Measurement of AC conductivity and dielectric properties of flexible conductive styrene–butadiene rubber‐carbon black composites

Flexible conductive polymer composites were prepared using styrene–butadiene rubber (SBR) as a matrix and conductive carbon black as filler. The filler loading was varied from 10 to 60 phr. The effect of frequency, filler loading, temperature, and applied pressure on the AC conductivity, permittivity, and loss factor of the composites was studied. The AC conductivity of low and high loaded composites was found to be frequency dependent and independent respectively. The permittivity and the loss factor were continuously decreasing with increasing frequency. The increase in filler loading increased the AC conductivity, dielectric constant, and loss factor of the composites. Increase in temperature imposed increase in conductivity and permittivity of the composites. With increasing applied pressure the properties showed exponential increase. The effect of time under a constant compressive stress was studied and dielectric relaxation times were evaluated. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci 104: 986–995, 2007     

Evaluation of realtime people tracking for indoor environments using ubiquitous motion sensors and limited wireless network infrastructure

We present the development and evaluation of a realtime indoor localisation system for tracking people. Our aim was to track a person’s indoor position using dead-reckoning, while limiting position error without depending on extensive wireless network infrastructure. The Indoor People Tracker used wearable motion sensors, a floor-plan map and a limited wireless sensor network for proximity ranging. We evaluated how the position accuracy of the Indoor People Tracker was affected by floor-plan map features, wireless proximity range and motion information. The advantage of the Indoor People Tracker was found; it was able to achieve accurate position resolution with minimal error, while not depending on wireless proximity.     

Association Rule Mining Frequent-Pattern-Based Intrusion Detection in Network

In the network security system, intrusion detection plays a significant role. The network security system detects the malicious actions in the network and also conforms the availability, integrity and confidentiality of data information resources. Intrusion identification system can easily detect the false positive alerts. If large number of false positive alerts are created then it makes intrusion detection system as difficult to differentiate the false positive alerts from genuine attacks. Many research works have been done. The issues in the existing algorithms are more memory space and need more time to execute the transactions of records. This paper proposes a novel framework of network security Intrusion Detection System (IDS) using Modified Frequent Pattern (MFP-Tree) via K-means algorithm. The accuracy rate of Modified Frequent Pattern Tree (MFPT)-K means method in finding the various attacks are Normal 94.89%, for DoS based attack 98.34%, for User to Root (U2R) attacks got 96.73%, Remote to Local (R2L) got 95.89% and Probe attack got 92.67% and is optimal when it is compared with other existing algorithms of K-Means and APRIORI.     

Hybrid Recommender System Using Systolic Tree for Pattern Mining

A recommender system is an approach performed by e-commerce for increasing smooth users’ experience. Sequential pattern mining is a technique of data mining used to identify the co-occurrence relationships by taking into account the order of transactions. This work will present the implementation of sequence pattern mining for recommender systems within the domain of e-commerce. This work will execute the Systolic tree algorithm for mining the frequent patterns to yield feasible rules for the recommender system. The feature selection's objective is to pick a feature subset having the least feature similarity as well as highest relevancy with the target class. This will mitigate the feature vector's dimensionality by eliminating redundant, irrelevant, or noisy data. This work presents a new hybrid recommender system based on optimized feature selection and systolic tree. The features were extracted using Term Frequency-Inverse Document Frequency (TF-IDF), feature selection with the utilization of River Formation Dynamics (RFD), and the Particle Swarm Optimization (PSO) algorithm. The systolic tree is used for pattern mining, and based on this, the recommendations are given. The proposed methods were evaluated using the MovieLens dataset, and the experimental outcomes confirmed the efficiency of the techniques. It was observed that the RFD feature selection with systolic tree frequent pattern mining with collaborative filtering, the precision of 0.89 was achieved.     

