A Mahalanobis Distance-based Diversification and Nelder-Mead Simplex Intensification Search Scheme for Continuous Ant Colony Optimization

Ant colony optimization (ACO) and its variants are applied extensively to resolve various continuous optimization problems. As per the various diversification and intensification schemes of ACO for continuous function optimization, researchers generally consider components of multidimensional state space to generate the new search point(s). However, diversifying to a new search space by updating only components of the multidimensional vector may not ensure that the new point is at a significant distance from the current solution. If a minimum distance is not ensured during diversification, then there is always a possibility that the search will end up with reaching only local optimum. Therefore, to overcome such situations, a Mahalanobis distance-based diversification with Nelder-Mead simplex-based search scheme for each ant is proposed for the ACO strategy. A comparative computational run results, based on nine nonlinear standard test problems, confirms that the performance of ACO is improved significantly with the integration of the proposed schemes in the ACO.

A Study on Neural Network Training Algorithm for Multiface Detection in Static Images

This paper reports the study results on neural network training algorithm of numerical optimization techniques multiface detection in static images. The training algorithms involved are scale gradient conjugate backpropagation, conjugate gradient backpropagation with Polak-Riebre updates, conjugate gradient backpropagation with Fletcher-Reeves updates, one secant backpropagation and resilent backpropagation. The final result of each training algorithms for multiface detection application will also be discussed and compared.

Improving Academic Performance Prediction using Voting Technique in Data Mining

In this paper we compare the accuracy of data mining methods to classifying students in order to predicting student-s class grade. These predictions are more useful for identifying weak students and assisting management to take remedial measures at early stages to produce excellent graduate that will graduate at least with second class upper. Firstly we examine single classifiers accuracy on our data set and choose the best one and then ensembles it with a weak classifier to produce simple voting method. We present results show that combining different classifiers outperformed other single classifiers for predicting student performance.

Whole Body CT for a Patient with Sepsis

This study retrospectively investigated the significance of whole body CT (WCT) for patients with sepsis. A medical chart review was retrospectively performed for all patients with systemic inflammatory response syndrome that were treated initially between April 2011 and March 2012. The subjects were divided into a WCT group that underwent WCT on arrival and a control group. Results of this study suggested that WCT for sepsis was useful for elderly patients whose chief complaint or physiological findings could not suggest the anatomical site of infection, to determine the infectious focus and indications/method for surgery, to diagnose the basic diseases associated with opportunistic infections and to evaluate complicated diseases

Corporate Social Responsibility and Values in Innovation Management

Corporate social responsibility (CSR) viewpoint have challenged the traditional perception to understand corporations position. Production- and managerial-centred views are expanding towards reference group-centred policies. Consequently, the significance of new kind of knowledge has emerged. In addition to management of the organisation, the idea of CSR emphasises the importance to recognise the value-expectations of operational environment. It is know that management is often well-aware of corporate social responsibilities, but it is less clear how well these high level goals are understood in practical product design and development work. In this study, the apprehension above proved to be real to some degree. While management was very aware of CSR it was less familiar to designers. The outcome shows that it is essential to raise ethical values and issues higher in corporate communication, if it is wished that they materialize also in products.

Modeling and Simulation of Motion of an Underwater Robot Glider for Shallow-water Ocean Applications

This paper describes the modeling and simulation of an underwater robot glider used in the shallow-water environment. We followed the Equations of motion derived by [2] and simplified dynamic Equations of motion of an underwater glider according to our underwater glider. A simulation code is built and operated in the MATLAB Simulink environment so that we can make improvements to our testing glider design. It may be also used to validate a robot glider design.

Evaluation of Some Chemical Parameters as Potential Determinants of Fresh Water Snails with Special Reference to Medically Important Snails in Egypt

Seasonal survey of freshwater snails in different water courses in Egypt during two successive years included 13 snail species. They represented by Biomphalaria alexandrina, Bulinus truncatus, Physa acuta, Helisoma duryi, Lymnaea natalensis, Planorbis pantries, Cleopatra bulimoides, Lanistes carinatus, Bellamya unicolor, Melanoides tuberculata, Theodoxus niloticus, Succinia cleopatra and Valvata nilotica. B. alexandrina was most abundant during autumn and spring represented by 26and14 snails/site, respectively. B. truncatus was most abundant during winter (7.7and3.6snails/site) of the two years, respectively. L. natalensis was represented by 7snails/site in summer. The tolerance of different snail species to the chemical elements was determined seasonally and correlated to their abundance. In spring, autumn and winter, B. alexandrina was significantly found to live under the highest level of Pb, Cd,Cu, Na, K and Ca concentrations than the other species (p

