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(Wolverhampton Intellectual Repository and E-Theses)
WIRE is an open access repository for the research publications and other outputs from postgraduate students and staff at the University of Wolverhampton.
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Dengue virus in Sri Lanka: an observational study from 2014-2018Dengue virus is one of major public heath burden in several countries, it is described to be “a fast-emerging pandemic prone viral disease” by the WHO and is one of the most common form of vector borne diseases worldwide. The disease is transmitted through the female Aedes mosquito and most commonly found in tropical countries. A reported 400 million reported dengue cases occur yearly and an estimated 3 billion people could be affected by the disease in the upcoming decade making it a global crisis. The disease is caused by four serotypes of the dengue virus (DENV1-4) making it difficult for the treatment to work on the patients due to its different virulent mechanism. Using the data available from the Ministry of Health, Epidemiology Unit in Sri Lanka the dengue reported cases from 2014 to 2018 are analyzed over the five years to identify the trends and occurrence patterns.
Awareness of big data concept in the Dominican Republic construction industry: an empirical studyThe construction industry, being one of the main characters in the ever-demanding need for technology developments, sometimes falls short of other industries in terms of implementation. The adoption of Big Data (BD) in industries like health and retail has had positive impacts in aspects such as decision-making processes and forecasting trends that allow planning some future business movements in advance. Hence, the question of whether these results can be recreated in construction industry. Therefore, this paper addresses the level of awareness identified as the first step towards implementation of the BD Concept within the construction industry of Dominican Republic (DR). Since little to no information exist on the subject the selected approach to perform this research was qualitative, twenty-one semi-structured interviews were studied using content analysis. Four levels of awareness is developed based on the Endsley situation awareness model. The results showed that nearly ninety-five percent of the interviewees had either no knowledge or a very basic awareness of the BD requirements or intermediate awareness but only five percent had actually applied BD in the construction industry. This paper provides the level of awareness of BD in the DR construction industry and provides evidence for the need to provide continuous professional development programmes for construction professionals and a need for an update of curriculum in construction-related education.
Sarcasm target identification with LSTM networksGeçmi¸s yıllarda, kinayeli metinler üzerine yapılan çalı¸smalarda temel hedef metinlerin kinaye içerip içermediginin ˘ tespit edilmesiydi. Sosyal medya kullanımı ile birlikte siber zorbalıgın yaygınla¸sması, metinlerin sadece kinaye içerip içer- ˘ mediginin tespit edilmesinin yanısıra kinayeli metindeki hedefin ˘ belirlenmesini de gerekli kılmaya ba¸slamı¸stır. Bu çalı¸smada, kinayeli metinlerde hedef tespiti için bir derin ögrenme modeli ˘ kullanılarak hedef tespiti yapılmı¸s ve elde edilen sonuçlar literatürdeki ˙Ingilizce üzerine olan benzer çalı¸smalarla kıyaslanmı¸stır. Sonuçlar, önerdigimiz modelin kinaye hedef tespitinde benzer ˘ çalı¸smalara göre daha iyi çalı¸stıgını göstermektedir. The earlier work on sarcastic texts mainly concentrated on detecting the sarcasm on a given text. With the spread of cyber-bullying with the use of social media, it becomes also essential to identify the target of the sarcasm besides detecting the sarcasm. In this study, we propose a deep learning model for target identification on sarcastic texts and compare it with other work on English. The results show that our model outperforms the related work on sarcasm target identification.
Turkish music generation using deep learningBu çalı¸smada derin ögrenme ile Türkçe ¸sarkı bes- ˘ teleme üzerine yeni bir model tanıtılmaktadır. ¸Sarkı sözlerinin Tekrarlı Sinir Agları kullanan bir dil modeliyle otomatik olarak ˘ olu¸sturuldugu, melodiyi meydana getiren notaların da benzer ˘ ¸sekilde nöral dil modeliyle olu¸sturuldugu ve sözler ile melodinin ˘ bütünle¸stirilerek ¸sarkı sentezlemenin gerçekle¸stirildigi bu çalı¸sma ˘ Türkçe ¸sarkı besteleme için yapılan ilk çalı¸smadır. In this work, a new model is introduced for Turkish song generation using deep learning. It will be the first work on Turkish song generation that makes use of Recurrent Neural Networks to generate the lyrics automatically along with a language model, where the melody is also generated by a neural language model analogously, and then the singing synthesis is performed by combining the lyrics with the melody. It will be the first work on Turkish song generation.
A mesoscopic modelling approach for direct numerical simulations of transition to turbulence in hypersonic flow with transpiration coolingA rescaling methodology is developed for high-fidelity, cost-efficient direct numerical simulations (DNS) of flow through porous media, modelled at mesoscopic scale, in a hypersonic freestream. The simulations consider a Mach 5 hypersonic flow over a flat plate with coolant injection from a porous layer with 42 % porosity. The porous layer is designed using a configuration studied in the literature, consisting of a staggered arrangement of cylinder/sphere elements. A characteristic Reynolds number Rec of the flow in a pore cell unit is first used to impose aerodynamic similarity between different porous layers with the same porosity, ∈, but different pore size. A relation between the pressure drop and the Reynolds number is derived to allow a controlled rescaling of the pore size from the realistic micrometre scales to higher and more affordable scales. Results of simulations carried out for higher cylinder diameters, namely 24 µm, 48 µm and 96 µm, demonstrate that an equivalent Darcy-Forchheimer behaviour to the reference experimental microstructure is obtained at the different pore sizes. The approach of a porous layer with staggered spheres is applied to a 3D domain case of porous injection in the Darcy limit over a flat plate, to study the transition mechanism and the associated cooling performance, in comparison with a reference case of slot injection. Results of the direct numerical simulations show that porous injection in an unstable boundary layer leads to a more rapid transition process, compared to slot injection. On the other hand, the mixing of coolant within the boundary layer is enhanced in the porous injection case, both in the immediate outer region of the porous layer and in the turbulent region. This has the beneficial effect of increasing the cooling performance by reducing the temperature near the wall, which provides a higher cooling effectiveness, compared to the slot injection case, even with an earlier transition to turbulence.