Critical success factors model (CSF’sM) affecting the competencies of civil engineer in construction project

Highly skilful and competent civil engineers are required to accelerate and contribute effectively to technology development in spearheading Malaysia’s transformation agendas. The competency of these engineers included a combination of technical and thinking skills (intelligences), knowledge and experience, and willingness to conduct specified job tasks and work in compliance with agreed standards, rules and procedures. The aim of this research is to establish the critical success factors models (CSF’sM) affecting competencies of civil engineers in a construction project as well as to help improve managerial performance on the successful completion of construction project. Quantitative research method has been adopted in this study and the main survey using structured questionnaires. The questionnaire consisted of 53 critical success factors and 10 engineering competencies skills. The critical success factors (Independent Variable) is clustered into 5 groups and all the engineering competencies skills (Dependent Variable) is clustered in 1 group. These factors and assigned groups were validated by 33 construction personnel (directors, managers and engineers) during a pilot study. The main survey was conducted with a total of 360 questionnaires were received from civil engineers who work in G7 grade contractor registered with the Construction Industry Development Board (CIDB) and only involved the states of Johor, Selangor and Federal Territory of Kuala Lumpur by respond rate of 60%. The results from the survey were analysed using descriptive analysis and factor analysis. Next, the data analysis is carried out using SmartPLS software. A structural model of critical success factors affecting competencies of civil engineer was developed using Partial Least Squared-Structural Equation Modelling (PLS-SEM) technique. It was found that the model is fit due to the R2 value = 0.502 and in line with expert’s validation results. The model identifies that all 5 groups (Interpersonal Skills, Project Integration Management, Project Human Resource Management, Project Communication Management and Project Risk Management) are significant with t-value ≥ 1.645. Finally, this finding was validated by 11 construction practitioners who agreed that ‘Interpersonal skills’ group of factors contributes the highest impact on critical success factors affecting competencies of Civil Engineer in construction project. It is important that Civil Engineer should have knowledge and skills in term of management and technical skill. Therefore, Civil Engineer should improve their personal knowledge management skills in order to help their project team develop and implement project management knowledge and skills for their construction project in future

The detection and classification of blast cell in Leukaemia Acute Promyelocytic Leukaemia (AML M3) blood using simulated annealing and neural networks

This paper was delivered at AIME 2011: 13th Conference on Artifical Intelligence in Medicine.This paper presents a method for the detection and classification of blast cells in M3 with others sub-types using simulated annealing and neural networks. In this paper, we increased our test result from 10 images to 20 images. We performed Hill Climbing, Simulated Annealing and Genetic Algorithms for detecting the blast cells. As a result, simulated annealing is the “best” heuristic search for detecting the leukaemia cells. From the detection, we performed features extraction on the blast cells and we classifying based on M3 and other sub-types using neural networks. We received convincing result which has targeting around 97% in classifying of M3 with other sub-types. Our results are based on real world image data from a Haematology Department.Universiti Sains Islam Malaysia and the Ministry of Higher Education, Malaysi

An investigation on benefits and future expectation of Industrialised Building System (IBS) implementation in construction practices

Industrialised Building System (IBS) is well known in many developing countries due to the benefits that can be derived from its applications in construction projects. However, the low percentage of IBS usage may be due to lack of awareness and knowledge about IBS among many professionals. There may be factors that contribute to a lack of interest from the client towards IBS. The aim of this study is to improve the application of IBS particularly in private construction projects in Malaysia by determining the benefits and expectation on application of IBS in private construction projects. This study adopts a quantitative method using questionnaires that were sent to 35 construction firms as a sampling frame. Finally, the finding of this study hopefully could assist professional parties in construction industry in providing a better ground knowledge for improving decisions making to achieve the success of IBS construction projects implementation and also this study will achieved the project objectives in terms of predetermined objectives that are mostly within the time, specified budget and standard qualit

Public Art Development

Please allow me to express my interest in participating in the event; the agenda and objective are of high significance for discussing the maturity and development of a sustainable "cultural and creative infrastructure" powered by cultural policies and practices. Involvement and lobbying for such topics is essential for the cultural and creative dynamics where creative cities attract creative people.While navigating through a search engine and typing a name of a city, the first images to appear visualize the built environment of the city. For instance when you type Cairo into Google, you will be mainly looking at the Pyramids and built environment around the Nile in addition to the Old City of Cairo. If you type in New York you will find images of skyscrapers positioned around the natural landscape of the city, and so on and so forth.Thus tourism depends a lot on the built environment and the touristic standard is subject to the built environment, type and quality of tenants attracting the general public and of course the natural landscape.Arts and architecture play an important role among the built environment having both tangible and intangible economic impacts resulting from touristic attractions as well as other means; Cairo was once described as the most beautiful city in the world with the rich urban fabric and prosperity of the arts and architecture.In a country like Egypt where segmentation between the different social levels is becoming a real threat for future generations, it is crucial to work with all stakeholders including the authorities, civil society and the general public with objectives that would aim to serve all interests and gain a positive public opinion. 

A histochemical study of the human endometrium and placenta in health and disease

Eight substances were studied by histochemical methods in the human placenta in all stages of normal gestation as well as in certain pathological conditions. The corresponding histochemicgl patterns were described and discussed

Deep learning for time series classification

Time series analysis is a field of data science which is interested in analyzing sequences of numerical values ordered in time. Time series are particularly interesting because they allow us to visualize and understand the evolution of a process over time. Their analysis can reveal trends, relationships and similarities across the data. There exists numerous fields containing data in the form of time series: health care (electrocardiogram, blood sugar, etc.), activity recognition, remote sensing, finance (stock market price), industry (sensors), etc. Time series classification consists of constructing algorithms dedicated to automatically label time series data. The sequential aspect of time series data requires the development of algorithms that are able to harness this temporal property, thus making the existing off-the-shelf machine learning models for traditional tabular data suboptimal for solving the underlying task. In this context, deep learning has emerged in recent years as one of the most effective methods for tackling the supervised classification task, particularly in the field of computer vision. The main objective of this thesis was to study and develop deep neural networks specifically constructed for the classification of time series data. We thus carried out the first large scale experimental study allowing us to compare the existing deep methods and to position them compared other non-deep learning based state-of-the-art methods. Subsequently, we made numerous contributions in this area, notably in the context of transfer learning, data augmentation, ensembling and adversarial attacks. Finally, we have also proposed a novel architecture, based on the famous Inception network (Google), which ranks among the most efficient to date.Comment: PhD thesi