Classification of Discharges Initiated by Liquid Droplet on Insulation Material under AC Voltages Adopting UHF Technique

In the present work, an attempt has been made to understand the feasibility of using UHF technique for identification of any corona discharges/ arcing in insulating material due to water droplets. The sensors of broadband type are useful for identification of such discharges. It is realised that arcing initiated by liquid droplet radiates UHF signals in the entire bandwidth up to 2 GHz. The frequency content of the UHF signal generated due to corona/arcing is not much varied in epoxy nanocomposites with different weight percentage of clay content. The exfoliated/intercalated properties were analysed through TEM studies. It is realized that corona initiated discharges are of intermittent process. The hydrophobicity of the material characterized through contact angle measurement. It is realized that low Wt % of nanoclay content in epoxy resin reduces the surface carbonization due to arcing/corona discharges. The results of the study with gamma irradiated specimen indicates that contact angle, discharge inception time and evaporation time of the liquid are much lower than the virgin epoxy nanocomposite material.

Cytotaxonomy and Morphology of Chironomid Larvae (Diptera, Chironomidae) in Armenia

In the study of chironomids in Armenia several species of Orthocladiinae subfamily of Cricotopus genus, Diamesinae subfamily of Diamesa genus, and Chironominae subfamily of Chironomus genus, have been identified. In the Cricotopus genus two sibling species were found, not distinguishable by larval morphological features, but clearly distinct cytogenetically.

A Study on Barreling Behavior during Upsetting Process using Artificial Neural Networks with Levenberg Algorithm

In this paper back-propagation artificial neural network (BPANN )with Levenberg–Marquardt algorithm is employed to predict the deformation of the upsetting process. To prepare a training set for BPANN, some finite element simulations were carried out. The input data for the artificial neural network are a set of parameters generated randomly (aspect ratio d/h, material properties, temperature and coefficient of friction). The output data are the coefficient of polynomial that fitted on barreling curves. Neural network was trained using barreling curves generated by finite element simulations of the upsetting and the corresponding material parameters. This technique was tested for three different specimens and can be successfully employed to predict the deformation of the upsetting process

Lessons from Applying XP Methodology to Business Requirements Engineering in Developing Countries Context

Most standard software development methodologies are often not applied to software projects in many developing countries of the world. The approach generally practice is close to what eXtreme Programming (XP) is likely promoting, just keep coding and testing as the requirement evolves. XP is an agile software process development methodology that has inherent capability for improving efficiency of Business Software Development (BSD). XP can facilitate Business-to-Development (B2D) relationship due to its customer-oriented advocate. From practitioner point of view, we applied XP to BSD and result shows that customer involvement has positive impact on productivity, but can as well frustrate the success of the project. In an effort to promote software engineering practice in developing countries of Africa, we present the experiment performed, lessons learned, problems encountered and solution adopted in applying XP methodology to BSD.

Flexible Manufacturing System

Flexible manufacturing system is a system that is able to respond to changed conditions. In general, this flexibility is divided into two key categories and several subcategories. The first category is the so called machine flexibility which enables to make various products by the given machinery. The second category is routing flexibility enabling to execute the same operation by various machines. Flexible manufacturing systems usually consist of three main parts: CNC machine tools, transport system and control system. A higher level of flexible manufacturing systems is represented by the so called intelligent manufacturing systems.

Agreement Options on Multi Criteria Group Decision and Negotiation

This paper presents a conceptual model of agreement options on negotiation support for civil engineering decision. The negotiation support facilitates the solving of group choice decision making problems in civil engineering decision to reduce the impact of mud volcano disaster in Sidoarjo, Indonesia. The approach based on application of analytical hierarchy process (AHP) method for multi criteria decision on three level of decision hierarchy. Decisions for reducing impact is very complicated since many parties involved in a critical time. Where a number of stakeholders are involved in choosing a single alternative from a set of solution alternatives, there are different concern caused by differing stakeholder preferences, experiences, and background. Therefore, a group choice decision support is required to enable each stakeholder to evaluate and rank the solution alternatives before engaging into negotiation with the other stakeholders. Such civil engineering solutions as alternatives are referred to as agreement options that are determined by identifying the possible stakeholder choice, followed by determining the optimal solution for each group of stakeholder. Determination of the optimal solution is based on a game theory model of n-person general sum game with complete information that involves forming coalitions among stakeholders.

