The Application of Digital Photogrammetric Techniques and Aerial Photography to the Preservation of Archaeological Detail. Case Study: The Copney Stone Circle Complex, Co. Tyrone, N. Ireland

The Copney Stone Circle Complex, Co. Tyrone, N. Ireland, is an important Bronze Age site forming part of the Mid-Ulster Stone Circle Complex. The Environment Service: Historic Monuments and Buildings (ESHMB) initiated a program of bog-clearance in August 1994 to excavate the stone circles. This work was completed by October 1994 and the excavated site was surveyed in August 1995. Almost immediately, the rate at which the stones forming the circles were breaking down was noted and a program of study initiated to make recommendations upon the conservation of this important site. Digital photogrammetric techniques were applied to aerial images of the stone circles and digital terrain models created from the images at a range of scales. These provide base data sets for comparison with identical surveys to be completed in successive years and will allow the rate of deterioration, and the areas most affected, of the circles to be determined. In addition, a 2D analysis of the stones provides an accurate analysis of the absolute 2D dimensions of the stones for rapid desktop computer analysis by researchers remote from the digital photogrammetric workstation used in the survey.

The products of this work are readily incorporated into web sites, educational packages and databases. The technique provides a rapid and user friendly method of presentation of a large body of information and measurements, and a reliable method of storage of the information from Copney should it become necessary to re-cover the site.

Artificial Neural Network for Compositional Ionic Liquid Viscosity Prediction

Being a new generation of green solvents and high-tech reaction media of the future, ionic liquids have increasingly attracted much attention. Of particular interest in this context are room temperature ionic liquids (in short as ILs in this paper). Due to the relatively high viscosity, ILs is expected to be used in the form of solvent diluted mixture with reduced viscosity in industrial application, where predicting the viscosity of IL mixture has been an important research issue. Different IL mixture and many modelling approaches have been investigated. The objective of this study is to provide an alternative model approach using soft computing technique, i.e., artificial neural network (ANN) model, to predict the compositional viscosity of binary mixtures of ILs [C _n-mim][NTf ₂] with n=4, 6, 8, 10 in methanol and ethanol over the entire range of molar fraction at a broad range of temperatures from T=293.0-328.0K. The results show that the proposed ANN model provides alternative way to predict compositional viscosity successfully with highly improved accuracy and also show its potential to be extensively utilized to predict compositional viscosity taking account of IL alkyl chain length, as well as temperature and compositions simultaneously, i.e., more complex intermolecular interactions between components in which it would be hard or impossible to establish the analytical model. This illustrates the potential application of ANN in the case that the physical and thermodynamic properties are highly non-linear or too complex. © 2012 Copyright the authors.

Artificial neural network model to predict compositional viscosity over a broad range of temperatures

The objective of this study is to provide an alternative model approach, i.e., artificial neural network (ANN) model, to predict the compositional viscosity of binary mixtures of room temperature ionic liquids (in short as ILs) [C _n-mim] [NTf ₂] with n=4, 6, 8, 10 in methanol and ethanol over the entire range of molar fraction at a broad range of temperatures from T=293.0328.0K. The results show that the proposed ANN model provides alternative way to predict compositional viscosity successfully with highly improved accuracy and also show its potential to be extensively utilized to predict compositional viscosity over a wide range of temperatures and more complex viscosity compositions, i.e., more complex intermolecular interactions between components in which it would be hard or impossible to establish the analytical model. © 2010 IEEE.

Simultaneous biosorption of methylene blue and trivalent chromium onto olive stone

In this work, olive stone (OS) was utilized to investigate its capacity as biosorbent for methylene blue (MB) and Cr(III), which are usually present in textile industry effluents. Equilibrium and kinetic experiments were performed in batch experiments. The biosorption process followed pseudo-second-order kinetics. The equilibrium data were fitted with several models, but Langmuir and Sips models best reproduced the experimental results. Maximum biosorption capacities were 3.296 mg/g (0.0116 mmol/g) and 4.990 mg/g (0.0960 mmol/g) for MB and Cr(III), respectively. Several operation variables, such as
biosorbent mass, flow rate, and initial concentration on the removal of dye and metal, were evaluated in column system. The removal efficiency improved as OS mass increased and decreased when flow rate and initial concentration increased. Also, MB uptake was substantially decreased by increasing the initial concentration of Cr(III), ranging from 6.09 to 2.75 mg/g. These results show that the presence of Cr(III) significantly modifies the biosorption capacity of MB by the OS. These results suggest that OS is a potential low-cost food industry waste for textile industry wastewater treatment.

