Design of a Workflow-Based Grid Framework

This paper aims to present the design of the Grid Collaborative Framework which has been proposed in one of our previous work. Grid infrastructure for resources sharing is somewhat stable with the wide acceptance of the Open Grid Services Architecture (OGSA) and Web Services Resource Framework (WSRF), but Grid framework for collaboration is far from desired. Current Grid Collaborative Frameworks (GCFs) are domain specific and lack of plan-supported capability. These limitations make them less useful and narrow in scope of application. Our grid collaborative framework aims to improve these limitations. With the theoretical foundation based on the activity theory, workflow languages, and designed on top of existing OGSA infrastructure, our proposed framework aims at accelerating the development of grid collaborative systems that consider work plans as central role

Distributed classifier migration in XCS for classification of electroencephalographic signals

This paper presents an investigation into combining migration strategies inspired by multi-deme Parallel Genetic Algorithms with the XCS Learning Classifier System to provide parallel and distributed classifier migration. Migrations occur between distributed XCS classifier sub-populations using classifiers ranked according to numerosity, fitness or randomly selected. The influence of the degree-of-connectivity introduced by Fully-Connected, Bi-directional Ring and Uni-directional Ring topologies is examined. Results indicate that classifier migration is an effective method for improving classification accuracy, improving learning speed and reducing final classifier population size, in the single-step classification of noisy, artefact-inclusive human electroencephalographic signals. The experimental results will be used as part of our larger research effort investigating the feasibility of using EEG signals as an interface to allow paralysed persons to control a powered wheelchair or other devices. © 2007 IEEE

Classification of EEG signals using a genetic-based machine learning classifier

This paper investigates the efficacy of the genetic-based learning classifier system XCS, for the classification of noisy, artefact-inclusive human electroencephalogram (EEG) signals represented using large condition strings (108bits). EEG signals from three participants were recorded while they performed four mental tasks designed to elicit hemispheric responses. Autoregressive (AR) models and Fast Fourier Transform (FFT) methods were used to form feature vectors with which mental tasks can be discriminated. XCS achieved a maximum classification accuracy of 99.3% and a best average of 88.9%. The relative classification performance of XCS was then compared against four non-evolutionary classifier systems originating from different learning techniques. The experimental results will be used as part of our larger research effort investigating the feasibility of using EEG signals as an interface to allow paralysed persons to control a powered wheelchair or other devices. © 2007 IEEE

Distributed simultaneous task allocation and motion coordination of autonomous vehicles using a parallel computing cluster

Task allocation and motion coordination are the main factors that should be consi-dered in the coordination of multiple autonomous vehicles in material handling systems. Presently, these factors are handled in different stages, leading to a reduction in optimality and efficiency of the overall coordination. However, if these issues are solved simultaneously we can gain near optimal results. But, the simultaneous approach contains additional algorithmic complexities which increase computation time in the simulation environment. This work aims to reduce the computation time by adopting a parallel and distributed computation strategy for Simultaneous Task Allocation and Motion Coordination (STAMC). In the simulation experiments, each cluster node executes the motion coordination algorithm for each autonomous vehicle. This arrangement enables parallel computation of the expensive STAMC algorithm. Parallel and distributed computation is performed directly within the interpretive MATLAB environment. Results show the parallel and distributed approach provides sub-linear speedup compared to a single centralised computing node. © 2007 Springer-Verlag Berlin Heidelberg

Effect of ciprofloxacin dosages on the performance of sponge membrane bioreactor treating hospital wastewater

© 2018 Elsevier Ltd This study aimed to evaluate treatment performance and membrane fouling of a lab-scale Sponge-MBR under the added ciprofloxacin (CIP) dosages (20; 50; 100 and 200 µg L−1) treating hospital wastewater. The results showed that Sponge-MBR exhibited effective removal of COD (94–98%) during the operation period despite increment of CIP concentrations from 20 to 200 µg L−1. The applied CIP dosage of 200 µg L−1 caused an inhibition of microorganisms in sponges, i.e. significant reduction of the attached biomass and a decrease in the size of suspended flocs. Moreover, this led to deteriorating the denitrification rate to 3–12% compared to 35% at the other lower CIP dosages. Importantly, Sponge-MBR reinforced the stability of CIP removal at various added CIP dosages (permeate of below 13 µg L−1). Additionally, the fouling rate at CIP dosage of 200 µg L−1 was 30.6 times lower compared to the control condition (no added CIP dosage)

Women's perspectives on termination service delivery in Vietnam: a cross-sectional survey in three provinces.

