78 research outputs found

    A Fuzzy Nonlinear Programming Approach for Optimizing the Performance of a Four-Objective Fluctuation Smoothing Rule in a Wafer Fabrication Factory

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    In theory, a scheduling problem can be formulated as a mathematical programming problem. In practice, dispatching rules are considered to be a more practical method of scheduling. However, the combination of mathematical programming and fuzzy dispatching rule has rarely been discussed in the literature. In this study, a fuzzy nonlinear programming (FNLP) approach is proposed for optimizing the scheduling performance of a four-factor fluctuation smoothing rule in a wafer fabrication factory. The proposed methodology considers the uncertainty in the remaining cycle time of a job and optimizes a fuzzy four-factor fluctuation-smoothing rule to sequence the jobs in front of each machine. The fuzzy four-factor fluctuation-smoothing rule has five adjustable parameters, the optimization of which results in an FNLP problem. The FNLP problem can be converted into an equivalent nonlinear programming (NLP) problem to be solved. The performance of the proposed methodology has been evaluated with a series of production simulation experiments; these experiments provide sufficient evidence to support the advantages of the proposed method over some existing scheduling methods

    Molecular Characteristics and Antimicrobial Resistance of Group B Streptococcus Strains Causing Invasive Disease in Neonates and Adults

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    We aimed to analyze the molecular characteristics, clonality and antimicrobial resistance profiles of group B streptococcus (GBS) isolates collected in Taiwan from invasive diseases and carriage. Multilocus sequence typing (MLST) was used to assess the genetic diversity of 225 GBS strains from neonates and adults with invasive GBS diseases. 100 GBS strains collected from colonized pregnant women during the same period were compared, and all strains were characterized for one of nine capsule genotypes. We also determined the susceptibilities of all GBS isolates to various antimicrobial agents. The most frequently identified serotypes that caused invasive disease in neonates were III (60.6%) and Ia (17.3%), whereas type VI (32.7%), Ib (19.4%), and V (19.4%) were the most common to cause invasive disease in adults. Serotype VI was the leading type that colonized pregnant women (35.0%). Twenty-six sequence types (STs) were identified, and 90.5% of GBS strains were represented by 6 STs. ST-17 and ST-1 were more prevalent in invasive diseases in neonates and adults, respectively. The majority of serotype III and VI isolates belonged to clonal complex (CC)-17 and CC-1, respectively. ST-17 strains were more likely to cause meningitis and late-onset disease than other strains. In addition, ST-12 and ST-17 GBS strains showed the highest rate of resistance to erythromycin and clindamycin (range: 75.8–100%). In conclusion, CC-17/type III and CC-1/type VI are the most important invasive pathogens in infants and non-pregnant adults in Taiwan, respectively. GBS genotypes vary between different age groups and geographical areas and should be considered during GBS vaccine development

    Molecular epidemiology and evolutionary genetics of Mycobacterium tuberculosis in Taipei

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    <p>Abstract</p> <p>Background</p> <p>The control of tuberculosis in densely populated cities is complicated by close human-to-human contacts and potential transmission of pathogens from multiple sources. We conducted a molecular epidemiologic analysis of 356 <it>Mycobacterium tuberculosis </it>(MTB) isolates from patients presenting pulmonary tuberculosis in metropolitan Taipei. Classical antibiogram studies and genetic characterization, using mycobacterial interspersed repetitive-unit-variable-number tandem-repeat (MIRU-VNTR) typing and spoligotyping, were applied after culture.</p> <p>Methods</p> <p>A total of 356 isolates were genotyped by standard spoligotyping and the strains were compared with in the international spoligotyping database (SpolDB4). All isolates were also categorized using the 15 loci MIRU-VNTR typing method and combin with <it>NTF </it>locus and RD deletion analyses.</p> <p>Results</p> <p>Of 356 isolates spoligotyped, 290 (81.4%) displayed known spoligotypes and 66 were not identified in the database. Major spoligotypes found were Beijing lineages (52.5%), followed by Haarlem lineages (13.5%) and EAI plus EAI-like lineages (11%). When MIRU-VNTR was employed, 140 patterns were identified, including 36 clusters by 252 isolates and 104 unique patterns, and the largest cluster comprised 95 isolates from the Beijing family. The combination of spoligotyping and MIRU-VNTR revealed that 236 (67%) of the 356 isolates were clustered in 43 genotypes. Strains of the Beijing family was more likely to be of modern strain and a higher percentage of multiple drug resistance than other families combined (P = 0.08). Patients infected with Beijing strains were younger than those with other strains (mean 58.7 vs. 64.2, p = 0.02). Moreover, 85.3% of infected persons younger than 25 years had Beijing modern strain, suggesting a possible recent spread in the young population by this family of TB strain in Taipei.</p> <p>Conclusion</p> <p>Our data on MTB genotype in Taipei suggest that MTB infection has not been optimally controlled. Control efforts should be reinforced in view of the high prevalence of the Beijing strain in young population and association with drug resistance.</p

    Enhancing the Sustainability of a Location-Aware Service through Optimization

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    A location-aware service (LAS) is an imperative topic in ambient intelligence; an LAS recommends suitable utilities to a user based on the user’s location and context. However, current LASs have several problems, and most of these services do not last. This study proposes an optimization-based approach for enhancing the sustainability of an LAS. In this paper, problems related to optimizing a LAS system are presented. The distinct nature of a LAS optimization problem in comparison with traditional optimization problems is subsequently described. Existing methods applicable to solving a LAS optimization problem are also reviewed. The advantages and disadvantages of each method are then discussed as a motive for combining multiple optimization methods in this study, as illustrated by an example. Finally, opportunities and challenges faced by researchers in this field are presented

    Entropy Thresholding and Its Parallel Algorithm on the Reconfigurable Array of Processors with Wider Bus Networks

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    Thresholding is the most commonly used technique in image segmentation. In this paper, we first propose an efficient sequential algorithm to improve the relative entropy-based thresholding technique. This algorithm combines the concepts of the relative entropy with that of the local entropy and also includes the quadtree hierarchical structure in it. Second, we derive a constant time parallel algorithm to solve this problem on the reconfigurable array of processors with wider bus networks (RAPWBN)
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