Wetting Properties of Silver Based Alloys

The temperature dependence of wettability (wetting angle, Θ (T)) for Ag-based melts on graphite and Al2O3 substrates is compared. Typical alloying effects are found, as the Ag host metal is gradually replaced by various metallic elements. The essence of alloying lies in the change of the electron/atom (e/a) ratio. This ratio is also manifested in the shift of wetting angles on the same substrate. Nevertheless, the effects are partially smeared by other (metallurgical) factors, like the interaction between the oxygenalloying elements and by the graphite substrate-oxygen interaction. In contrast, such effects are not pronounced in the case of Al2O3 substrates. As a consequence, Θ(T) exhibits an opposite trend in the case of two substrates. Crossovers of the Θ(T) curves were often found. The positions of crossovers depend on the chemical character and concentration of solute atoms. Segregation and epitaxial texture formation after solidification were also observed in certain alloy drops, especially in high concentration range. This phenomenon is not yet explained in every detail.

Copolymers of Pyrrole and α,ω-Dithienyl Terminated Poly(ethylene glycol)

This work presents synthesis of α,ω-dithienyl terminated poly(ethylene glycol) (PEGTh) capable for further chain extension by either chemical or electrochemical polymeriztion. PEGTh was characterized by FTIR and 1H-NMR. Further copolymerization of PEGTh and pyrrole (Py) was performed by chemical oxidative polymerization using ceric (IV) salt as an oxidant (PPy-PEGTh). PEG without end group modification was used directly to prepare copolymers with Py by Ce (IV) salt (PPy-PEG). Block copolymers with mole ratio of pyrrole to PEGTh (PEG) 50:1 and 10:1 were synthesized. The electrical conductivities of copolymers PPy-PEGTh and PPy-PEG were determined by four point probe technique. Influence of the synthetic route and content of the insulating segment on conductivity and yield of the copolymers were investigated.

Heterophase Polymerization of Pyrrole and Thienyl End Capped Ethoxylated Nonyl Phenol by Iron (III) Chloride

This study presents synthesis of novel block copolymers of thienyl end capped ethoxylated nonyl phenol and pyrrole via chemical oxidative polymerization. Ethoxylated nonyl phenol (ENP) was reacted with 2-thiophenecarbonyl chloride in order to synthesize a macromonomer containing thienyl end-group (ENPThC). Then copolymers of ENP-ThC and pyrrole were synthesized by chemical oxidative polymerization using iron (III) chloride as an oxidant. ENP-ThC served both as a macromonomer and an emulsifier for pyrrole with poor solubility in water. The synthesized block copolymers (ENP-ThC-b-PPy) were characterized by spectroscopic analysis and the electrical conductivities were investigated with 4-point probe technique.

Green-Y Model for Preliminary Sustainable Economical Concept of Renewable Energy Sources Deployment in ASEAN Countries

Endowed of renewable energy sources (RES) are the advantages of ASEAN, but they are using a low amount of RES only to generate electricity because their primary energy sources are fossil and coal. The cost of purchasing fossil and coal is cheaper now, but it might be expensive soon, as it will be depleted sooner and after. ASEAN showed that the RES are convenient to be implemented. Some country in ASEAN has huge renewable energy sources potential and use. The primary aim of this project is to assist ASEAN countries in preparing the renewable energy and to guide the policies for RES in the more upright direction. The Green-Y model will help ASEAN government to study and forecast the economic concept, including feed-in tariff.

Comparative Study of Line Voltage Stability Indices for Voltage Collapse Forecasting in Power Transmission System

At present, the evaluation of voltage stability assessment experiences sizeable anxiety in the safe operation of power systems. This is due to the complications of a strain power system. With the snowballing of power demand by the consumers and also the restricted amount of power sources, therefore, the system has to perform at its maximum proficiency. Consequently, the noteworthy to discover the maximum ability boundary prior to voltage collapse should be undertaken. A preliminary warning can be perceived to evade the interruption of power system’s capacity. The effectiveness of line voltage stability indices (LVSI) is differentiated in this paper. The main purpose of the indices used is to predict the proximity of voltage instability of the electric power system. On the other hand, the indices are also able to decide the weakest load buses which are close to voltage collapse in the power system. The line stability indices are assessed using the IEEE 14 bus test system to validate its practicability. Results demonstrated that the implemented indices are practically relevant in predicting the manifestation of voltage collapse in the system. Therefore, essential actions can be taken to dodge the incident from arising.

