The purpose of this study was to investigate corruption and its effects on the development of the construction industry in Malawi. The major causes were identified and probable solutions as well as preventive measures suggested for all stakeholders in the construction industry in Malawi and neighbouring countries to follow in order to combat bribery and corruption. This treatise consisted of a literature review for the causes of bribery, fraud and corruption, effects of corruption on the construction industry, preventive measures, probable solutions to corruption and a descriptive survey involving responses from building and civil engineering contractors, the built environment professionals, home owners, developers, public works officers amongst others from the construction industry in Malawi. According to the literature study, the construction industry is one of the most corrupt industries in the world, which is a huge concern and threat both to governments, investors and humanity at large. This must be addressed by all the official players in the construction industry, from the innovator of a project to the tradesmen employed on that site. The research showed that all players in the construction industry are aware of the impact of corruption on the development of the construction industry in Malawi. Furthermore, there is room for improvement as far as prevention, reduction and elimination of corruption is concerned.

In the early feasibility study stage, the information concerning the target project is very limited. It is very common in practice for a Quantity Surveyor (Q.S.) to use the mean value of the historical building price data (with similar characteristics to the target project) to forecast the early construction cost for a target project. Most clients rely heavily on this early cost forecast, provided by the Q.S., and use it to make their investment decision and advance financial arrangement. The primary aim of this research is to develop a statistical model and demonstrate through this developed model how to measure the accuracy of mean value forecast. A secondary aim is to review the homogeneity of construction project cost. The third aim is to identify the best data pooling for mean value cost forecast in early construction stages by making the best use of the data available. Three types of mean value forecasts are considered: (1) the use of the target base group (relating to a source with similar characteristics to the target project), (2) the use of a non-target base group (relating to sources with less or dissimilar characteristics to the target project) and (3) the use of a combined target and non-target base group. A formulation of mean square error is derived for each to measure the forecasting accuracy. To accomplish the above research aims, this research uses cost data from 450 completed Hong Kong projects. The collected data is clustered into two levels as: (1) Level one - by project nature (i.e. Residential, Commercial centre, Car parking, Social community centre, School, Office, Hotel, Industrial, University and Hospital), (2) Level two -by project specification and construction floor area. In this research, the accuracy of mean value forecast (i.e. mean square error) for a total number of 10,539 of combined data groups is measured. From their performance, it may reasonably be concluded that (1) the use of a non-target base group (relating to sources with less or dissimilar characteristics to the target project) never improves the forecasting performance, (2) the use of a target base group (relating to a source with similar characteristics to the target project) cannot always provide the best forecasting performance, (3) the use of a combined target and non-target base group in some cases can furnish a better forecasting performance, and (4) when the cost data groups are clustered into a more detailed level, it can improve the forecasting performance.

