56 research outputs found

    Tender price modelling : artificial neural networks and regression techniques

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    Cost modelling in construction is the art and science of developing a reliable and effective estimation of the tender price of a project. Cost estimation is an experiencebased task, which involves evaluations of unknown circumstances and complex relationships of cost-influencing factors. Researchers argue that cost model developments lack rigour and consistent conceptual framework within which the performance of different models may be compared and evaluated. This study analyses construction cost models by classifying them into three groups according to the techniques used. These include deterministic models (regression analysis); probabilistic models (Monte Carlo simulation); and artificial intelligence models (neural networks). This research investigates the development of two methodologies for tender price estimation of buildings utilising neural computing and regression techniques. The emphasis is to provide clients and practitioners with a reliable tool, which would offer trustworthy advice and prediction of tender prices at an early stage of a construction project. The analysis in this research is based upon a data set of 230 office projects, newly constructed in the UK between 1983 and 1997. The cost data of these buildings consists of tender prices and 13 other cost influencing factors. The data extracted using the Building Cost Information Service (BCIS) database of the Royal Institution of Chartered Surveyors (RICS). Questionnaire survey and interviews were adopted to identify, evaluate and rank cost significant factors according to their degree of influence on tender prices. The practitioners involved in this stage were UK based quantity surveyors. Some of these cost variables formulate the basis for developing the tender estimation models. Cluster analysis was conducted to categorise the data set into more homogeneous project groups based upon the cost variables. The hypothesis is that developing estimation models using project categories would yield better performance and more efficient models. Self-Organising Maps (SOM), a type of neural networks, is used for the cluster analysis. Seventeen neural networks and thirteen regression models are developed for tender price estimation using different parameters and cost factors. The performance and efficiency of these models are analysed and compared before and after the cluster analysis of the data set. On the other hand, sensitivity analysis is conducted by developing fifty-five models to evaluate the effectiveness of different combinationso f network parameterso n the accuracyo f tenderp rice estimation. The research findings indicate that, when the whole data set of 230 office projects is used, both methodologies produced low accuracy and failed to map the relationship between the tender price and the selected influencing cost factors. On the contrary, after clustering the data set into coherent groups using Kohonen neural networks, the performance of both RA and ANN models increased dramatically, with many estimation accuracies above 80% and 90%, which is highly satisfactory for tender price estimation at an early stage of a project. The outcomes imply that: (a) clustering the projects into homogeneous categories is significant and key for model performance and accuracy; (b) after cluster analysis there is no significant difference in the performance of RA and ANN models, although the RA outperformed the ANN in some models. The results also reveal that for both methodologies the accuracy of the estimation models that utilised two cost factors (project area and duration) outperformed the estimation models that used 13 cost factors, which is an indication that area and duration are the most dominant cost determinant variables

    Inteligencia emocional y habilidades sociales en los estudiantes del 2º año de educación secundaria de la I.E. Francisco Lizarzaburu, el Porvenir, 2018

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    La presente investigación tiene como propósito de establecer la relación que existe entre “Inteligencia Emocional y Habilidades Sociales en los Estudiantes del 2º Año de educación secundaria de la I.E. Francisco Lizarzaburu, El Porvenir, 2018”. Para alcanzar este objetivo se trabajó con una población muestral conformada por 185 niños de segundo grado de educación secundaria de la I.E. Francisco Lizarzaburu, El Porvenir, Para comprobar la hipótesis se utilizó un diseño correlacional, los instrumentos de recojo de datos que se emplearon lo constituyeron el Test TMMS-24 de Inteligencia Emocional y el Test de habilidades sociales de Goldstein et.Al.1980, para encontrar el nivel de correlación se trabajó con el coeficiente de Pearson y la validación de la hipótesis se realizó con la t de Student para grupos correlacionados, con un valor crítico del 5%. Los resultados indicaron que el nivel de inteligencia emocional es adecuado en un 58.4% y excelente en un 37.8% en los estudiantes del 2º año de educación secundaria de la I.E. Francisco Lizarzaburu, El Porvenir, 2018. El nivel de habilidades sociales, siendo de nivel alto en un 62.7% y un 36.8% en un nivel medio, en los estudiantes del 2º año de educación secundaria de la I.E. Francisco Lizarzaburu, El Porvenir, 2018.Se determinó la relación que existe entre las dimensiones de la inteligencia emocional y las dimensiones de las habilidades sociales encontrando que existe relación moderada y significativa entre habilidades relacionadas con los sentimientos y la atención emocional (rs=0.450; p<0.05); existe relación moderada y significativa entre habilidades relacionadas con los sentimientos y la reparación emocional (rs=0.402; p<0.05); existe relación moderada y significativa entre habilidades alternativas y la reparación emocional (rs=0.450; p<0.05); y por último también existe una relación moderada y significativa entre las habilidades de planificación y la atención emocional (rs=0.438; p<0.05); las otras dimensiones también presentan relaciones bajas pero significativas; en los estudiantes del 2º año de educación secundaria de la I.E. Francisco Lizarzaburu, El Porvenir, 2018

