks trained by the particle swarm optimization (PSO) and back-propagation (BP), indicating that the proposed approach performed more effectively. Based on the experimental results, the scenario using the rainfall and the flow as input yielded the highest forecasting accuracy when compared with other scenarios. The performance criteria RMSE, MAPE, and R obtained by the CS-FNN in this scenario were calculated as 48.7161, 0.067268 and 0.8965, respectively. These results were highly correlated to actual values. It is expected that this work may be useful for hydrographic forecasting