Les enjeux liés aux problématiques de développement durable encouragent de plus en plus d'industriels, dans le secteur du bâtiment, à se lancer dans une politique de réduction de la consommation énergétique de leurs procédés industriels. C'est dans ce cadre qu'est menée cette étude, où nous nous intéressons au cas particulier de la fabrication des plaques de plâtre, qui de par les qualités qu'elles présentent liées à leur caractère pratique et rapide à poser (temps pour le neuf que la rénovation), sont parmi les matériaux de construction les plus utilisés à l'heure actuelle. En effet pour leur fabrication, on récupère d'abord du gypse depuis la carrière que l'on calcine pour avoir de l'hémihydrate, que l'on mélange ensuite avec de l'eau pour en faire du gypse, que nous rencontrons dans les plaques de plâtre. Cependant, pour avoir une meilleure ouvrabilité lors de la préparation, on est obligé d'ajouter une quantité d'eau excédentaire par rapport à celle que nécessite la stoechiométrie de la réaction d'hydratation – quantité qu'il faudrait évacuer par la suite par séchage. Ainsi, la fabrication des plâtre s'avère être très énergivore ; c'est tout l'intérêt de la thèse où il s'agira de mieux comprendre la physique qui régit le séchage du plâtre de façon à réduire cette surconsommation énergétique. Pour mener cette étude, nous nous sommes d'abord intéressés au cas du séchage de milieux poreux assez simples (empilement de billes de verre, tubes capillaires), nous servir ensuite de la compréhension des mécanismes physiques qui régissent le séchage de ces dits-milieux, d'une part, et des observations locales (RMN, IRM, microtomographie), d'autre part, pour expliquer les différents mécanismes physiques qui entrent en jeu lors du séchage du plâtre. Cette démarche nous a donné la possibilité d'avoir une bonne maîtrise de la physique du séchage du plâtre, c'est-à-dire l'identification des différents leviers et paramètres qui régissent sa cinétique. Ceci nous a permis de mettre en place un modèle physique pour la prédiction de cette cinétique - modèle qui peut être utilisé pour une démarche d'optimisation énergétique de la fabrication des plaques de plâtre / Issues related to sustainability encourage more building material industries to engage policies in making processes energy consumption reduction. This study is conducted in this purpose, and is focused on the case of plasterboard. Indeed for plasterboard manufacturing, gypsum from quarry are first calcined to get hemihydrate, which is then mixed with water to make again gypsum we find in plasterboard. However, to get a good workability during the preparation process, it is necessary to add an excess amount of water relative to that required by the stoichiometry of the hydration reaction. This excess water should be evacuated thereafter drying. Thus, the manufacture of gypsum proved to be very energy intensive : that is the cornerstone of this thesis, during which we will try to understand the physics that govern the drying of plaster in order to reduce its energy consumption. To conduct this study, we are primarily interested in understanding of simple porous media drying (stack of glass beads, capillary tubes). Then based on our understanding of the physical mechanisms that govern their drying, on one hand, and on local observations (NMR, MRI, microtomography), on the other hand, we give an explanation to the different physical mechanisms of plaster drying. This allows us to establish a physical model to predict the drying kinetics of plaster - model that can be used for energy optimization approach during the manufacturing process of plasterboard. Its can also be used for the drying kinetics prediction of other building materials

La thèse présentée ici s'attache à répondre au manque de formalisation de la TRIZ. Cet objectif répond au manque scientifique permettant de reconnaître la TRIZ en tant que théorie ; et de proposer un outil informatique d'assistance à la formulation des problèmes, selon les cadres de la TRIZ, enjeu industriel reconnu. <br />La méthode déployée s'appuie sur les outils de l'Intelligence Artificielle pour construire une ontologie de la formulation des problèmes en conception inventive de systèmes techniques, selon les cadres de la TRIZ. Cette ontologie est une représentation centrée-objet des concepts liés à la formulation des problèmes. Cette représentation est validée par une analyse, en logique de description, de la cohérence de la hiérarchisation des concepts et de leur bonne définition. L'opérationnalisation du modèle s'appuie sur la programmation d'une interface d'instanciation. Cette interface est basée sur un moteur de systèmes experts à base de règles.

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The primary energy costs of building materials and structures are discussed and comparisons are made between typical dwelling types. The economics of alternative wall, roof and floor constructions, providing various levels of insulationy are examined. Costs are assessed for a number of periods from 1970 to early 1980 for heating by gas and night rate electricity. The effect of price changes-on the economic attractiveness of insulation is investigated and the likely effects of future price rises are considered. It is concluded that, in certain circumstances, higher levels of insulation than those normally used in the UK have been economically attractive for the last few years and may possibly become more so. A survey of over fifty local authority houses with central heating, carried out by the author in Spring 1978, is described. Three types of houses of similar size were involved, having gas-fired 'wet' systems, and ducted warm air heating from electric storage and gas-fired units respectively. The survey was designed to determine certain aspects of occupant behaviour relevant to fuel consumption. Using regression techniques, relationships are obtained which explain more than two thirds of the variance of mean useful energy input rate between the houses of a given type in cold weather in terms of hours of use of central heating window opening habits, and for warm air heating, the closing of outlet registers. It was also revealed that for the house types with gas-fired heating the number of hours of use of the central heating was strongly influenced by household size and occupancy patterns. The implications for building design of the effects of occupant behaviour and of financial and energy costs are discussed.