Real Time Compensation of Machining Errors for Machine Tools NC based on Systematic Dispersion

Manufacturing tolerancing is intended to determine the intermediate geometrical and dimensional states of the part during its manufacturing process. These manufacturing dimensions also serve to satisfy not only the functional requirements given in the definition drawing, but also the manufacturing constraints, for example geometrical defects of the machine, vibration and the wear of the cutting tool. In this paper, an experimental study on the influence of the wear of the cutting tool (systematic dispersions) is explored. This study was carried out on three stages .The first stage allows machining without elimination of dispersions (random, systematic) so the tolerances of manufacture according to total dispersions. In the second stage, the results of the first stage are filtered in such way to obtain the tolerances according to random dispersions. Finally, from the two previous stages, the systematic dispersions are generated. The objective of this study is to model by the least squares method the error of manufacture based on systematic dispersion. Finally, an approach of optimization of the manufacturing tolerances was developed for machining on a CNC machine tool

Clustering Protein Sequences with Tailored General Regression Model Technique

Cluster analysis divides data into groups that are meaningful, useful, or both. Analysis of biological data is creating a new generation of epidemiologic, prognostic, diagnostic and treatment modalities. Clustering of protein sequences is one of the current research topics in the field of computer science. Linear relation is valuable in rule discovery for a given data, such as if value X goes up 1, value Y will go down 3", etc. The classical linear regression models the linear relation of two sequences perfectly. However, if we need to cluster a large repository of protein sequences into groups where sequences have strong linear relationship with each other, it is prohibitively expensive to compare sequences one by one. In this paper, we propose a new technique named General Regression Model Technique Clustering Algorithm (GRMTCA) to benignly handle the problem of linear sequences clustering. GRMT gives a measure, GR*, to tell the degree of linearity of multiple sequences without having to compare each pair of them.

Emission Constrained Hydrothermal Scheduling Algorithm

This paper presents an efficient emission constrained hydrothermal scheduling algorithm that deals with nonlinear functions such as the water discharge characteristics, thermal cost, and transmission loss. It is then incorporated into the hydrothermal coordination program. The program has been tested on a practical utility system having 32 thermal and 12 hydro generating units. Test results show that a slight increase in production cost causes a substantial reduction in emission.

Cost-Effective Design of Space Structures Joints: A Review

In construction of any structure, the aesthetic and utility values should be considered in such a way as to make the structure cost-effective. Most structures are composed of elements and joints which are very critical in any skeletal space structure because they majorly determine the performance of the structure. In early times, most space structures were constructed using rigid joints which had the advantage of better performing structures as compared to pin-jointed structures but with the disadvantage of requiring all the construction work to be done on site. The discovery of semi-rigid joints now enables connections to be prefabricated and quickly assembled on site while maintaining good performance. In this paper, cost-effective is discussed basing on strength of connectors at the joints, buckling of joints and overall structure, and the effect of initial geometrical imperfections. Several existing joints are reviewed by classifying them into categories and discussing where they are most suited and how they perform structurally. Also, finite element modeling using ABAQUS is done to determine the buckling behavior. It is observed that some joints are more economical than others. The rise to span ratio and imperfections are also found to affect the buckling of the structures. Based on these, general principles that guide the design of cost-effective joints and structures are discussed.

An Improved Resource Discovery Approach Using P2P Model for Condor: A Grid Middleware

Resource Discovery in Grids is critical for efficient resource allocation and management. Heterogeneous nature and dynamic availability of resources make resource discovery a challenging task. As numbers of nodes are increasing from tens to thousands, scalability is essentially desired. Peer-to-Peer (P2P) techniques, on the other hand, provide effective implementation of scalable services and applications. In this paper we propose a model for resource discovery in Condor Middleware by using the four axis framework defined in P2P approach. The proposed model enhances Condor to incorporate functionality of a P2P system, thus aim to make Condor more scalable, flexible, reliable and robust.

