Profiles, Use, and Perceptions of Singapore Multiple Credit Cardholders

This study analyzes Singapore’s diverse cardholders in search of variations among demographic groups, credit card profiles, and their perceptions with regards to credit card ownership and use, it then discusses possible reasons governing Singaporeans’ credit card ownership and use. A survey was conducted (n = 636), decision trees were then constructed using Chi-square automatic interaction detection algorithm (CHAID) and SPSS software AnswerTree to examine the association between the number of credit cards (target variable) and the demographic characteristics, perceptions and other credit card related variables. The number of credit cards was found to be significantly influenced by income and gender as well as perceptions that include “credit card leads to overspending”, “savings as payment source”, “unreasonable interest rates”, “credit card as status symbol”. The number of credit cards was also affected by credit card related variables such as missing payments sometimes, frequency of use, entertainment expenditures, and petrol purchase. This research provides an in-depth understanding of Singaporean multiple cardholders, thus it is useful in designing marketing strategies for card-issuers as well as anti-debt strategies for policy-makers in Singapore. Despite the importance of consumer credit, virtually no literature or research exists on the ownership and use of credit cards in Singapore, so this paper intends to close this gap. Further, by combining the demographics, cardholders’ profiles and usage patterns with the respondents’ perceptions concerning credit card ownership and use, our study offers a richer analysis to explain consumer behavior than previous literatures.Credit card ownership, credit card use, credit revolving, credit debts, decision tree, Singapore

Fundamental study of transpiration cooling

Isothermal and non-isothermal pressure drop data and heat transfer data generated on porous 304L stainless steel wire forms, sintered spherical stainless steel powder, and sintered spherical OFHC copper powder are reported and correlated. Pressure drop data was collected over a temperature range from 500 R to 2000 R and heat transfer data collected over a heat flux range from 5 to 15 BTU/in2/sec. It was found that flow data could be correlated independently of transpirant temperature and type (i.e., H2, N2). It was also found that no simple relation between heat transfer coefficient and specimen porosity was obtainable

Fracture Toughness of Fibrous Membranes

Random fibrous networks exist in both natural biological and engineering materials. While the nonlinear deformation of fibrous networks has been extensively studied, the understanding of their fracture behaviour is still incomplete. To study the fracture toughness of fibrous materials, the near-tip region is crucial because failure mechanisms such as fibril rupture occur in this region. The consideration of this region in fracture studies is, however, a difficult task because it involves microscopic mechanical responses at a small length scale. This paper extends our previous finite element analysis by incorporating the microscopic responses into a macroscopic domain by using a submodeling technique. The detailed study of microstructures at crack tips show a stochastic toughness of membranes due to the random nature of fibrous networks. Further, the sizes of crack tip region, which are sufficient to provide a reasonable prediction of fracture behaviour in a specific type of fibrous network, were presented. Future work includes improving the current linear assumption in the macroscopic models to become nonlinear

The stability of drop shapes for translation at zero Reynolds number through a quiescent fluid

Boundary-integral calculations are used to investigate the evolution of the shape of an initially nonspherical drop that translates at zero Reynolds through a quiescent, unbounded fluid. For finite capillary numbers, it is shown that the drop reverts to a sphere, provided the initial deformation is not too large. However, drops that are initially deformed to a greater extent are shown to deform continuously, forming an elongated shape with a tail when initially prolate, and a flattened shape with a cavity at the rear when initially oblate. The critical degree of deformation decreases as the capillary number increases and appears to be consistent with the results of Kojima et al. [Phys. Fluids 27, 19 (1984)], who showed that the spherical drop is unstable to infinitesimal disturbances in the limit Ca=∞

Electronic states and optical properties of PbSe nanorods and nanowires

A theory of the electronic structure and excitonic absorption spectra of PbS and PbSe nanowires and nanorods in the framework of a four-band effective mass model is presented. Calculations conducted for PbSe show that dielectric contrast dramatically strengthens the exciton binding in narrow nanowires and nanorods. However, the self-interaction energies of the electron and hole nearly cancel the Coulomb binding, and as a result the optical absorption spectra are practically unaffected by the strong dielectric contrast between PbSe and the surrounding medium. Measurements of the size-dependent absorption spectra of colloidal PbSe nanorods are also presented. Using room-temperature energy-band parameters extracted from the optical spectra of spherical PbSe nanocrystals, the theory provides good quantitative agreement with the measured spectra.Comment: 35 pages, 12 figure

Review: Consumption-stage food waste reduction interventions - What works and how to design better interventions

