IEEE-PES Transmission and Distribution Conference and Exposition Call for Papers

Static network-related system voltage stability margin (VSM) depends on the availability of reactive power to support the transport of real power from sources to sinks. Based on this premise, the total VAr loss is minimized in the unified OPF framework considering real and reactive power controllers, and its effect on VSM is studied. Studies are conducted on a three-bus system, the IEEE 30-bus system, and a 191-bus Indian electric power system, and their results are reported.     

Experimental design in soap manufacturing for optimization of fuzzified process capability index

In manufacturing industries, the quality of a product depends on the combined effect of multiple input variables working singly or together and therefore attention has been given on process capability indices to shift from single to multivariate domain. In case of multivariable domain the capability to incorporate uncertainties at the time of decision making becomes necessary. Fuzzy system is introduced to take care of this requirement. In this article the process parameters of soap manufacturing industries have been analyzed. The process capability is determined using Fuzzy Inference System rule editor based on a set of justified if then statements as applicable for the process. The data has been collected in linguistic form to derive its process capability, using a set of justified rules and the effect of each factor has been determined using Design of Experiments (DoE) and analysis of variance technique (ANOVA) for improving the soap quality from perspective of its softness. This article ventures to propose a new methodology by integrating Fuzzy with DoE providing better result followed by DoE and Fuzzy Inference system in isolation.     

Target following with motion prediction for unmanned surface vehicle operating in cluttered environments

The capability of following a moving target in an environment with obstacles is required as a basic and necessary function for realizing an autonomous unmanned surface vehicle (USV). Many target following scenarios involve a follower and target vehicles that may have different maneuvering capabilities. Moreover, the follower vehicle may not have prior information about the intended motion of the target boat. This paper presents a trajectory planning and tracking approach for following a differentially constrained target vehicle operating in an obstacle field. The developed approach includes a novel algorithm for computing a desired pose and surge speed in the vicinity of the target boat, jointly defined as a motion goal, and tightly integrates it with trajectory planning and tracking components of the entire system. The trajectory planner generates a dynamically feasible, collision-free trajectory to allow the USV to safely reach the computed motion goal. Trajectory planning needs to be sufficiently fast and yet produce dynamically feasible and short trajectories due to the moving target. This required speeding up the planning by searching for trajectories through a hybrid, pose-position state space using a multi-resolution control action set. The search in the velocity space is decoupled from the search for a trajectory in the pose space. Therefore, the underlying trajectory tracking controller computes desired surge speed for each segment of the trajectory and ensures that the USV maintains it. We have carried out simulation as well as experimental studies to demonstrate the effectiveness of the developed approach.     

Grafting of methyl methacrylate onto guar gum by hydrogen peroxide initiation

Graft copolymerization of methyl methacrylate (MMA) onto guar gum (GG) in aqueous slurry has been carried out using hydrogen peroxide (H₂O₂) as initiator. The copolymers were characterized by infrared spectroscopy. The grafting parameters like percent grafting, grafting efficiency, percent add-on, and the grafting frequency were determined, and the effect of reaction time, concentration of initiator, and [GG]/[MMA] ratios on the grafting parameters have been discussed. The decrease in % add-on at increasing concentration of H₂O₂ indicated enhancement in the rate of homopolymerization of methyl methacrylate.     

Micropore characterization using the Dubinin-Astakhov equation to analyze high pressure CO2 (273 K) adsorption data

The characterization of the pore structure of microporous materials is of interest because of the usefulness of these materials in many applications. Of these, the characterization of carbon adsorbents is particularly problematic because of the presence of small pores with size on the order of small molecules (micropores) along with a wide distribution of pore sizes, and their non-crystalline structure. In this paper, we present results obtained using the Dubinin-Astakhov equation to analyze data from high pressure CO₂ adsorption at 273 K to characterize two sets of microporous carbons. Our results support the conclusions of previous workers that the Dubinin-Astakhov (DA) equation is able to linearize adsorption data that gives rise to curved Dubinin-Radushkevich plots. However, when applied over different ranges of relative pressure on the adsorption isotherm, the Dubinin-Astakhov plots result in different values of micropore volume and characteristic adsorption potential. Furthermore, DA analysis of CO₂ (273 K) adsorption data over a wide range of pressures (10^–3–22000 Tort), gives results different from DA analysis of CO₂ (273 K) isotherms measured at low pressures only (10^–3–830 Tort). It would appear desirable to apply the DA equation to data that reflects the entire range of micropore filling on the adsorption isotherm, as opposed to data over a limited relative pressure range. For CO₂ adsorption at 273 K, this would necessitate adsorption studies at high pressures, to about 28 atm. Micropore volumes obtained in this manner, agreed with the total pore volumes determined by nitrogen (77 K) adsorption for all the activated carbons studied.     