    Surgical Complications of Arteriovenous Fistula as Permanent Vascular Access in Patients with End Stage Renal Disease at Gezira Hospital for Renal Disease and Surgery. Revisited

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    Background: Vascular access (VA) is a mainstay to perform an efficient hemodialysis (HD) procedure. Objectives: To evaluate the surgical complications of AV fistula as permanent vascular access in a patient of end stage renal disease (ESRDS) at Gezira hospital for renal diseases and surgery (GHRDS). Methods: Retrospective, prospective cross sectional hospital based study, done in 237 patients with end stage renal disease who underwent arteriovenous fistula.In 206 patients of the study sample done retrospectively and 31 patients of the study sample done prospectively,and they were followed for 1year. Study was conducted from September 2010 to September 2016. Data was collected using questionnaire.&nbsp; Results: Sixty eight percent of study sample were males, with 42% above 50 years and 0.8% less than 10 years. Most of the patients (52.3%) were diagnosed as ESRD from the first presentation, 43.5% were diagnosed as chronic renal failure (CRF) on regular followup, while the minor rest of the patients were due to acute renal failure(ARF) which progressed to end stage renal disease.The complications rate was 32.8% (n=82), perioperative complications were 9.3% (n=22) represented as infections 3.8% (n=9), bleeding 3.0% (n=7), stenosis 1.7% (n=4), thrombosis 0.8% (n=2). The late complications were 23.18% (n= 60) the commonest was pseudo aneurysmal 19.4% (n=46) followed by venous HTN 0.8% (n=2) and steal syndrome 0.4%(n=1), skin necrosis 0.4%(n=1), idiopathic stop function 2.1% (n=5), thrombosis 0.4% (n=1). Conclusion: Permanent arteriovenous fistula is the best option for haemodialysis in patients with end stage renal disease. The commonest complication was puncture site pseudo aneurysm

    The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

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    INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

    Sustainability in the rural built environment : vernacular architecture of the Gezira Area/Sudan

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    PhD ThesisThe Gezira area of the Sudan saw the construction of one of the major agricultural schemes in Africa in the beginning of the twentieth century (1925). The construction of this scheme led to a development of two different rural models of settlement: the colonial model established by the British Governors at the time and the traditional vernacular model built organically by the local people; the farmers who are the main stakeholder of the scheme. Through time the local settlements have been subjected to changes in many aspects of housing design and quality. In the Sudan, the need to reorganize the organic villages is a critical issue, but government planning initiatives failed to pay attention to the simple planning issues of the organic settlements within their planning processes. The recognition of the simplicity and humbleness of the rural traditional villages may be itself a merit to those settlements that adapted themselves to changing conditions of many factors such as changing environment, changing socio-cultural behaviour and changing spatial arrangements and persist in competing with the planned organized agricultural scheme, which has exerted influential limitations on their development. These architectural changes - in settlement patterns, structure, and in the external appearance of the local houses - indicate the complexity of their causes. We are trying to understand the changes that the relationships of spaces and society have conveyed. The basic focus will be on the relationship between the socio-cultural factors and the built environment at three levels of development: regional settlement, local settlement and dwelling. To achieve this aim a systematic approach is used to investigate the relationship of socio-cultural behaviour with the built environment as it has evolved in the Gezira area of the Sudan. The analytical approach includes aspects of history and sociocultural factors that could expose the complex relationships between the settlement patterns, houses and their users. A second important feature of this research is its comparative character. The comparative characters of the planned settlement of the agricultural scheme, the organic settlement and the new extension of the organic village may explain the socio-cultural relationships. The research, also, contributes to explain the impact of built environment infrastructures and the planning interventions processes carried out by the Government to organise the organic vernacular settlements on the Gezira settlements. The research explores a wide range of literature and information resources to address these issues and draw a conceptual framework. The Gezira area is taken as a case study as it is characterised by different types of settlements that have emerged within the fabric of a developed agricultural scheme. Data collected for a case study of two space domains representing two types of settlements is used to consolidate the information used in the research. The thesis provides evidence that, working empirically; people are well able to navigate themselves to shape resources nearer to the realisation of their values. Evidence that at least tells us there are many ways in which to make a home meaningful, sustainable and far from rural deprivation. These ways could be reflected within the traditional vernacular architecture
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