A Fast and Robust Protocol for Reconstruction and Re-Enactment of Historical Sites

This research proposes a novel reconstruction protocol for restoring missing surfaces and low-quality edges and shapes in photos of artifacts at historical sites. The protocol starts with the extraction of a cloud of points. This extraction process is based on four subordinate algorithms, which differ in the robustness and amount of resultant. Moreover, they use different -but complementary- accuracy to some related features and to the way they build a quality mesh. The performance of our proposed protocol is compared with other state-of-the-art algorithms and toolkits. The statistical analysis shows that our algorithm significantly outperforms its rivals in the resultant quality of its object files used to reconstruct the desired model.

Application of Adaptive Neural Network Algorithms for Determination of Salt Composition of Waters Using Laser Spectroscopy

In this study, a comparative analysis of the approaches associated with the use of neural network algorithms for effective solution of a complex inverse problem – the problem of identifying and determining the individual concentrations of inorganic salts in multicomponent aqueous solutions by the spectra of Raman scattering of light – is performed. It is shown that application of artificial neural networks provides the average accuracy of determination of concentration of each salt no worse than 0.025 M. The results of comparative analysis of input data compression methods are presented. It is demonstrated that use of uniform aggregation of input features allows decreasing the error of determination of individual concentrations of components by 16-18% on the average.

Using Artificial Neural Networks for Optical Imaging of Fluorescent Biomarkers

The article presents the results of the application of artificial neural networks to separate the fluorescent contribution of nanodiamonds used as biomarkers, adsorbents and carriers of drugs in biomedicine, from a fluorescent background of own biological fluorophores. The principal possibility of solving this problem is shown. Use of neural network architecture let to detect fluorescence of nanodiamonds against the background autofluorescence of egg white with high accuracy - better than 3 ug/ml.

Temperature Investigations in Two Type of Crimped Connection Using Experimental Determinations

In this paper we make a temperature investigations in two type of superposed crimped connections using experimental determinations. All the samples use 8 copper wire 7.1 x 3 mm2 crimped by two methods: the first method uses one crimp indents and the second is a proposed method with two crimp indents. The ferrule is a parallel one. We study the influence of number and position of crimp indents. The samples are heated in A.C. current at different current values until steady state heating regime. After obtaining of temperature values, we compare them and present the conclusion.

Selecting the Best Sub-Region Indexing the Images in the Case of Weak Segmentation Based On Local Color Histograms

Color Histogram is considered as the oldest method used by CBIR systems for indexing images. In turn, the global histograms do not include the spatial information; this is why the other techniques coming later have attempted to encounter this limitation by involving the segmentation task as a preprocessing step. The weak segmentation is employed by the local histograms while other methods as CCV (Color Coherent Vector) are based on strong segmentation. The indexation based on local histograms consists of splitting the image into N overlapping blocks or sub-regions, and then the histogram of each block is computed. The dissimilarity between two images is reduced, as consequence, to compute the distance between the N local histograms of the both images resulting then in N*N values; generally, the lowest value is taken into account to rank images, that means that the lowest value is that which helps to designate which sub-region utilized to index images of the collection being asked. In this paper, we make under light the local histogram indexation method in the hope to compare the results obtained against those given by the global histogram. We address also another noteworthy issue when Relying on local histograms namely which value, among N*N values, to trust on when comparing images, in other words, which sub-region among the N*N sub-regions on which we base to index images. Based on the results achieved here, it seems that relying on the local histograms, which needs to pose an extra overhead on the system by involving another preprocessing step naming segmentation, does not necessary mean that it produces better results. In addition to that, we have proposed here some ideas to select the local histogram on which we rely on to encode the image rather than relying on the local histogram having lowest distance with the query histograms.

