Survey of Spatio-Temporal Databases

Spatio-temporal databases aim to support extensions to existing models of Spatial Information Systems (SIS) to include time in order to better describe our dynamic environment. Although interest into this area has increased in the past decade, a number of important issues remain to be investigated. With the advances made in temporal database research, we can expect a more unified approach towards aspatial temporal data in SIS and a wider discussion on spatio-temporal data models. This paper provides an overview of previous achievements within the field and highlights areas currently receiving or requiring further investigation.     

Using fuzzy logic to match strings in documents

This paper describes a new method that utilizes technology from soft computing to understand words after any OCR software system generated the proper database. First, the problem will be defined very precisely, and then, the algorithm for solving the problem of recognizing words will be presented. Finally, examples are provided to show how the algorithm is applied to recognize different types of words. © 2001 John Wiley & Sons, Inc.     

Effect of time-periodic boundary temperatures/body force on Rayleigh–Benard convection in a ferromagnetic fluid

Summary.  We discuss the thermal instability in a layer of a ferromagnetic fluid when the boundaries of the layer are subjected to synchronous/asynchronous imposed time-periodic boundary temperatures (ITBT)/time–periodic body force (TBF). Only infinitesimal disturbances are considered. The Venezian approach is adopted in arriving at the critical Rayleigh and wave numbers for small amplitudes of ITBT. A perturbation solution in powers of the amplitude of the applied temperature field is obtained. When the ITBT at the two walls are synchronized then, for moderate frequency values, the role of magnetization in inducing sub-critical instabilities is delineated. A similar role is shown to be played by the Prandtl number. The magnetization parameters and Prandtl number have the opposite effect at large frequencies. The system is most stable when the ITBT is asynchronous. The effect of TBF on the onset of convection is found to be qualitatively similar to the effect of an asynchronous ITBT. Low Prandtl number fluids are shown to be more easily vulnerable to destabilization by TBF compared to very large Prandtl number fluids. The problem has relevance in many ferromagnetic fluid applications wherein regulation of thermal convection is called for. Received February 19, 2001; revised October 25, 2002 Published online: April 17, 2003 The work was supported by the UGC – DSA program being implemented at the Department of Mathematics, Bangalore University, India. A. Abraham would like to acknowledge the support of the Bishop Cotton Women's Christian College administration in deputing her to the Ph. D. program. The authors are most grateful to the referees and to Prof. D. Poulikakos for helpful comments and encouragement.     

Cost-Benefit Model for the Construction of Tornado Shelters

Tornadoes have been identified as one of the leading causes of death and injuries among natural disasters in the United States. Shelters play an important role in tornado mitigation efforts, since tornado-related mortality and injury rates are higher when tornado shelters are not available. This paper describes a methodology to address the viability of construction of tornado shelters in areas which have significant tornado hazards. A cost-benefit model that estimates the relative advantages of three tornado shelter construction strategies was developed and tested. The model accounts for factors such as probability of tornado occurrence, historical death and injury rates, economic incentives, and local construction and maintenance costs. The implications of factors such as useful life period, discount rate, and occupancy on the viability of the shelter were also studied. Relevance of this model to decision makers, as well as future needs for the model, is discussed.     

Effect of drying methods on the flavour quality of marjoram (Oreganum majorana L.)

Fresh marjoram volatiles contained mostly (97%) monoterpenes and to a small extent (3%) sesquiterpenes. The impact of drying methods, namely, convection and microwave drying on the flavour quality of the herb was studied. Cis-sabinene hydrate, trans-sabinene hydrate and terpinen-4-ol were found to be the major components responsible for the characteristic flavour of the herb. The Indian marjoram contained more of cis-sabinene hydrate (23.6%) compared to any other sample referred to in the literature and this compound was retained in the convection and microwave (175 W) dried samples to a great extent. Convection drying at ～45°C preserved the flavour quality of marjoram better than microwave drying.     