FRP composites based on different types of glass fibers and matrix resins: A comparative study

Flexural properties, impact energy, heat deflection temperature, and resistance to thermal and hydrothermal degradation of composites based on E-glass and N-glass fibers as the reinforcing agents, and epoxy, unsaturated polyester, phenolic, and epoxy-phenolic resin systems as the matrix materials were studied and compared. As a reinforcing agent E-glass fiber is superior to N-glass fiber, particularly with respect to development of flexural strength and modulus, impact strength, and thermal resistance; N-glass fiber, however, imparts to the composites substantially higher resistance to hydrothermal degradation under boiling conditions in different chemical environments. For use of both E-glass and N-glass fibers as reinforcing agents, the general order of resistance to hydrothermal degradation for the composites based on different matrix resins is epoxy > phenolic > unsaturated polyester resin. Incorporation of a low dose of a rubbery polymer, such as styrene butadiene rubber (0.1–0.2%) and liquid polybutadiene (0.5–0.75%), in unsaturated polyester resin as the matrix resin measurably enhances impact energy of the composite. © 1995 John Wiley & Sons, Inc.     

Survey of denoising,segmentation and classification of magnetic resonance imaging for prostate cancer

Multimedia Tools and Applications - Prostate cancer (PCa) has become the second most dreadful cancer in men after lung cancer. Traditional approaches used for treatment of PCa were manual, time...     

Liver disorder detection using variable- neighbor weighted fuzzy K nearest neighbor approach

The human liver disorder is a genetic problem due to the habituality of alcohol or effect by the virus. It can lead to liver failure or liver cancer, if not been detected in initial stage. The aim of the proposed method is to detect the liver disorder in initial stage using liver function test dataset. The problem with many real-world datasets including liver disease diagnosis data is class imbalanced. The word imbalance refers to the conditions that the number of observations belongs to one class having more or less than the other class(es). Traditional K- Nearest Neighbor (KNN) or Fuzzy KNN classifier does not work well on the imbalanced dataset because they treat the neighbor equally. The weighted variant of Fuzzy KNN assign a large weight for the neighbor belongs to the minority class data and relatively small weight for the neighbor belongs to the majority class to resolve the issues with data imbalance. In this paper, Variable- Neighbor Weighted Fuzzy K Nearest Neighbor Approach (Variable-NWFKNN) is proposed, which is an improved variant of Fuzzy-NWKNN. The proposed Variable-NWFKNN method is implemented on three real-world imbalance liver function test datasets BUPA, ILPD from UCI and MPRLPD. The Variable-NWFKNN is compared with existing NWKNN and Fuzzy-NWKKNN methods and found accuracy 73.91% (BUPA Dataset), 77.59% (ILPD Dataset) and 87.01% (MPRLPD Dataset). Further, TL_RUS method is used for preprocessing and it improved the accuracy as 78.46% (BUPA Dataset), 78.46% (ILPD Dataset) and 95.79% (MPRLPD Dataset).

     

Product recommendation for e-commerce business by applying principal component analysis (PCA) and K-means clustering: benefit for the society

Innovations in Systems and Software Engineering - Recommender system is a computer-based intelligent technique which facilitates the customers to fulfill their purchase requirements. In addition to...     

A comparative study on the metaheuristic-based optimization of skew composite laminates

Engineering with Computers - Plate structures are the integral parts of any maritime engineering platform. With the recent focus on composite structures, the need for optimizing their design and...