OBJECTIVE: To explore the perspectives of abortion service users regarding termination methods and abortion service delivery in Vietnam. MATERIALS AND METHODS: Structured exit interviews were conducted between August and November 2011 with women who underwent termination of pregnancy at 62 public health facilities in Hanoi, Khanh Hoa, and Ho Chi Minh City in Vietnam. All women presenting for termination during the study period were recruited to participate in the study. Following their abortion, women were asked about their perspectives on abortion service delivery and attributes of medical abortion (MA) versus manual vacuum aspiration (MVA). Multiple logistic regression was used to assess the association between current method uptake and each attribute. RESULTS: A total of 1,233 women were included in the survey: 541 (43.9%) from Hanoi, 163 (13.2%) from Khanh Hoa, and 529 (42.9%) from Ho Chi Minh: 23.1% underwent MA; 78.9% reported that women should be given a choice between MA and MVA; and 77.6% thought that abortion services were accessible. Among the 48% who responded, 30.1% thought that MA should be made available at primary/secondary health care facilities. Among women who had previously undergone both methods, women who reported that MA "feels more natural" (like a menstrual regulation/period) were more likely to choose MA for their current abortion (odds ratio 2.15, 95% confidence interval 1.26-3.69). CONCLUSION: MA uptake is significantly lower than MVA uptake. Further insights to women's perceptions of MA in Vietnam could help improve abortion service delivery in the country

Attributes and perspectives of public providers related to provision of medical abortion at public health facilities in Vietnam: a cross-sectional study in three provinces.

BACKGROUND: The purpose of this study was to investigate attributes of public service providers associated with the provision of medical abortion in Vietnam. METHODS: We conducted a cross-sectional study via interviewer-administered questionnaire among abortion providers from public health facilities in Hanoi, Khanh Hoa, and Ho Chi Minh City in Vietnam between August 2011 and January 2012. We recruited abortion providers at all levels of Vietnam's public health service delivery system. Participants were questioned about their medical abortion provision practices and perspectives regarding abortion methods. RESULTS: A total of 905 providers from 62 health facilities were included, comprising 525 (58.0%) from Hanoi, 122 (13.5%) from Khanh Hoa, and 258 (28.5%) from Ho Chi Minh City. The majority of providers were female (96.7%), aged ≥25 years (94%), married (84.4%), and had at least one child (89%); 68.9% of providers offered only manual vacuum aspiration and 31.1% performed both medical abortion and manual vacuum aspiration. Those performing both methods included physicians (74.5%), midwives (21.7%), and nurses (3.9%). Unadjusted analyses showed that female providers (odds ratio 0.1; 95% confidence interval 0.01-0.30) and providers in rural settings (odds ratio 0.3; 95% confidence interval 0.08-0.79) were less likely to provide medical abortion than their counterparts. Obstetricians and gynecologists were more likely to provide medical abortion than providers with nursing/midwifery training (odds ratio 22.2; 95% confidence interval 3.81-129.41). The most frequently cited advantages of medical abortion for providers were that no surgical skills are required (61.7%) and client satisfaction is better (61.0%). CONCLUSION: Provision of medical abortion in Vietnam is lower than provision of manual vacuum aspiration. While the majority of abortion providers are female midwives in Vietnam, medical abortion provision is concentrated in urban settings among physicians. Individuals providing medical abortion found that the method yields high client satisfaction

Stakeholder Perceptions towards the Quality of Coursera MOOCs Blended Learning in Vietnam: A Qualitative Study