Microwave exfoliated reduced graphene oxide epoxy nanocomposites for high performance applications

Graphene has captured the attention of scientific community due to recently emerging high performance applications. Hence, studying its reinforcing effects on epoxy resin is a significant step. In this study, microwave exfoliated reduced graphene oxide (MERGO) was prepared from natural graphite for subsequent fabrication of epoxy nanocomposites using triethylenetetramine (TETA) as a curing agent via in-situ polymerization. Thermogravimetric analysis (TGA), X-ray diffraction (XRD), Raman spectroscopy, Fourier transform infrared spectroscopy (FTIR), C¹³ NMR spectroscopy, X-ray photoelectron spectroscopy (XPS) and ultraviolet–visible (UV–vis) spectroscopy were employed to confirm the simultaneous reduction and exfoliation of graphene oxide. The reinforcing effect of MERGO on epoxy resin was explored by investigating its static mechanical properties and dynamic mechanical analysis (DMA) at MERGO loadings of 0 to 0.5 phr. The micro-structure of epoxy/MERGO nanocomposites was investigated using scanning electron microscope (SEM), transmission electron microscope (TEM) and XRD techniques. The present work reports an enhancement of 32%, 103% and 85% in tensile, impact and flexural strength respectively of epoxy by the addition of even 0.25 phr MERGO. At this loading elastic and flexural moduli also increased by 10% and 65%, respectively. Single-edge-notch three-point-Bending (SEN-TPB) fracture toughness (K_IC) measurements were carried out where a 63% increase was observed by the introduction of 0.25 phr MERGO. The interfacial interactions brought about by graphene also benefited the dynamic mechanical properties to a large extent in the form of a significant enhancement in storage modulus and slightly improved glass transition temperature. Considerable improvements were also detected in dielectric properties. The epoxy nanocomposite also attained an ac conductivity of 10⁻⁵ S/m and a remarkable increase in dielectric constant. The simple and cost effective way of graphene synthesis for the fabrication of epoxy/MERGO nanocomposites may be extended to the preparation of other MERGO based polymer nanocomposites. This remarkable class of materials has thrown open enormous opportunities for developing conductive adhesives and in microelectronics.     

Utilising robotic process automation technologies for streamlining the additive manufacturing design workflow

This paper proposes a framework that utilises robotic process automation (RPA) technologies within the additive manufacturing (AM) design workflow to make the product development process more efficient. A commercial RPA platform is employed to create an automated workflow, which is capable of considering multiple AM process configurations. The main objective is to ensure that AM process cost and time requirements may be reliably calculated for any Computer-Aided Design (CAD) part model and multiple process configurations via simulation, with minimal human interaction. The proposed automated workflow was tested on a realistic case scenario and was compared against a standard conventional AM workflow.     

Modelling of synthesis of waste cooking oil methyl esters by artificial neural network and response surface methodology

This present study was carried out to investigate the application of artificial neural network (ANN) and response surface methodology (RSM) as modelling tools for predicting the waste cooking oil methyl esters (WCOME) yield obtained from alkali-catalysed methanolysis of waste cooking oil (WCO). The impact of process parameters involved was studied by a central composite rotatable design. A comparison of the two developed models for the methanolysis process was carried out based on pertinent statistical parameters. The calculated values of coefficient of determination (R²) of 0.9950 and the average absolute deviation (AAD) of 0.4930 for the ANN model compared with R² of 0.9843 and AAD of 0.9376 for the RSM model demonstrated that the ANN model was more accurate than the RSM model. The actual maximum WCOME yield of 94?wt% was obtained at a reaction temperature of 55°C, a catalyst amount of 1?w/v, a reaction time of 70 min and a methanol-to-oil ratio of 6:1.

Abbreviations/Nomenclature CV: coefficient of variance; FFA: free-fatty acid; R: correlation coefficient; R²: coefficient of determination