Enhancing Landfill Gas Production by Methanogenic Sand Layer

Landfill gas, particularly methane is one of the greenhouse gases which contributes to global warming. This paper presents the findings of a study on methane gas production from simulated landfill reactor under saturated conditions. A reactor was constructed to represent a landfill cell of 2.5 m thickness on sandy soil. The reactor was 0.2 m in diameter and 4 m in height. One meter of sand and pebble layer was packed at the bottom of the reactor followed by 2.5 m of solid waste layer and 0.4 m of sand layer as the cover soil. Degradation of waste in the solid waste layer was at acidification stage as indicated by the leachate quality with COD as high as 55,511 mg/L and pH as low as 5.1. However, methanogenic environment was established at the bottom sand layer after one year of operation indicated by pH of 7.2 and methane gas generation. Leachate degradation took place as the leachate moved through the sand layer at an infiltration of rate 0.7 cm/day. This resulted in landfill gas production of 77 mL/day/kg containing 55 to 65% methane. The application of sand layer contributed to the gas production from landfill by an in-situ degradation of leachate in the sand at the bottom of the landfill.

Integrating Computational Intelligence Techniques and Assessment Agents in ELearning Environments

In this contribution an innovative platform is being presented that integrates intelligent agents and evolutionary computation techniques in legacy e-learning environments. It introduces the design and development of a scalable and interoperable integration platform supporting: I) various assessment agents for e-learning environments, II) a specific resource retrieval agent for the provision of additional information from Internet sources matching the needs and profile of the specific user and III) a genetic algorithm designed to extract efficient information (classifying rules) based on the students- answering input data. The agents are implemented in order to provide intelligent assessment services based on computational intelligence techniques such as Bayesian Networks and Genetic Algorithms. The proposed Genetic Algorithm (GA) is used in order to extract efficient information (classifying rules) based on the students- answering input data. The idea of using a GA in order to fulfil this difficult task came from the fact that GAs have been widely used in applications including classification of unknown data. The utilization of new and emerging technologies like web services allows integrating the provided services to any web based legacy e-learning environment.

A Decision Support Model for Bank Branch Location Selection

Location selection is one of the most important decision making process which requires to consider several criteria based on the mission and the strategy. This study-s object is to provide a decision support model in order to help the bank selecting the most appropriate location for a bank-s branch considering a case study in Turkey. The object of the bank is to select the most appropriate city for opening a branch among six alternatives in the South-Eastern of Turkey. The model in this study was consisted of five main criteria which are Demographic, Socio-Economic, Sectoral Employment, Banking and Trade Potential and twenty one subcriteria which represent the bank-s mission and strategy. Because of the multi-criteria structure of the problem and the fuzziness in the comparisons of the criteria, fuzzy AHP is used and for the ranking of the alternatives, TOPSIS method is used.

Design and Development of an MPH Program for Distance Education Delivery

The Master-s of Public Health (MPH) degree is growing in popularity among a number of higher education institutions throughout the world as a distance education graduate program. This paper offers an overview of program design and development strategies that promote successful distance delivery of MPH programs. Design and development challenges are discussed in terms of type of distance delivery, accreditation, student demand, faculty development, user needs, course content, and marketing strategies. The ongoing development of a distance education MPH program at Utah State University will be used to highlight and consider various aspects of this important but challenging process.

Cereals' Products with Red Grape and Walnut Extracts as Functional Foods for Prevention of Kidney Dysfunction

In the present research, two nutraceuticals made from red grape and walnut that showed previously to improve kidney dysfunction were incorporated separately into functional foods' bread made from barley and rice bran. The functional foods were evaluated in rats in which chronic renal failure was induced through feeding diet rich in adenine and phosphate (APD). The evaluation based on assessing kidney function, oxidative stress, inflammatory biomarkers and body weight gain. Results showed induction of chronic kidney failure reflected in significant increase in plasma urea, creatinine, malondialdehyde, tumor necrosis factor- α and low density lipoprotein cholesterol along with significant reduction of plasma albumin, and total antioxidant and creatinine clearance and body weight gain on feeding APD compared to control healthy group. Feeding the functional foods produced amelioration in the different biochemical parameters and body weight gain indicating improvement in kidney function.

Photodegradation of Phenol Red in the Presence of ZnO Nanoparticles

In our recent study, we have used ZnO nanoparticles assisted with UV light irradiation to investigate the photocatalytic degradation of Phenol Red (PR). The ZnO photocatalyst was characterized by X-ray diffraction (XRD), transmission electron microscopy (TEM), specific surface area analysis (BET) and UVvisible spectroscopy. X-ray diffractometry result for the ZnO nanoparticles exhibit normal crystalline phase features. All observed peaks can be indexed to the pure hexagonal wurtzite crystal structures, with the space group of P63mc. There are no other impurities in the diffraction peak. In addition, TEM measurement shows that most of the nanoparticles are rod-like and spherical in shape and fairly monodispersed. A significant degradation of the PR was observed when the catalyst was added into the solution even without the UV light exposure. In addition, the photodegradation increases with the photocatalyst loading. The surface area of the ZnO nanomaterials from the BET measurement was 11.9 m2/g. Besides the photocatalyst loading, the effect of some parameters on the photodegradation efficiency such as initial PR concentration and pH were also studied.