Coursera MOOCs blended learning (CMBL) has been implemented at a Vietnamese Higher Education Institute (HEI) since the Fall 2019 semester. Our case study, which shows how Coursera MOOCs and the traditional classroom may work together, is unique in the context of Vietnamese higher education. In this case, students must complete the courses and earn certifications through Coursera MOOCs to qualify for the HEI’s offline final examinations. Meanwhile, students also engage in offline mentoring sessions with their classmates and lecturers (mentors). By employing the Service Quality (SERVQUAL) and 3P models, the research was conducted to explore how key factors might influence the quality of CMBL. This research conducted semi-structured interviews and employed thematic analysis with thirty interview participants, including ten administrators, eleven lecturers, three curriculum developers, and six students across four campuses of the HEI. We found that assessment, learning outcomes, learning content, Coursera staff’s responsiveness, offline mentors’ responsiveness and assurance, interaction, and student satisfaction might have considerably significant relationships with the quality of CMBL. On the other hand, Coursera instructors and offline mentors’ reliability have insignificant relationships with the quality of CMBL. This study has both theoretical and practical implications for universities and academics. Regarding the theoretical implications, this qualitative study provides critical criteria to measure the quality of the CMBL. Regarding the practical implications, it provides implications for curriculum development, teaching and learning, and assessment to improve the quality of CMBL. However, the authors could not travel across Vietnam to conduct face-to-face interviews in 2021 due to the COVID-19 pandemic. Therefore, twenty-eight online interviews were conducted via Microsoft Teams and two email interviews. A downside of an online interview is that personal qualities that are critical to a study may be amended during the interview, forcing the researcher to rely on the participant’s words. Additionally, unlike a face-to-face interview, an email interview lacks simultaneous communication between the interviewer and the interviewee. Keywords: Higher Education Institution (HEI), blended MOOCs, Coursera MOOCs Blended Learning (CMBL), Coursera MOOCs, offline mentoring, sustainable developmen

Atopic asthmatic immune phenotypes associated with airway microbiota and airway obstruction

© 2017 Turturice et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Background: Differences in asthma severity may be related to inflammation in the airways. The lower airway microbiota has been associated with clinical features such as airway obstruction, symptom control, and response to corticosteroids. Objective: To assess the relationship between local airway inflammation, severity of disease, and the lower airway microbiota in atopic asthmatics. Methods: A cohort of young adult, atopic asthmatics with intermittent or mild/moderate persistent symptoms (n = 13) were assessed via bronchoscopy, lavage, and spirometry. These individuals were compared to age matched non-asthmatic controls (n = 6) and to themselves after six weeks of treatment with fluticasone propionate (FP). Inflammation of the airways was assessed via a cytokine and chemokine panel. Lower airway microbiota composition was determined by metagenomic shotgun sequencing. Results: Unsupervised clustering of cytokines and chemokines prior to treatment with FP identified two asthmatic phenotypes (AP), termed AP1 and AP2, with distinct bronchoalveolar lavage inflammatory profiles. AP2 was associated with more obstruction, compared to AP1. After treatment with FP reduced MIP-1β and TNF-α and increased IL-2 was observed. A module of highly correlated cytokines that include MIP-1β and TNF-α was identified that negatively correlated with pulmonary function. Independently, IL-2 was positively correlated with pulmonary function. The airway microbiome composition correlated with asthmatic phenotypes. AP2, prior to FP treatment, was enriched with Streptococcus pneumoniae. Unique associations between IL-2 or the cytokine module and the microbiota composition of the airways were observed in asthmatics subjects prior to treatment but not after or in controls. Conclusion: The underlying inflammation in atopic asthma is related to the composition of microbiota and is associated with severity of airway obstruction. Treatment with inhaled corticosteroids was associated with changes in the airway inflammatory response to microbiota

High rate nitrogen removal by ANAMMOX internal circulation reactor (IC) for old landfill leachate treatment

© 2017 Elsevier Ltd This study aimed to evaluate the performance of a high rate nitrogen removal lab-scale ANAMMOX reactor, namely Internal Circulation (IC) reactor, for old landfill leachate treatment. The reactor was operated with pre-treated leachate from a pilot Partial Nitritation Reactor (PNR) using a high nitrogen loading rate ranging from 2 to 10 kg N m−3 d−1. High rate removal of nitrogen (9.52 ± 1.11 kg N m−3 d−1) was observed at an influent nitrogen concentration of 1500 mg N L−1. The specific ANAMMOX activity was found to be 0.598 ± 0.026 gN2-N gVSS−1 d−1. Analysis of ANAMMOX granules suggested that 0.5–1.0 mm size granular sludge was the dominant group. The results of DNA analysis revealed that Candidatus Kueneniastuttgartiensis was the dominant species (37.45%) in the IC reactor, whereas other species like uncultured Bacteroidetes bacterium only constituted 5.37% in the system, but they were still responsible for removing recalcitrant organic matter