Generalized Predictive Control of Batch Polymerization Reactor

This paper describes the application of a model predictive controller to the problem of batch reactor temperature control. Although a great deal of work has been done to improve reactor throughput using batch sequence control, the control of the actual reactor temperature remains a difficult problem for many operators of these processes. Temperature control is important as many chemical reactions are sensitive to temperature for formation of desired products. This controller consist of two part (1) a nonlinear control method GLC (Global Linearizing Control) to create a linear model of system and (2) a Model predictive controller used to obtain optimal input control sequence. The temperature of reactor is tuned to track a predetermined temperature trajectory that applied to the batch reactor. To do so two input signals, electrical powers and the flow of coolant in the coil are used. Simulation results show that the proposed controller has a remarkable performance for tracking reference trajectory while at the same time it is robust against noise imposed to system output.

Design and Implementation of Optimal Winner Determination Algorithm in Combinatorial e- Auctions

The one of best robust search technique on large scale search area is heuristic and meta heuristic approaches. Especially in issue that the exploitation of combinatorial status in the large scale search area prevents the solution of the problem via classical calculating methods, so such problems is NP-complete. in this research, the problem of winner determination in combinatorial auctions have been formulated and by assessing older heuristic functions, we solve the problem by using of genetic algorithm and would show that this new method would result in better performance in comparison to other heuristic function such as simulated annealing greedy approach.

MHD Falkner-Skan Boundary Layer Flow with Internal Heat Generation or Absorption

This paper examines the forced convection flow of incompressible, electrically conducting viscous fluid past a sharp wedge in the presence of heat generation or absorption with an applied magnetic field. The system of partial differential equations governing Falkner - Skan wedge flow and heat transfer is first transformed into a system of ordinary differential equations using similarity transformations which is later solved using an implicit finite - difference scheme, along with quasilinearization technique. Numerical computations are performed for air (Pr = 0.7) and displayed graphically to illustrate the influence of pertinent physical parameters on local skin friction and heat transfer coefficients and, also on, velocity and temperature fields. It is observed that the magnetic field increases both the coefficients of skin friction and heat transfer. The effect of heat generation or absorption is found to be very significant on heat transfer, but its effect on the skin friction is negligible. Indeed, the occurrence of overshoot is noticed in the temperature profiles during heat generation process, causing the reversal in the direction of heat transfer.

Bifurcations and Chaotic Solutions of Two-dimensional Zonal Jet Flow on a Rotating Sphere

We study bifurcation structure of the zonal jet flow the streamfunction of which is expressed by a single spherical harmonics on a rotating sphere. In the non-rotating case, we find that a steady traveling wave solution arises from the zonal jet flow through Hopf bifurcation. As the Reynolds number increases, several traveling solutions arise only through the pitchfork bifurcations and at high Reynolds number the bifurcating solutions become Hopf unstable. In the rotating case, on the other hand, under the stabilizing effect of rotation, as the absolute value of rotation rate increases, the number of the bifurcating solutions arising from the zonal jet flow decreases monotonically. We also carry out time integration to study unsteady solutions at high Reynolds number and find that in the non-rotating case the unsteady solutions are chaotic, while not in the rotating cases calculated. This result reflects the general tendency that the rotation stabilizes nonlinear solutions of Navier-Stokes equations.

Incidence of Chronic Disease and Lipid Profile in Veteran Rugby Athletes

Recently, the health of retired National Football League players, particularly lineman has been investigated. A number of studies have reported increased cardiometabolic risk, premature cardiovascular disease and incidence of type 2 diabetes. Rugby union players have somatotypes very similar to National Football League players which suggests that rugby players may have similar health risks. The International Golden Oldies World Rugby Festival (GORF) provided a unique opportunity to investigate the demographics of veteran rugby players. METHODOLOGIES: A cross-sectional, observational study was completed using an online web-based questionnaire that consisted of medical history and physiological measures. Data analysis was completed using a one sample t-test (50yrs) and Chi-square test. RESULTS: A total of 216 veteran rugby competitors (response rate = 6.8%) representing 10 countries, aged 35-72 yrs (mean 51.2, S.D. ±8.0), participated in the online survey. As a group, the incidence of current smokers was low at 8.8% (avg 72.4 cigs/wk) whilst the percentage consuming alcohol was high (93.1% (avg 11.2 drinks/wk). Competitors reported the following top six chronic diseases/disorders; hypertension (18.6%), arthritis (OA/RA, 11.5%), asthma (9.3%), hyperlipidemia (8.2%), diabetes (all types, 7.5%) and gout (6%), there were significant differences between groups with regard to cancer (all types) and migraines. When compared to the Australian general population (Australian Bureau of Statistics data, n=18,000), GORF competitors had a significantly lower incidence of anxiety (p