A Comparison of SVM-based Criteria in Evolutionary Method for Gene Selection and Classification of Microarray Data

An evolutionary method whose selection and recombination operations are based on generalization error-bounds of support vector machine (SVM) can select a subset of potentially informative genes for SVM classifier very efficiently [7]. In this paper, we will use the derivative of error-bound (first-order criteria) to select and recombine gene features in the evolutionary process, and compare the performance of the derivative of error-bound with the error-bound itself (zero-order) in the evolutionary process. We also investigate several error-bounds and their derivatives to compare the performance, and find the best criteria for gene selection and classification. We use 7 cancer-related human gene expression datasets to evaluate the performance of the zero-order and first-order criteria of error-bounds. Though both criteria have the same strategy in theoretically, experimental results demonstrate the best criterion for microarray gene expression data.

A Study of Color Transformation on Website Images for the Color Blind

In this paper, we study on color transformation method on website images for the color blind. The most common category of color blindness is red-green color blindness which is viewed as beige color. By transforming the colors of the images, the color blind can improve their color visibility. They can have a better view when browsing through the websites. To transform colors on the website images, we study on two algorithms which are the conversion techniques from RGB color space to HSV color space and self-organizing color transformation. The comparative study focuses on criteria based on the ease of use, quality, accuracy and efficiency. The outcome of the study leads to enhancement of website images to meet the color blinds- vision requirements in perceiving image detailed.

Improving the Road Construction Supply Chain by Developing a National Level Performance Measurement System: the Case of Estonia

Transport and logistics are the lifeblood of societies. There is a strong correlation between overall growth in economic activity and growth of transport. The movement of people and goods has the potential for creating wealth and prosperity, therefore the state of transportation infrastructure and especially the condition of road networks is often a governmental priority. The design, building and maintenance of national roads constitute a substantial share of government budgets. Taking into account the magnitude and importance of these investments, the expedience, efficiency and sustainability of these projects are of great public interest. This paper provides an overview of supply chain management principles applied to road construction. In addition, road construction performance measurement systems and ICT solutions are discussed. Road construction in Estonia is analyzed. The authors propose the development of a national performance measurement system for road construction.

Detection of Bias in GPS satellites- Measurements for Enhanced Measurement Integrity

In this paper, the detection of a fault in the Global Positioning System (GPS) measurement is addressed. The class of faults considered is a bias in the GPS pseudorange measurements. This bias is modeled as an unknown constant. The fault could be the result of a receiver fault or signal fault such as multipath error. A bias bank is constructed based on set of possible fault hypotheses. Initially, there is equal probability of occurrence for any of the biases in the bank. Subsequently, as the measurements are processed, the probability of occurrence for each of the biases is sequentially updated. The fault with a probability approaching unity will be declared as the current fault in the GPS measurement. The residual formed from the GPS and Inertial Measurement Unit (IMU) measurements is used to update the probability of each fault. Results will be presented to show the performance of the presented algorithm.

Preparation and Characterization of Self Assembled Gold Nanoparticles on Amino Functionalized SiO2 Dielectric Core

Wet chemistry methods are used to prepare the SiO2/Au nanoshells. The purpose of this research was to synthesize gold coated SiO2 nanoshells for biomedical applications. Tunable nanoshells were prepared by using different colloidal concentrations. The nanoshells are characterized by FTIR, XRD, UV-Vis spectroscopy and atomic force microscopy (AFM). The FTIR results confirmed the functionalization of the surfaces of silica nanoparticles with NH2 terminal groups. A tunable absorption was observed between 470-600 nm with a maximum range of 530-560 nm. Based on the XRD results three main peaks of Au (111), (200) and (220) were identified. Also AFM results showed that the silica core diameter was about 100 nm and the thickness of gold shell about 10 nm.

Integrating Context Priors into a Decision Tree Classification Scheme

Scene interpretation systems need to match (often ambiguous) low-level input data to concepts from a high-level ontology. In many domains, these decisions are uncertain and benefit greatly from proper context. This paper demonstrates the use of decision trees for estimating class probabilities for regions described by feature vectors, and shows how context can be introduced in order to improve the matching performance.

Multi-objective Optimization with Fuzzy Based Ranking for TCSC Supplementary Controller to Improve Rotor Angle and Voltage Stability

Many real-world optimization problems involve multiple conflicting objectives and the use of evolutionary algorithms to solve the problems has attracted much attention recently. This paper investigates the application of multi-objective optimization technique for the design of a Thyristor Controlled Series Compensator (TCSC)-based controller to enhance the performance of a power system. The design objective is to improve both rotor angle stability and system voltage profile. A Genetic Algorithm (GA) based solution technique is applied to generate a Pareto set of global optimal solutions to the given multi-objective optimisation problem. Further, a fuzzy-based membership value assignment method is employed to choose the best compromise solution from the obtained Pareto solution set. Simulation results are presented to show the effectiveness and robustness of the proposed approach.