Decision-making process framework at the planning phase of housing development project

Every housing development project needs to go through several procedures which consist of a decision-making process. By practising the decision-making process since the planning phase, the relevant decision-maker is assisted in analysing and organising all issues arise such as the problem in identification and selection of a suitable contractor for housing development. However, the decisions are made without knowing precisely what will happen in the future. The research’s primary purpose is to develop a process model for decision-making at Malaysia’s housing development planning phase. This study also examines the decision-making process practised among Malaysian private housing developers at the planning phase and classifies four main aspects of decision-making: methods, tools, criteria and information. The study then discovers whether the four main aspects (methods, tools, criteria and information) are strongly related to the decision making process. This study comprises the development of a theoretical framework by integrating the models that have been developed by numerous authors and researchers on the subject of decision making. Besides, 67 private housing developers have been chosen as respondents for a questionnaire survey in this study. The descriptive statistical analysis and the correlated analysis are conducted employing the Statistical Package for Social Sciences (SPSS). The results of this study show different findings for every four main aspects studied. However, it still answers the research objectives, and the relationship between the four main aspects of the decision-making process is accepted. This study is useful because it serves as a guide for private housing developers and governments in decision making at the planning phase of housing development. Moreover, this study provides a new process framework for decision making at the planning phase of housing development in Malaysia and assists housing developers and governments to make better predictions before proceeding to the construction phase

Visualisation of Origins, Destinations and Flows with OD Maps

We present a new technique for the visual exploration of origins (O) and destinations (D) arranged in geographic space. Previous attempts to map the flows between origins and destinations have suffered from problems of occlusion usually requiring some form of generalisation, such as aggregation or flow density estimation before they can be visualized. This can lead to loss of detail or the introduction of arbitrary artefacts in the visual representation. Here, we propose mapping OD vectors as cells rather than lines, comparable with the process of constructing OD matrices, but unlike the OD matrix, we preserve the spatial layout of all origin and destination locations by constructing a gridded two‐level spatial treemap. The result is a set of spatially ordered small multiples upon which any arbitrary geographic data may be projected. Using a hash grid spatial data structure, we explore the characteristics of the technique through a software prototype that allows interactive query and visualisation of 105‐106 simulated and recorded OD vectors. The technique is illustrated using US county to county migration and commuting statistics

Visualizing curved spacetime

I present a way to visualize the concept of curved spacetime. The result is a curved surface with local coordinate systems (Minkowski Systems) living on it, giving the local directions of space and time. Relative to these systems, special relativity holds. The method can be used to visualize gravitational time dilation, the horizon of black holes, and cosmological models. The idea underlying the illustrations is first to specify a field of timelike four-velocities. Then, at every point, one performs a coordinate transformation to a local Minkowski system comoving with the given four-velocity. In the local system, the sign of the spatial part of the metric is flipped to create a new metric of Euclidean signature. The new positive definite metric, called the absolute metric, can be covariantly related to the original Lorentzian metric. For the special case of a 2-dimensional original metric, the absolute metric may be embedded in 3-dimensional Euclidean space as a curved surface.Comment: 15 pages, 20 figure