Optimisation of a Dragonfly-Inspired Flapping Wing-Actuation System

An optimisation method using both global and local optimisation is implemented to determine the flapping profile which will produce the most lift for an experimental wing-actuation system. The optimisation method is tested using a numerical quasi-steady analysis. Results of an optimised flapping profile show a 20% increase in lift generated as compared to flapping profiles obtained by high speed cinematography of a Sympetrum frequens dragonfly. Initial optimisation procedures showed 3166 objective function evaluations. The global optimisation parameters - initial sample size and stage one sample size, were altered to reduce the number of function evaluations. Altering the stage one sample size had no significant effect. It was found that reducing the initial sample size to 400 would allow a reduction in computational effort to approximately 1500 function evaluations without compromising the global solvers ability to locate potential minima. To further reduce the optimisation effort required, we increase the local solver’s convergence tolerance criterion. An increase in the tolerance from 0.02N to 0.05N decreased the number of function evaluations by another 20%. However, this potentially reduces the maximum obtainable lift by up to 0.025N.

Surface Roughness Prediction Model for Grinding of Composite Laminate Using Factorial Design

Glass fiber reinforced polymer (GFRP) laminates have been widely used because of their unique mechanical and physical properties such as high specific strength, stiffness and corrosive resistance. Accordingly, the demand for precise grinding of composites has been increasing enormously. Grinding is the one of the obligatory methods for fabricating products with composite materials and it is usually the final operation in the assembly of structural laminates. In this experimental study, an attempt has been made to develop an empirical model to predict the surface roughness of ground GFRP composite laminate with respect to the influencing grinding parameters by factorial design approach of design of experiments (DOE). The significance of grinding parameters and their three factor interaction effects on grinding of GFRP composite have been analyzed in detail. An empirical equation has been developed to attain minimum surface roughness in GFRP laminate grinding.

Parametric Study on Grindability of GFRP Laminates Using Different Abrasives

A study on grindability of chopped strand mat glass fiber reinforced polymer laminates (CSM GFRP) have been carried out to evaluate the significant parameters on wheel performance. Performance of Aluminum oxide and c-BN wheels during grinding of CSM GFRP laminate was evaluated in terms of grinding force and surface roughness during grinding. The cubic Boron Nitride wheel experiences higher tangential grinding forces components and lower normal force component than Aluminum oxide grinding wheels. In case of surface finish, Aluminum oxide grinding wheels outdo the cubic Boron Nitride grinding wheels.

Composite Relevance Feedback for Image Retrieval

This paper presents content-based image retrieval (CBIR) frameworks with relevance feedback (RF) based on combined learning of support vector machines (SVM) and AdaBoosts. The framework incorporates only most relevant images obtained from both the learning algorithm. To speed up the system, it removes irrelevant images from the database, which are returned from SVM learner. It is the key to achieve the effective retrieval performance in terms of time and accuracy. The experimental results show that this framework had significant improvement in retrieval effectiveness, which can finally improve the retrieval performance.

Micro-Hydrokinetic for Remote Rural Electrification

Standalone micro-hydrokinetic river (MHR) system is one of the promising technologies to be used for remote rural electrification. It simply requires the flow of water instead of elevation or head, leading to expensive civil works. This paper demonstrates an economic benefit offered by a standalone MHR system when compared to the commonly used standalone systems such as solar, wind and diesel generator (DG) at the selected study site in Kwazulu Natal. Wind speed and solar radiation data of the selected rural site have been taken from national aeronautics and space administration (NASA) surface meteorology database. The hybrid optimization model for electric renewable (HOMER) software was used to determine the most feasible solution when using MHR, solar, wind or DG system to supply 5 rural houses. MHR system proved to be the best cost-effective option to consider at the study site due to its low cost of energy (COE) and low net present cost (NPC).