Food waste prevention has become an issue of international concern, with Sustainable Development Goal 12.3 aiming to halve per capita global food waste at the retail and consumer levels by 2030. However there is no review that has considered the effectiveness of interventions aimed at preventing food waste in the consumption stages of the food system. This significant gap, if filled, could help support those working to reduce food waste in the developed world, providing knowledge of what interventions are specifically effective at preventing food waste. This paper fills this gap, identifying and summarizing food-waste prevention interventions at the consumption/consumer stage of the supply chain via a rapid review of global academic literature from 2006 to 2017. We identify 17 applied interventions that claim to have achieved food waste reductions. Of these, 13 quantified food waste reductions. Interventions that changed the size or type of plates were shown to be effective (up to 57% food waste reduction) in hospitality environments. Changing nutritional guidelines in schools were reported to reduce vegetable waste by up to 28%, indicating that healthy diets can be part of food waste reduction strategies. Information campaigns were also shown to be effective with up to 28% food waste reduction in a small sample size intervention. Cooking classes, fridge cameras, food sharing apps, advertising and information sharing were all reported as being effective but with little or no robust evidence provided. This is worrying as all these methods are now being proposed as approaches to reduce food waste and, except for a few studies, there is no reproducible quantified evidence to assure credibility or success. To strengthen current results, a greater number of longitudinal and larger sample size intervention studies are required. To inform future intervention studies, this paper proposes a standardised guideline, which consists of: (1) intervention design; (2) monitoring and measurement; (3) moderation and mediation; (4) reporting; (5) systemic effects. Given the importance of food-waste reduction, the findings of this review highlight a significant evidence gap, meaning that it is difficult to make evidence-based decisions to prevent or reduce consumption-stage food waste in a cost-effective manner

Parts verification for multi-level-dependent demand manufacturing systems: a recognition and classification structure

This research has developed and implemented a part recognition and classification structure to execute parts verification in a multi-level dependent demand manufacturing system. The part recognition algorithm enables the parent and child relationship between parts to be recognised in a finite-capacitated manufacturing system. This algorithm was developed using SIMAN simulation language and implemented in a multi-level dependent demand manufacturing simulation model. The part classification structure enables the modelling of a multi-level dependent demand manufacturing between parts to be carried out effectively. The part classification structure was programmed using Visual Basic Application (VBA) and was integrated to the work-to-list generated from a simulated MRP model. This part classification structure was then implemented in the multi-level dependent demand manufacturing simulation model. Two stages of implementation, namely parameterisation and execution, of the part recognition and classification structure were carried out. A real case study was used and five detail steps of execution were processed. Simulation experiments and MRP were run to verify and validate the part recognition and classification structure. The results led to the conclusion that implementation of the recognition and classification structure has effectively verified the correct parts and sub-assemblies used for the correct product and order. No parts and sub-assemblies shortages were found, and the quantity required was produced. The scheduled release for some orders was delayed due to overload of the required resources. When the loading is normal, all scheduled release timing is adhered to. The recognition and classification structure has a robust design; hence it can be easily adapted to new systems parameter to study a different or more complex case

Developing and applying a user-centered model for the design and implementation of information visualization tools

The objective of this paper is to show how approaches for user-centered information visualization design and development are being applied in the context of healthcare where users are not familiar with information visualization techniques. We base our design methods on user-centered frameworks in which 'prototyping' plays an important role in the process. We modify existing approaches to involve prototyping at an early stage of the process as the problem domain is assessed. We believe this to be essential, as it increases users' awareness of what information visualization techniques can offer them and that it enables users to participate more effectively in later stages of the design and development process. This also acts as a stimulus for engagement. The problem domain analysis stage of a pilot study using this approach is presented, in which techniques are being collaboratively developed with domain users from a healthcare institution. Our results suggest that this approach has engaged users, who are subsequently able to apply generic information visualization concepts to their domains and as a result are better equipped to take part in the subsequent collaborative design and development process

Statistical Basis for Predicting Technological Progress

Forecasting technological progress is of great interest to engineers, policy makers, and private investors. Several models have been proposed for predicting technological improvement, but how well do these models perform? An early hypothesis made by Theodore Wright in 1936 is that cost decreases as a power law of cumulative production. An alternative hypothesis is Moore's law, which can be generalized to say that technologies improve exponentially with time. Other alternatives were proposed by Goddard, Sinclair et al., and Nordhaus. These hypotheses have not previously been rigorously tested. Using a new database on the cost and production of 62 different technologies, which is the most expansive of its kind, we test the ability of six different postulated laws to predict future costs. Our approach involves hindcasting and developing a statistical model to rank the performance of the postulated laws. Wright's law produces the best forecasts, but Moore's law is not far behind. We discover a previously unobserved regularity that production tends to increase exponentially. A combination of an exponential decrease in cost and an exponential increase in production would make Moore's law and Wright's law indistinguishable, as originally pointed out by Sahal. We show for the first time that these regularities are observed in data to such a degree that the performance of these two laws is nearly tied. Our results show that technological progress is forecastable, with the square root of the logarithmic error growing linearly with the forecasting horizon at a typical rate of 2.5% per year. These results have implications for theories of technological change, and assessments of candidate technologies and policies for climate change mitigation