Mechanism of Alizarin Red S and Methylene Blue Biosorption onto Olive Stone: Isotherm study in Single and Binary Systems

The biosorption process of anionic dye Alizarin Red S (ARS) and cationic dye methylene blue (MB) as a function of contact time, initial concentration and solution pH onto olive stone (OS) biomass has been investigated. Equilibrium biosorption isotherms in single and binary systems and kinetics in batch mode were also examined. The kinetic data of the two dyes were better described by the pseudo second-order model. At low concentration, ARS dye appeared to follow a two-step diffusion process, while MB dye followed a three-step diffusion process. The biosorption experimental data for ARS and MB dyes were well suited to the Redlich-Peterson isotherm. The maximum biosorption of ARS dye, qmax = 16.10 mg/g, was obtained at pH 3.28 and the maximum biosorption of MB dye, qmax = 13.20 mg/g, was observed at basic pH values. In the binary system, it was indicated that the MB dye diffuses firstly inside the biosorbent particle and occupies the biosorption sites forming a monodentate complex and then the ARS dye enters and can only bind to untaken sites; forms a tridentate complex with OS active sites.

Non-parametric bill of quantities estimation of concrete road bridges' superstructure: an artificial neural networks approach

Bridge construction responds to the need for environmentally friendly design of motorways and facilitates the passage through sensitive natural areas and the bypassing of urban areas. However, according to numerous research studies, bridge construction presents substantial budget overruns. Therefore, it is necessary early in the planning process for the decision makers to have reliable estimates of the final cost based on previously constructed projects. At the same time, the current European financial crisis reduces the available capital for investments and financial institutions are even less willing to finance transportation infrastructure. Consequently, it is even more necessary today to estimate the budget of high-cost construction projects -such as road bridges- with reasonable accuracy, in order for the state funds to be invested with lower risk and the projects to be designed with the highest possible efficiency. In this paper, a Bill-of-Quantities (BoQ) estimation tool for road bridges is developed in order to support the decisions made at the preliminary planning and design stages of highways. Specifically, a Feed-Forward Artificial Neural Network (ANN) with a hidden layer of 10 neurons is trained to predict the superstructure material quantities (concrete, pre-stressed steel and reinforcing steel) using the width of the deck, the adjusted length of span or cantilever and the type of the bridge as input variables. The training dataset includes actual data from 68 recently constructed concrete motorway bridges in Greece. According to the relevant metrics, the developed model captures very well the complex interrelations in the dataset and demonstrates strong generalisation capability. Furthermore, it outperforms the linear regression models developed for the same dataset. Therefore, the proposed cost estimation model stands as a useful and reliable tool for the construction industry as it enables planners to reach informed decisions for technical and economic planning of concrete bridge projects from their early implementation stages.

The Middle Stone Age of Eastern Africa

The Middle Stone Age (MSA) covers the evolution, emergence, and dispersal of Homo sapiens. This article focuses on archaeological data and on published material from key stratified sites with some form of geochronological control from across eastern Africa. The MSA is often characterised by a shift from handaxe production towards discoidal and Levallois techniques. Although evidence for the controlled use of fire remains minimal, it seems likely that MSA hominins used it, as well as being highly skilled in working stone and probably bone and wood. MSA hominins appear to have exploited a range of different ecozones and many MSA sites are focused on ecotones, maximising access to resources. Over time, use of rockshelters and caves also seems to have increased. Although much work remains, the MSA is presently one of the most exciting and dynamic periods in the study of human evolution.

The inventorying of building stone performance-in-use to assess susceptibility to decay

The Natural Stone Database for Northern Ireland was constructed to address the paucity of information available to stone conservation practitioners within the region. Almost 2000 listed buildings and monuments were surveyed over three years to produce an interactive GIS database. This contained information on stone sources, together with details of stone condition and decay processes. This paper uses elements of this GIS to investigate stone decay patterns across Northern Ireland. The results demonstrate that as the level of stone decay increases, so does the proportion of buildings with sandstone as the primary stone type. It appears that a
higher open porosity level combined with Northern Ireland’s wetter climate and maritime location leads to rapid wetting and drying cycles within sandstones. This is coupled with the ingress and crystallisation of marine and other salts within stone pores leading to considerably
higher rates of decay than for any other stone type.