GIS and development control system for a local authority in Malaysia

The process of development control involves a technique for the systematic compilation of expert quantitative analysis and qualitative assessment of project land use and property development viability, including its effect on the surrounding area, and the presentation of results in a way that enables the importance of the predicted results, and the scope of modifying or mitigating them to be properly evaluated by the relevant decision making body before a planning permission is rendered. Taking the local authorities in Malaysia as an example, this paper will discuss and demonstrate the development of a GIS database and its integration and application for development and building control. The first part of the paper examines the functions of local authorities particularly in the context of development control. In this study, the procedure involved in granting a planning permission as well as enforcement becomes the main focus because it determines the bulk of the system design. The study identifies seven sub-systems namely planning permission, building control, planning enforcement, geospatial database, information kiosk, document processing and presentation sub-systems. The system is developed using a combination of office automation, CAD, GIS, multimedia and other software packages. This paper will focus on the development of the GIS for the purpose of development control. The components of the GIS database include land information, buildings, existing developments, planning information, development plans, utilities, community facilities, transportation, environment and the socio-economy database. The GIS database will be used at every stage of development control, for example, in initial discussions, registration, invitation of objections, the development control process, the consideration by Technical Committee and the consideration by Planning Committee. It is anticipated that the GIS database could be used by many parties involved in the process as a reference point in evaluating a planning submission. Having access to the database will provide flexibility in assessing a proposed development and deciding on the overall urban growth management programme in the most cost-effective manner. The system will also provide transparency and consistency in the development control procedure.     

Partial Identification in Triangular Systems of Equations With Binary Dependent Variables

This paper studies the special case of the triangular system of equations in Vytlacil and Yildiz (2007), where both dependent variables are binary but without imposing the restrictive support condition required by Vytlacil and Yildiz (2007) for identification of the average structural function (ASF) and the average treatment effect (ATE). Under weak regularity conditions, we derive upper and lower bounds on the ASF and the ATE. We show further that the bounds on the ASF and ATE are sharp under some further regularity conditions and an additional restriction on the support of the covariates and the instrument.     

Minimal Neighbor Designs in Linear Blocks

Neighbor designs are useful to neutralize the neighbor effects. In literature, most of the constructed neighbor designs are in circular blocks but linear blocks have more practical application in field experiments. In this article, some infinite series of minimal neighbor designs are constructed in proper linear blocks. There are many situations where minimal neighbor designs cannot be constructed in proper linear blocks. To overcome this problem neighbor designs in improper linear blocks and GN₂-designs in proper linear blocks are constructed.     

Construction of Neighbor-Balanced Designs in Linear Blocks

Neighbor-balanced designs are useful to remove the neighbor effects in experiments where the performance of a treatment is affected by the treatments applied to its adjacent neighbors. In this article, neighbor-balanced designs are constructed in linear blocks of (i) equal sizes and (ii) two different sizes k ₁ and k ₂.     

New invariant and consistent chi-squared type goodness-of-fit tests for multivariate normality and a related comparative simulation study

ABSTRACT

New invariant and consistent goodness-of-fit tests for multivariate normality are introduced. Tests are based on the Karhunen–Loève transformation of a multidimensional sample from a population. A comparison of simulated powers of tests and other well-known tests with respect to some alternatives is given. The simulation study demonstrates that power of the proposed McCull test almost does not depend on the number of grouping cells. The test shows an advantage over other chi-squared type tests. However, averaged over all of the simulated conditions examined in this article, the Anderson–Darling type and the Cramer–von Mises type tests seem to be the best.     

One-Hit Models of Carcinogenesis: Conservative or Not?