Frequent Itemset Mining Using Rough-Sets

Frequent pattern mining is the process of finding a pattern (a set of items, subsequences, substructures, etc.) that occurs frequently in a data set. It was proposed in the context of frequent itemsets and association rule mining. Frequent pattern mining is used to find inherent regularities in data. What products were often purchased together? Its applications include basket data analysis, cross-marketing, catalog design, sale campaign analysis, Web log (click stream) analysis, and DNA sequence analysis. However, one of the bottlenecks of frequent itemset mining is that as the data increase the amount of time and resources required to mining the data increases at an exponential rate. In this investigation a new algorithm is proposed which can be uses as a pre-processor for frequent itemset mining. FASTER (FeAture SelecTion using Entropy and Rough sets) is a hybrid pre-processor algorithm which utilizes entropy and roughsets to carry out record reduction and feature (attribute) selection respectively. FASTER for frequent itemset mining can produce a speed up of 3.1 times when compared to original algorithm while maintaining an accuracy of 71%.

3D Guidance of Unmanned Aerial Vehicles Using Sliding Mode Approach

This paper presents a 3D guidance scheme for Unmanned Aerial Vehicles (UAVs). The proposed guidance scheme is based on the sliding mode approach using nonlinear sliding manifolds. Generalized 3D kinematic equations are considered here during the design process to cater for the coupling between longitudinal and lateral motions. Sliding mode based guidance scheme is then derived for the multiple-input multiple-output (MIMO) system using the proposed nonlinear manifolds. Instead of traditional sliding surfaces, nonlinear sliding surfaces are proposed here for performance and stability in all flight conditions. In the reaching phase control inputs, the bang-bang terms with signum functions are accompanied with proportional terms in order to reduce the chattering amplitudes. The Proposed 3D guidance scheme is implemented on a 6-degrees-of-freedom (6-dof) simulation of a UAV and simulation results are presented here for different 3D trajectories with and without disturbances.

Temperature Distribution in Friction Stir Welding Using Finite Element Method

During welding, the amount of heat present in weld zones determines the quality of weldment produced. Thus, the heat distribution characteristics and its magnitude in weld zones with respect to process variables such as tool pin-shoulder rotational and traveling speed during welding is analyzed using thermal finite element analyses method. For this purpose, transient thermal finite element analyses are performed to model the temperatures distribution and its quantities in weld-zones with respect to process variables such as rotational speed and traveling speed during welding. Commercially available software Altair HyperWork is used to model three-dimensional tool pin-shoulder vs. workpieces and to simulate the friction stir process. The results show that increasing tool rotational speed, at a constant traveling speed, will increase the amount of heat generated in weld-zones. In contrary, increasing traveling speed, at constant tool pin-shoulder rotational speeds, will reduce the amount of heat generated in weld zones.

Magnetic Properties of Sr-Ferrite Nano-Powder Synthesized by Sol-Gel Auto-Combustion Method

In this paper, strontium ferrite (SrO.6Fe2O3) was synthesized by the sol-gel auto-combustion process. The thermal behavior of powder obtained from self-propagating combustion of initial gel was evaluated by simultaneous differential thermal analysis (DTA) and thermo gravimetric (TG), from room temperature to 1200°C. The as-burnt powder was calcined at various temperatures from 700-900°C to achieve the single-phase Sr-ferrite. Phase composition, morphology and magnetic properties were investigated using X-ray diffraction (XRD), transmission electron microscopy (TEM) and vibrating sample magnetometry (VSM) techniques. Results showed that the single-phase and nano-sized hexagonal strontium ferrite particles were formed at calcination temperature of 800°C with crystallite size of 27 nm and coercivity of 6238 Oe.

Roof Material Detection Based on Object-Based Approach Using WorldView-2 Satellite Imagery

One of the most important tasks in urban remote sensing is the detection of impervious surfaces (IS), such as roofs and roads. However, detection of IS in heterogeneous areas still remains one of the most challenging tasks. In this study, detection of concrete roof using an object-based approach was proposed. A new rule-based classification was developed to detect concrete roof tile. This proposed rule-based classification was applied to WorldView-2 image and results showed that the proposed rule has good potential to predict concrete roof material from WorldView-2 images, with 85% accuracy.