Academic Mobbing in Turkey

People at workplace always face with stress and feel it in their lives. There are many factors that create stress and mobbing is one of them. Mobbing is a psychological terror, conducted systematically toward an individual by others at the same workplace. Mobbing started to become a famous subject last years in U.S and Europe. In Turkey, it is a new concept not because it does not occur, because of human nature that does not allow confessing it. Mobbing is being ignored by people, organizations and also government in our country. The focus of this study will be mobbing in Turkey by examining the workplace mobbing among Turkish academicians. There are other studies about mobbing in Turkey but none of them studied academy. Because mobbing methods change according to sectors and occupations, it is important to analyze each sector to understand the methods used in mobbing and the reactions of victims to these actions. The concept is analyzed in detail before focusing on mobbing at universities. This paper will be unique because there is no information about this specific subject in Turkish literature. In this paper, both qualitative and quantitative methods will be used to describe the mobbing at Turkish academic environment.

Effect of Coolant on Cutting Forces and Surface Roughness in Grinding of CSM GFRP

This paper presents a comparative study on dry and wet grinding through experimental investigation in the grinding of CSM glass fibre reinforced polymer laminates using a pink aluminium oxide wheel. Different sets of experiments were performed to study the effects of the independent grinding parameters such as grinding wheel speed, feed and depth of cut on dependent performance criteria such as cutting forces and surface finish. Experimental conditions were laid out using design of experiment central composite design. An effective coolant was sought in this study to minimise cutting forces and surface roughness for GFRP laminates grinding. Test results showed that the use of coolants reduces surface roughness, although not necessarily the cutting forces. These research findings provide useful economic machining solution in terms of optimized grinding conditions for grinding CSM GFRP.

Web Service Architecture for Computer-Adaptive Testing on e-Learning

This paper proposes a Web service and serviceoriented architecture (SOA) for a computer-adaptive testing (CAT) process on e-learning systems. The proposed architecture is developed to solve an interoperability problem of the CAT process by using Web service. The proposed SOA and Web service define all services needed for the interactions between systems in order to deliver items and essential data from Web service to the CAT Webbased application. These services are implemented in a XML-based architecture, platform independence and interoperability between the Web service and CAT Web-based applications.

Lithofacies Classification from Well Log Data Using Neural Networks, Interval Neutrosophic Sets and Quantification of Uncertainty

This paper proposes a novel approach to the question of lithofacies classification based on an assessment of the uncertainty in the classification results. The proposed approach has multiple neural networks (NN), and interval neutrosophic sets (INS) are used to classify the input well log data into outputs of multiple classes of lithofacies. A pair of n-class neural networks are used to predict n-degree of truth memberships and n-degree of false memberships. Indeterminacy memberships or uncertainties in the predictions are estimated using a multidimensional interpolation method. These three memberships form the INS used to support the confidence in results of multiclass classification. Based on the experimental data, our approach improves the classification performance as compared to an existing technique applied only to the truth membership. In addition, our approach has the capability to provide a measure of uncertainty in the problem of multiclass classification.

Analysis of a Population of Diabetic Patients Databases with Classifiers

Data mining can be called as a technique to extract information from data. It is the process of obtaining hidden information and then turning it into qualified knowledge by statistical and artificial intelligence technique. One of its application areas is medical area to form decision support systems for diagnosis just by inventing meaningful information from given medical data. In this study a decision support system for diagnosis of illness that make use of data mining and three different artificial intelligence classifier algorithms namely Multilayer Perceptron, Naive Bayes Classifier and J.48. Pima Indian dataset of UCI Machine Learning Repository was used. This dataset includes urinary and blood test results of 768 patients. These test results consist of 8 different feature vectors. Obtained classifying results were compared with the previous studies. The suggestions for future studies were presented.