One-hit formulas are widely believed to be "conservative" when used to analyze carcinogenesis bioassays, in the sense that they will rarely underestimate risks of cancer at low exposures. Such formulas are generally applied to the lifetime incidence of cancer at a specific site, with risks estimated from animal data at zero dose (control), and two or more additional doses that are appreciable fractions of a maximum tolerated dose. No empirical study has demonstrated that the one-hit formula is conservative in the sense described. The Carcinogenesis Bioassay Database System contains data on 1212 separate bioassays of 308 chemical substances tested at exactly three evaluable doses. These provided sufficient data to examine 8432 specific combinations of cancer site with sex, species, and chemical. For each of these we fitted a one-hit formula to the zero and maximum dose data points, then examined the relation of the fitted curve to the incidence rate observed at the mid-dose, with and without adjustment for intercurrent mortality. Both underestimates and overestimates of risk at mid-dose occurred substantially more often than expected by chance. We cannot tell whether such underestimates would occur at lower doses, but offer six biological reasons why underestimates might be expected. In a high percentage of animal bioassays, the one-hit formula is not conservative when applied in the usual way to animal data. It remains possible that the one-hit formula may indeed be conservative at sufficiently low doses (below the observational range), but the usual procedure, applied to the usual dose range, can be nonconservative in estimating the slope of the formula at such low doses. Risk assessments for regulation of carcinogens should incorporate some measure of additional uncertainty.     

On the use ofR-estimators in analyzing repeated measures incomplete block clinical trials with baseline values as covariates

Summary This article develops a rank based inference using a dispersion function for repeated measures incomplete block designs (IBD) with baseline values as covariates. Scores, Waldtype and drop in dispersion tests are developed for testing slope equals zero and equality of treatment effects. Multiple comparison procedures are also developed usingR-estimators which are obtained by minimizing a piece-wise linear dispersion function. A consistent estimator of a scale parameter, which appears in test statistic as a standardizing constant, is discussed. A data set from pharmaceutical research, which compares 12μg and 24μg formoterol (asthma drug) solution aerosol with a placebo treatment, is analyzed using the result of this article. Part of this work was completed when the author was a faculty member at Worcester Polytechnic Institute. Worcester, Massachusetts. The view expressed in this article are those of the author and not those of the United States. Food and Drug Administration.     

Providing sex education to adolescents in rural Bangladesh: experiences from BRAC

In 1995, the Bangladesh Rural Advancement Committee set up an Adolescent Reproductive Health Education (ARHE) program to provide information about reproductive health to adolescents in rural areas. This article explores the impact of the ARHE on adolescent girls and boys, their parents, and community members among rural areas in Bangladesh. Drawing on data from the field research conducted among the target audience, it is noted that ARHE has mobilized the community. It helped break the silence and shame about sensitive topics, such as menstruation, family planning methods, sexually transmitted diseases and HIV/AIDS. Subsequently, these developments have affected relationships between adolescents and their parents, and among adolescents themselves. Moreover, the diffusion of knowledge as a result of the ARHE is occurring in the context of a wider process affecting rural areas of Bangladesh, involving the media, books, exposure to urban and nontraditional ways of life, and schooling. The need for additional research, with a greater focus on adolescents who participate in the program and go on to marry, is highlighted.     

Detection of outliers in high-dimensional data using nu-support vector regression

Support Vector Regression (SVR) is gaining in popularity in the detection of outliers and classification problems in high-dimensional data (HDD) as this technique does not require the data to be of full rank. In real application, most of the data are of high dimensional. Classification of high-dimensional data is needed in applied sciences, in particular, as it is important to discriminate cancerous cells from non-cancerous cells. It is also imperative that outliers are identified before constructing a model on the relationship between the dependent and independent variables to avoid misleading interpretations about the fitting of a model. The standard SVR and the μ-ε-SVR are able to detect outliers; however, they are computationally expensive. The fixed parameters support vector regression (FP-ε-SVR) was put forward to remedy this issue. However, the FP-ε-SVR using ε-SVR is not very successful in identifying outliers. In this article, we propose an alternative method to detect outliers i.e. by employing nu-SVR. The merit of our proposed method is confirmed by three real examples and the Monte Carlo simulation. The results show that our proposed nu-SVR method is very successful in identifying outliers under a variety of situations, and with less computational running time.     

Perturbed nuptiality,delayed fertility: childbirth effects of Covid19

Journal of Population Research - An aspect of the Covid-19 pandemic that merits attention is its effects on marriage and childbirth. Although the direct fertility effects of people getting the...