Biosynthesised silver and copper nanoformulation as foliar spray to control bird's eye spot disease in tea plantations

Tea leaves have economic importance in preparation of the popular beverage of the world “tea”. Bird’s eye spot disease of tea leaves creates significant revenue loss in tea trade of many tea plant cultivating countries. Management of this disease by silver (AgNps) and copper (CuNps) nanoparticles that are biosynthesised by efficient antagonists was studied. The biocontrol agents like Pseudomonas fluorescens, Trichoderma atroviride and Streptomyces sannanensis were evaluated for nanoparticle synthesis against Cercospora theae isolates namely KC10, MC24 and VC38. Initially, the freshly prepared extracellular AgNps showed high disease control (59.42 – 79.76%), but the stability of antagonistic property in stored nanoparticles were significantly high in CuNps (58.71 – 73.81%). Greenhouse studies on various treatments imposed also showed reduced disease incidence percentage of 13.4, 7.57 and 10.11% when treated with CuNps synthesized by P. fluorescens, T. atroviride and S. sannanensis respectively. Various treatment schedule in fields suggested the use of Bionanocopper@1.5 ppm for highest yield (3743 kg/ha) with 66.1% disease prevention. The results suggest the use of biosynthesised CuNps using Streptomyces sannanensis for controlling the tea plant pathogens causing foliar disease with higher stability in releasing the antagonistic activity during sporadic disease incidence of bird’s eye spot disease in tea plants.Inspec keywords: silver, copper, crops, plant diseases, nanoparticles, air pollution, agrochemicals, nanobiotechnologyOther keywords: biosynthesised silver, biosynthesised copper, nanoformulation, foliar spray, bird eye spot disease control, tea plantations, tea leaves, economic importance, revenue loss, tea trade, tea plant cultivating countries, silver nanoparticles, AgNps, copper nanoparticles, CuNps, biocontrol agents, nanoparticle synthesis, Cercospora theae isolates, KC10, MC24, VC38, greenhouse studies, antagonistic property, P. fluorescens, T. atroviride, S. sannanensis, fungicides, synthetic nanomaterials, bionanomaterials, disease prevention, green leaf yield, BionanoCu, tea plant pathogens, foliar disease     

Robust Estimation of GARMA Model Parameters with an Application to Cointegration among Interest Rates of Industrialized Countries

We review the literature on long memory ARFIMA and GARMA models andintroduce a new efficient estimator for GARMA models, which we show to berobust. Next we conduct a Monte Carlo study to demonstate the power of theDickie–Fuller test when the data are generated from a stationary GARMAprocess. We conclude with a brief discussion of cointegration in the contextof GARMA models with an application to international interest rates.     

Influence of <Emphasis Type="Italic">Cissus quadrangularis</Emphasis> Stabilized AgNPs and Its Structural,Optical, Antibacterial Analysis: A Comparative Study

Silver nanoparticles (AgNPs) was synthesized by using AgCl precursor with the stabilizing agent Cissus quadrangularis by precipitation method and the obtained particles were characterized by X-ray diffraction (XRD) analysis, Field Emission Scanning Electron Microscope (FESEM) and UV–Visible (UV–Vis) analysis. The influence of a stabilizing agent on AgNPs was compared with non-stabilized AgNPs through the experimental analysis. The XRD patterns show pure face center cubic structure for both samples, whereas the crystallite size is found to be low in stabilizer used samples. FESEM image and the UV–Vis spectra show less agglomeration and blue shift respectively, for stabilizer used AgNPs, indicating small size particles. Photoluminescence spectra show the emission band at 390 nm for both samples. Antibacterial tests show good activity against Pseudomonas aeruginosa for stabilizer used AgNPs. The study concluded that Cissus quadrangularis can be used as a potential stabilizing agent for preparing AgNPs from AgCl, for optical and biomedical applications.     