Trends and Prospects for the Development of Georgian Wine Market

The article presents the trends in Georgian wine market development and evaluates the competitive advantages of Georgia to enter the wine market based on its customs, traditions and historical practices combined with modern technologies. In order to analyze the supply of wine, dynamics of vineyard land area and grape varieties are discussed, trends in wine production are presented, trends in export and import are evaluated, local wine market, its micro and macro environments are studied and analyzed based on the interviews with experts and analysis of initial recording materials. For strengthening its position on the international market, the level of competitiveness of Georgian wine is defined, which is evaluated by “ex-ante” and “ex-post” methods, as well as by four basic and two additional factors of the Porter’s diamond method; potential advantages and disadvantages of Georgian wine are revealed. Conclusions are made by identifying the factors that hinder the development of Georgian wine market. Based on the conclusions, relevant recommendations are developed.

The Effect of Solution Density on the Synthesis of Magnesium Borate from Boron-Gypsum

Boron-gypsum is a waste which occurs in the boric acid production process. In this study, the boron content of this waste is evaluated for the use in synthesis of magnesium borates and such evaluation of this kind of waste is useful more than storage or disposal. Magnesium borates, which are a sub-class of boron minerals, are useful additive materials for the industries due to their remarkable thermal and mechanical properties. Magnesium borates were obtained hydrothermally at different temperatures. Novelty of this study is the search of the solution density effects to magnesium borate synthesis process for the increasing the possibility of borongypsum usage as a raw material. After the synthesis process, products are subjected to XRD and FT-IR to identify and characterize their crystal structure, respectively.

Survey to Assess the Feasibility of Executing the Web-Based Collaboration Process Using WBCS

The importance of the formal specification in the software life cycle is barely concealing to anyone. Formal specifications use mathematical notation to describe the properties of information system precisely, without unduly constraining the way in how these properties are achieved. Having a correct and quality software specification is not easy task. This study concerns with how a group of rectifiers can communicate with each other and work to prepare and produce a correct formal software specification. WBCS has been implemented based mainly in the proposed supported cooperative work model and a survey conducted on the existing Webbased collaborative writing tools. This paper aims to assess the feasibility of executing the web-based collaboration process using WBCS. The purpose of conducting this test is to test the system as a whole for functionality and fitness for use based on the evaluation test plan.

Comparison of Fundamental Frequency Model and PWM Based Model of UPFC

Among all FACTS devices, the unified power flow controller (UPFC) is considered to be the most versatile device. This is due to its capability to control all the transmission system parameters (impedance, voltage magnitude, and phase angle). With the growing interest in UPFC, the attention to develop a mathematical model has increased. Several models were introduced for UPFC in literature for different type of studies in power systems. In this paper a novel comparison study between two dynamic models of UPFC with their proposed control strategies.

Possibilistic Aggregations in the Investment Decision Making

This work proposes a fuzzy methodology to support the investment decisions. While choosing among competitive investment projects, the methodology makes ranking of projects using the new aggregation OWA operator – AsPOWA, presented in the environment of possibility uncertainty. For numerical evaluation of the weighting vector associated with the AsPOWA operator the mathematical programming problem is constructed. On the basis of the AsPOWA operator the projects’ group ranking maximum criteria is constructed. The methodology also allows making the most profitable investments into several of the project using the method developed by the authors for discrete possibilistic bicriteria problems. The article provides an example of the investment decision-making that explains the work of the proposed methodology.