Simulation of the Flow in a Packed-Bed with and without a Static Mixer by Using CFD Technique

The major focus of this work was to characterize hydrodynamics in a packed-bed with and without static mixer by using Computational Fluid Dynamic (CFD). The commercial software: COMSOL MULTIPHYSICSTM Version 3.3 was used to simulate flow fields of mixed-gas reactants i.e. CO and H2. The packed-bed was a single tube with the inside diameter of 0.8 cm and the length of 1.2 cm. The static mixer was inserted inside the tube. The number of twisting elements was 1 with 0.8 cm in diameter and 1.2 cm in length. The packed-bed with and without static mixer were both packed with approximately 700 spherical structures representing catalyst pellets. Incompressible Navier-Stokes equations were used to model the gas flow inside the beds at steady state condition, in which the inlet Reynolds Number (Re) was 2.31. The results revealed that, with the insertion of static mixer, the gas was forced to flow radially inward and outward between the central portion of the tube and the tube wall. This could help improving the overall performance of the packed-bed, which could be utilized for heterogeneous catalytic reaction such as reforming and Fischer- Tropsch reactions.

Leaching Characteristics of Upgraded Copper Flotation Tailings

The copper flotation tailings from Konkola Copper mine in Nchanga, Zambia were used in the study. The purpose of this study was to determine the leaching characteristics of the tailings material prior and after the physical beneficiation process is employed. The Knelson gravity concentrator (KC-MD3) was used for the beneficiation process. The copper leaching efficiencies and impurity co-extraction percentages in both the upgraded and the raw feed material were determined at different pH levels and temperature. It was observed that the copper extraction increased with an increase in temperature and a decrease in pH levels. In comparison to the raw feed sample, the upgraded sample reported a maximum copper extraction of 69% which was 9%, higher than raw feed % extractions. The impurity carry over was reduced from 18% to 4 % on the upgraded sample. The reduction in impurity co-extraction was as a result of the removal of the reactive gangue elements during the upgrading process, this minimized the number of side reaction occurring during leaching.

Protective Effect of Ethanolic Extract of Polyherbal Formulation on Carbon Tetrachloride Induced Liver Injury

Protective effect of ethanolic extract of polyherbal formulation (PHF) was studied on carbon tetrachloride induced liver damage on carbon tetrachloride induced liver damage. Treatment of rats with 250mg /kg body weight of ethanolic extract of PHF protected rats against carbon tetrachloride liver injury by significant lowerering 5’ nucleotidase (5’NT), Gamma Glutamyl transferase (GGT), Glutamate dehdyrogenasse (GDH) and Succinate Dehydrogenase (SDH) levels compared to control. Normalization in these enzyme levels indicates strong hepatoprotective property of PHF extract.

Precombining Adaptive LMMSE Detection for DS-CDMA Systems in Time Varying Channels: Non Blind and Blind Approaches

This paper deals with an adaptive multiuser detector for direct sequence code division multiple-access (DS-CDMA) systems. A modified receiver, precombinig LMMSE is considered under time varying channel environment. Detector updating is performed with two criterions, mean square estimation (MSE) and MOE optimization technique. The adaptive implementation issues of these two schemes are quite different. MSE criterion updates the filter weights by minimizing error between data vector and adaptive vector. MOE criterion together with canonical representation of the detector results in a constrained optimization problem. Even though the canonical representation is very complicated under time varying channels, it is analyzed with assumption of average power profile of multipath replicas of user of interest. The performance of both schemes is studied for practical SNR conditions. Results show that for poor SNR, MSE precombining LMMSE is better than the blind precombining LMMSE but for greater SNR, MOE scheme outperforms with better result.

Understanding the Silence: When Courts Don-t Speak About Religion

India recognizes the personal laws of the various religious communities that reside in the country. At the same time all the institutions of the state in India are committed to the value of secularism. This paper has been developed on the basis of a case study that indicates the dynamics of religion in the working of the lower judiciary in India. Majority of the commentary on religion and the judiciary has focused on debates surrounding the existence and application of personal laws. This paper, through a case study in the lower judiciary, makes an attempt to examine whether the interface between religion and the judiciary goes beyond personal laws. The first part of this paper explains the history and application of personal laws in social, political and legal contexts in India. The second part examines the case study located in two courts of first instance, following into the third part which provides an analysis of the empirical evidence. The fourth part focuses on preliminary observations about why there is a hesitancy to speak about religion in relation to the working of the judicial system.