Biocomposite based electrode for effective removal of Cr (VI) heavy metal via capacitive deionization

Abstract

This study focuses on the fabrication of biocomposite electrode and removal of Cr (VI) ions from wastewater using a capacitive deionization (CDI) method. The activated carbon (AC) was synthesized from Bael fruit shell (BS). The synthesized AC surface has a macroporous and mesoporous structure with the large specific surface area (617.72?m² g^?1) and high adsorption capacity. The cyclic voltammetry and CDI were performed for the detection and for the removal of chromium (VI) ions, respectively. The lower level of detection of Cr (VI) by a modified electrode was found to be 10 ppt. SEM, BET, and FTIR analyses were performed to explore the surface properties of electrode materials. The removal efficiency was achieved 100% by using biocomposite electrode with an applied potential of 15?V. The highest percent removal mechanism consists of electrosorption and electroreduction due to the affinity between polyvinyl alcohol modified electrode and Cr (VI) ions, under electrochemically faradic process.     

Influence of compressive stress on the pore structure of carbon cloth based gas diffusion layer investigated by capillary flow porometry

Gas diffusion layer (GDL) is subjected to compressive stress at high temperature along with polymer electrolyte membrane in the fabrication process and in assembling the fuel cell stacks. Compressive stress decreases the thickness of GDL, electrical conductivity, permeability, and affects the pores. Carbon cloth based GDL withstands higher strain level when compared to carbon paper and the pore structure is also disrupted to a greater extent in cloth based GDL. In the present paper, we have addressed the effects of stress on pore structure of cloth based GDL. An optimum GDL must offer low mass transport resistance in an operating PEM fuel cell. The pore size analysis of pristine GDL and GDLs pressed at different pressure levels (200, 600 & 1000 kg cm⁻²) and their characteristics are evaluated using capillary flow porometry. The compressive stress affects the three types of pores in GDL called bubble point pore, mean flow pore and smallest pore. The change in electrical resistance, wetting behavior and surface morphology is also examined as a function of compressive stress. The fuel cell performances using these GDLs pressed at different compressive stresses are also evaluated and presented. The highest PEMFC performance is achieved at a compressive stress of 200 kg cm⁻², which could be attributed to the combined effect of reduced ohmic resistance and optimized pore structure. The order of increasing performance in terms of current density is observed to be j₂₀₀ > j_Pristine > j₆₀₀ > j₁₀₀₀ at 0.15 V. The thicknesses and pore sizes of custom made GDL for optimum fuel cell performance are recommended.     

The experimental study on the performance,combustion and emission characteristics of a diesel engine using diesel – biodiesel – diethyl ether blends

ABSTRACT

In the present research work, the experimental analysis has been executed to investigate the influence of diethyl ether as an oxygenated additive to the diesel-biodiesel blend on the performance, combustion and emission characteristics of a diesel engine. The biodiesel (Frying oil methyl ester) was prepared by the transesterification process, and the biodiesel was added (40% by volume) to the diesel fuel to prepare the diesel-biodiesel blend (D60FME40). The diethyl ether was added to the diesel-biodiesel blends D60FM35 (diesel 60% + biodiesel 35% by volume) and D60FM30 (diesel 60% + biodiesel 30% by volume) with suitable volume proportions of 5% and 10% respectively to form diesel-biodiesel-diethyl ether blends ((D60FM35DEE5) & (D60FM30DEE10)). Initially, the test was conducted with diesel fuel to obtain the baseline reference reading. Then, the reading was compared with results taken from the engine using a diesel-biodiesel blend (D60FME40) and diethyl ether blends (D60FM35DEE5) & (D60FM30DEE10). The results reveal that the maximum brake thermal efficiency was obtained with diesel fuel and it was higher than the diesel-biodiesel blend and diethyl ether blends. The peak in-cylinder gas pressure and heat release rate in the premixed stage was less for the diesel-biodiesel blend, but it was increased with the addition of diethyl ether to the blend. The diesel-biodiesel-diethyl ether blends show less carbon monoxide and hydrocarbon emissions except for NO_X emission as compared to the diesel and diesel-biodiesel blend, especially at the engine rated power.