Semantic Web: An Integrated Approach for Web Service Discovery, Selection and Composition

Web services are remote methods can be invoked through open standards such as Simple Object Access Protocols. The increasing web services in the repositories makes the selection process very complex. The same can be extended in forming the composition of web services. This research focuses on the semantic web service selection and composition through design and implementation of a framework. The proposed framework is an ontology based service selection approach and the selected services are participating in the composition process. This approach deals with semantic search, which uses Quality of services for service selection and composition. The entire framework is implemented with semantic web technology and the performance of the system is observed with domain specific ontologies

Modelling the elements of flash flood hydrograph using genetic programming

1031-1038A novel approach is proposed in this work on constructing the flash flood hydrograph by modelling the elements of the hydrograph namely the time to start of the initial flood (ti), the time to peak discharge (tp), the peak discharge (Qp) and the base time (tb) using Genetic Programming (GP). The proposed method is applied to the Kickapoo River catchment in Wisconsin, USA. It is demonstrated that even under limited data scenario, for a poorly gauged station, GP is able to model the elements of hydrograph with reasonably high accuracy thereby offering considerable lead time to predict the flash flood. The mathematical models developed by GP also offer some understanding of the influence of rainfall events and the stream discharge in producing the flash floods

Modeling studies on the behavior of single and double rubble mound breakwaters using genetic programming tool

Experimental investigation on wave transmission, reflection and dissipation characteristics of rubble mound breakwater models are time consuming and expensive. However, such studies are required for designing the rubble mound breakwaters for marine structures in an optimal condition. In order to overcome such problems many researchers used various soft computing techniques such as Artificial Neural Network (ANN), Adaptive Neuro Fuzzy Interference System (ANFIS), Genetic Programming (GP), Support Vector Machine (SVM) etc, in order to predict the design factors in the field of coastal engineering. The current work proposes Genetic Programming (GP) as a modeling tool to evolve mathematical models for the behavior of single and double breakwaters. Based on the detailed experimental data, GP models were performed to predict the reflected wave height (Hr), wave height on the breakwater (H5) and transmitted wave height (Ht) by considering with and without trigonometric effects of those breakwaters. The quality of predictability of the present model is measured by the statistical parameter, RMSE (Root Mean Square Error). Since the waves were more complex in nature, it is very essential in considering the trigonometric function’s effect in the modeling aspects. It is evident that, the GP model accurately described the non linear complex effects

The effects of daily gratitude writing and self-paced high intensity interval training on regulating emotional distress, sustained attention and hedonic perception among students in Universiti Sains Malaysia, Health Campus

A 2017’s cross-sectional study found that more than 80% of 287 Malaysian adolescents were either, depressed, stressed or experiencing anxiety with university students have being identified as the higher risk group for developing those mental health challenges. Due to the transitional phase adolescents face, there has been inadequate coping strategies towards stress. However, positive psychology has highlighted the potential impact that physical activities and the act of expressing gratitude has towards managing psychological challenges. Hence, this study aims to determine the effects of daily gratitude writing and self-paced high intensity interval (HIIT) training towards regulating emotional distress, sustained attention and hedonic perception among 46 students in Universiti Sains Malaysia, Health Campus. The selfdetermination theory and the ‘Broaden-and-Build’ theory of positive emotions contributed significantly to the development of this study. The RESET app – a mobile application was introduced as a gratitude journaling tool while quantitative data was obtained through the administration of a pre-post-Depression, Anxiety and Stress Scale-21 Questionnaire (DASS-21), Borg’s Scale for Rate of Perceived Exertion (RPE), Feeling Scale, and the Digital Vigilance Test (DVT). Upon completing the 8-week study, the results showed that there were differences between the pre-post intervention for DASS-21 and RPE scores within the 4 experimental groups but the results were not significant (p > .050). However, there was a significant decrease in errors made in the DVT (F (1,42) = 17.057, p = .000) while there was a significant increase in the Feeling Scale scores for gratitude journaling within participants (F (2,40) = 3.879, p = .029). Due to the study’s novelty, the results serve as a launch pad for future works in the efforts of integrating physical activities and positive psychology interventions towards effective psychological management and nurturing among the Malaysian youth

Ascertaining Time Series Predictability in Process Control: Case Study on Rainfall Prediction

Rainfall prediction is a challenging task due to its dependency on many natural phenomenon. Some authors used Hurst exponent as a predictability indicator to ensure predictability of the time series before prediction. In this paper, a detailed analysis has been done to ascertain whether a definite relation exists between a strong Hurst exponent and predictability. The one-lead monthly rainfall prediction has been done for 19 rain gauge station of the Yarra river basin in Victoria, Australia using Artificial Neural Network. The prediction error in terms of normalized Root Mean Squared Error has been compared with Hurst exponent. The study establishes the truth of the hypothesis for only 6 stations out of 19 stations, and thus recommends further investigation to prove the hypothesis. This concept is relevant for any time series which need to be used for real time process control

Sequential Multiple Assignment Randomized Trial (SMART) to identify optimal sequences of telemedicine interventions for improving initiation of insulin therapy: A simulation study

10.1186/s12874-021-01395-7BMC Medical Research Methodology21120

Estimating costs and benefits of stroke management: a population-based simulation model

The paper demonstrates how a system dynamics approach can support strategic planning of health care services and can in particular help to balance cost-effectiveness considerations with budget impact considerations when assessing a comprehensive package of stroke care interventions in Singapore. A population-level system dynamics model is used to investigate 12 intervention scenarios based on six stroke interventions (a public information campaign, thrombolysis, endovascular therapy, acute stroke unit (ASU), out-of-hospital rehabilitation, and secondary prevention). Primary outcomes included cumulative discounted costs and quality-adjusted life years (QALYs) gained, as well as cumulative net monetary benefit by 2030. All intervention scenarios result in an increase in net monetary benefit by 2030; much of these gains were realized through improved post-acute care. Findings highlight the importance of coordination of care, and affirms the economic value of current stroke interventions