Thesis (MTech (Construction Management))--Cape Peninsula University of Technology, 2005. / Cooperative education is practiced in many fields of industry. The South African construction industry has shown a preference for cooperative construction management education. Cooperative construction management education is practiced worldwide, but the majority of these programmes do not have compulsory credit bearing experiential learning as part of its programmes. This study examined the experiential leaning experience as well as the relevance and adequacy of preparation of subject areas taught in UT construction management programmes from the perspective of all the stakeholders. The study had four main objectives namely (I) To measure the extent of the perceived relevance by industry stakeholders, students and academics of the topics and content of construction management programmes at UT; (2) To establish the level of inadequacy, as perceived by industry stakeholders and academic staff of the preparation of UT construction management graduates to perform construction management functions: (3) To determine the level of dissatisfaction, if it existed with the experiential learning of construction management students; and (4) To establish the preparedness of construction industry stakeholders to mentor construction management experiential learning students; and to use the findings of the study to inform development of construction management programmes. Literature was reviewed relative to experiential learning and its general and specific application to construction management education. Self- administered questionnaires were completed by I" year as well as senior students registered for the National Diploma: Building as well as the B. Tech. degrees in Construction Management and Quantity Surveying. The study suggests that although the experiential learning experience IS relevant and generally well accepted by all role-players, there is a mismatch between the needs of industry and what is being produced by the UT. The topics that form the programme are relevant, but a level of dissatisfaction exists with the preparation of construction management graduates to perform construction management functions do exist.

The goal of this diploma thesis is to design a frame for an experimental vehicle. The primary object is to design a conception and layot of a drive unit. The frame design is followed by a creation of a model for an analysis. The model will serve for torsional stiffness computing using FEM analysis software. After evaluation of results additional chanhges of the design may take place. A vehicle will serve for testing combustion engines of the same conception and thus it is not intended to run on public roads.

The primary energy costs of building materials and structures are discussed and comparisons are made between typical dwelling types. The economics of alternative wall, roof and floor constructions, providing various levels of insulationy are examined. Costs are assessed for a number of periods from 1970 to early 1980 for heating by gas and night rate electricity. The effect of price changes-on the economic attractiveness of insulation is investigated and the likely effects of future price rises are considered. It is concluded that, in certain circumstances, higher levels of insulation than those normally used in the UK have been economically attractive for the last few years and may possibly become more so. A survey of over fifty local authority houses with central heating, carried out by the author in Spring 1978, is described. Three types of houses of similar size were involved, having gas-fired 'wet' systems, and ducted warm air heating from electric storage and gas-fired units respectively. The survey was designed to determine certain aspects of occupant behaviour relevant to fuel consumption. Using regression techniques, relationships are obtained which explain more than two thirds of the variance of mean useful energy input rate between the houses of a given type in cold weather in terms of hours of use of central heating window opening habits, and for warm air heating, the closing of outlet registers. It was also revealed that for the house types with gas-fired heating the number of hours of use of the central heating was strongly influenced by household size and occupancy patterns. The implications for building design of the effects of occupant behaviour and of financial and energy costs are discussed.

The construction sector is embossed with uncertainty, where cash flow prediction, time delays, and complex feature interaction make it hard to predict which future projects will be profitable or not. This thesis explores the prediction of project yield and project success for a company in the construction industry using supervised learning models. Leveraging historical project data, parametric traditional regression and machine learning techniques are employed to develop predictive models for project yield and project success. The models were chosen based on previously related work and consultations with employees with domain knowledge in the industry. The study aims to identify the most effective modeling approach for yield prediction and success in construction projects through comprehensive analysis and comparison. The features influencing project yield are investigated using SHAP (SHapley Additive exPla-nations) and permutation feature importance (PFI) values. These explainability techniquesprovide insights into feature importance in the models, thereby enhancing the understandingof the underlying factors driving project yield and project success. The results of this research contribute to the advancement of predictive modeling in the construction industry, offering valuable insights for project planning and decision-making. Construction companies can optimize resource allocation, mitigate risks, and improve projectoutcomes by accurately predicting project yield and success and understanding the keyfactors influencing it. The results in this thesis reveal that the machine-learning models outperform the parametric models overall. The best-performing models, based primarily on accuracy and ROI, were the random forest models with both binary and continuous outputs, leading to a suggested data-driven guideline for the company to use in their project decision-making process.