Review of Downscaling Methods in Climate Change and Their Role in Hydrological Studies

Recent perceived climate variability raises concerns with unprecedented hydrological phenomena and extremes. Distribution and circulation of the waters of the Earth become increasingly difficult to determine because of additional uncertainty related to anthropogenic emissions. The world wide observed changes in the large-scale hydrological cycle have been related to an increase in the observed temperature over several decades. Although the effect of change in climate on hydrology provides a general picture of possible hydrological global change, new tools and frameworks for modelling hydrological series with nonstationary characteristics at finer scales, are required for assessing climate change impacts. Of the downscaling techniques, dynamic downscaling is usually based on the use of Regional Climate Models (RCMs), which generate finer resolution output based on atmospheric physics over a region using General Circulation Model (GCM) fields as boundary conditions. However, RCMs are not expected to capture the observed spatial precipitation extremes at a fine cell scale or at a basin scale. Statistical downscaling derives a statistical or empirical relationship between the variables simulated by the GCMs, called predictors, and station-scale hydrologic variables, called predictands. The main focus of the paper is on the need for using statistical downscaling techniques for projection of local hydrometeorological variables under climate change scenarios. The projections can be then served as a means of input source to various hydrologic models to obtain streamflow, evapotranspiration, soil moisture and other hydrological variables of interest.

People Participation as Social Capital Form for Realizing Sustainable Ecotourism

As an entity of the tourism system, local communities were considered have better understanding of their region as well as influenced positively or negatively by the tourism activities in the region. This paper aimed to study role of community involvement in the development of ecotourism at Kintamani Bali from two perspectives of view, i.e. participation in the process of initiatives and participation in the utilizing the economic benefits of tourism. Thorough participation as an antecedent of social capital form, the sustainability of ecotourism at Kintamani could be expected.

Antimicrobial Agents Produced by Yeasts

Natural antimicrobials are used to preserve foods that can be found in plants, animals, and microorganisms. Antimicrobial substances are natural or artificial agents that produced by microorganisms or obtained semi/total chemical synthesis are used at low concentrations to inhibit the growth of other microorganisms. Food borne pathogens and spoilage microorganisms are inactivated by the use of antagonistic microorganisms and their metabolites. Yeasts can produce toxic proteins or glycoproteins (toxins) that cause inhibition of sensitive bacteria and yeast species. Antimicrobial substance producing phenotypes belonging different yeast genus were isolated from different sources. Toxins secreted by many yeast strains inhibiting the growth of other yeast strains. These strains show antimicrobial activity, inhibiting the growth of mold and bacteria. The effect of antimicrobial agents produced by yeasts can be extremely fast, and therefore may be used in various treatment procedures. Rapid inhibition of microorganisms is possibly caused by microbial cell membrane lipopolysaccharide binding and in activation (neutralization) effect. Antimicrobial agents inhibit the target cells via different mechanisms of action.

Two Stage Fuzzy Methodology to Evaluate the Credit Risks of Investment Projects

The work proposes a decision support methodology for the credit risk minimization in selection of investment projects. The methodology provides two stages of projects’ evaluation. Preliminary selection of projects with minor credit risks is made using the Expertons Method. The second stage makes ranking of chosen projects using the Possibilistic Discrimination Analysis Method. The latter is a new modification of a well-known Method of Fuzzy Discrimination Analysis.

Generalized Vortex Lattice Method for Predicting Characteristics of Wings with Flap and Aileron Deflection

A generalized vortex lattice method for complex lifting surfaces with flap and aileron deflection is formulated. The method is not restricted by the linearized theory assumption and accounts for all standard geometric lifting surface parameters: camber, taper, sweep, washout, dihedral, in addition to flap and aileron deflection. Thickness is not accounted for since the physical lifting body is replaced by a lattice of panels located on the mean camber surface. This panel lattice setup and the treatment of different wake geometries is what distinguish the present work form the overwhelming majority of previous solutions based on the vortex lattice method. A MATLAB code implementing the proposed formulation is developed and validated by comparing our results to existing experimental and numerical ones and good agreement is demonstrated. It is then used to study the accuracy of the widely used classical vortex-lattice method. It is shown that the classical approach gives good agreement in the clean configuration but is off by as much as 30% when a flap or aileron deflection of 30° is imposed. This discrepancy is mainly due the linearized theory assumption associated with the conventional method. A comparison of the effect of four different wake geometries on the values of aerodynamic coefficients was also carried out and it is found that the choice of the wake shape had very little effect on the results.