Generalised Slant Weighted Toeplitz Operator

A slant weighted Toeplitz operator Aφ is an operator on L2(β) defined as Aφ = WMφ where Mφ is the weighted multiplication operator and W is an operator on L2(β) given by We2n = βn β2n en, {en}n∈Z being the orthonormal basis. In this paper, we generalise Aφ to the k-th order slant weighted Toeplitz operator Uφ and study its properties.

Using Morphological and Microsatellite (SSR) Markers to Assess the Genetic Diversity in Alfalfa (Medicago sativa L.)

Utilization of diverse germplasm is needed to enhance the genetic diversity of cultivars. The objective of this study was to evaluate the genetic relationships of 98 alfalfa germplasm accessions using morphological traits and SSR markers. From the 98 tested populations, 81 were locals originating in Europe, 17 were introduced from USA, Australia, New Zealand and Canada. Three primers generated 67 polymorphic bands. The average polymorphic information content (PIC) was very high (> 0.90) over all three used primer combinations. Cluster analysis using Unweighted Pair Group Method with Arithmetic Means (UPGMA) and Jaccard´s coefficient grouped the accessions into 2 major clusters with 4 sub-clusters with no correlation between genetic and morphological diversity. The SSR analysis clearly indicated that even with three polymorphic primers, reliable estimation of genetic diversity could be obtained.

Reutilization of Organic and Peat Soils by Deep Cement Mixing

Limited infrastructure development on peats and organic soils is a serious geotechnical issues common to many countries of the world especially Malaysia which distributed 1.5 mill ha of those problematic soil. These soils have high water content and organic content which exhibit different mechanical properties and may also change chemically and biologically with time. Constructing structures on peaty ground involves the risk of ground failure and extreme settlement. Nowdays, much efforts need to be done in making peatlands usable for construction due to increased landuse. Deep mixing method employing cement as binders, is generally used as measure again peaty/ organic ground failure problem. Where the technique is widely adopted because it can improved ground considerably in a short period of time. An understanding of geotechnical properties as shear strength, stiffness and compressibility behavior of these soils was requires before continues construction on it. Therefore, 1- 1.5 meter peat soil sample from states of Johor and an organic soil from Melaka, Malaysia were investigated. Cement were added to the soil in the pre-mixing stage with water cement ratio at range 3.5,7,14,140 for peats and 5,10,30 for organic soils, essentially to modify the original soil textures and properties. The mixtures which in slurry form will pour to polyvinyl chloride (pvc) tube and cured at room temperature 250C for 7,14 and 28 days. Laboratory experiments were conducted including unconfined compressive strength and bender element , to monitor the improved strength and stiffness of the 'stabilised mixed soils'. In between, scanning electron miscroscopic (SEM) were observations to investigate changes in microstructures of stabilised soils and to evaluated hardening effect of a peat and organic soils stabilised cement. This preliminary effort indicated that pre-mixing peat and organic soils contributes in gaining soil strength while help the engineers to establish a new method for those problematic ground improvement in further practical and long term applications.

The Rank-scaled Mutation Rate for Genetic Algorithms

A novel method of individual level adaptive mutation rate control called the rank-scaled mutation rate for genetic algorithms is introduced. The rank-scaled mutation rate controlled genetic algorithm varies the mutation parameters based on the rank of each individual within the population. Thereby the distribution of the fitness of the papulation is taken into consideration in forming the new mutation rates. The best fit mutate at the lowest rate and the least fit mutate at the highest rate. The complexity of the algorithm is of the order of an individual adaptation scheme and is lower than that of a self-adaptation scheme. The proposed algorithm is tested on two common problems, namely, numerical optimization of a function and the traveling salesman problem. The results show that the proposed algorithm outperforms both the fixed and deterministic mutation rate schemes. It is best suited for problems with several local optimum solutions without a high demand for excessive mutation rates.