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.     

Security Driven Scheduling Model for Computational Grid Using NSGA-II

Number of software applications demands various levels of security at the time of scheduling in Computational Grid. Grid may offer these securities but may result in the performance degradation due to overhead in offering the desired security. Scheduling performance in a Grid is affected by the heterogeneities of security and computational power of resources. Customized Genetic Algorithms have been effectively used for solving complex optimization problems (NP Hard) and various heuristics have been suggested for solving Multi-objective optimization problems. In this paper a security driven, elitist non-dominated sorting genetic algorithm, Optimal Security with Optimal Overhead Scheduling (OSO₂S), based on NSGA-II, is proposed. The model considers dual objectives of minimizing the security overhead and maximizing the total security achieved. Simulation results exhibit that the proposed algorithm delivers improved makespan and lesser security overhead in comparison to other such algorithms viz. MinMin, MaxMin, SPMinMin, SPMaxMin and SDSG.     

Long Duration Persistent Photocurrent in 3 nm Thin Doped Indium Oxide for Integrated Light Sensing and In-Sensor Neuromorphic Computation

Miniaturization and energy consumption by computational systems remain major challenges to address. Optoelectronics based synaptic and light sensing provide an exciting platform for neuromorphic processing and vision applications offering several advantages. It is highly desirable to achieve single-element image sensors that allow reception of information and execution of in-memory computing processes while maintaining memory for much longer durations without the need for frequent electrical or optical rehearsals. In this work, ultra-thin (<3 nm) doped indium oxide (In₂O₃) layers are engineered to demonstrate a monolithic two-terminal ultraviolet (UV) sensing and processing system with long optical state retention operating at 50 mV. This endows features of several conductance states within the persistent photocurrent window that are harnessed to show learning capabilities and significantly reduce the number of rehearsals. The atomically thin sheets are implemented as a focal plane array (FPA) for UV spectrum based proof-of-concept vision system capable of pattern recognition and memorization required for imaging and detection applications. This integrated light sensing and memory system is deployed to illustrate capabilities for real-time, in-sensor memorization, and recognition tasks. This study provides an important template to engineer miniaturized and low operating voltage neuromorphic platforms across the light spectrum based on application demand.     

Validity as a Measure of Data Quality in Internet of Things Systems

Data quality became significant with the emergence of data warehouse systems. While accuracy is intrinsic data quality, validity of data presents a wider perspective, which is more representational and contextual in nature. Through our article we present a different perspective in data collection and collation. We focus on faults experienced in data sets and present validity as a function of allied parameters such as completeness, usability, availability and timeliness for determining the data quality. We also analyze the applicability of these metrics and apply modifications to make it conform to IoT applications. Another major focus of this article is to verify these metrics on aggregated data set instead of separate data values. This work focuses on using the different validation parameters for determining the quality of data generated in a pervasive environment. Analysis approach presented is simple and can be employed to test the validity of collected data, isolate faults in the data set and also measure the suitability of data before applying algorithms for analysis. On analyzing the data quality of the two data sets on the basis of above-mentioned parameters. We show that validity for data set 1 was found to be 75% while it was found to be 67% only for data set 2. Availability and data freshness metrics performance were analyzed graphically. It was found that for data set 1, data freshness was better while availability metric was found better for data set 2. Usability obtained for data set 2 was 86% which was higher as compared to data set 1 whose usability metric was 69%. Thus, this work presents methods that can be leveraged for estimating data quality that can be beneficial in various IoT based industries which are essentially data centric and the decisions made by them depends upon the validity of data.

     

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...     

A simple decision tree-based disturbance monitoring system for VSC-based HVDC transmission link integrating a DFIG wind farm

Fault detection and classification is a key challenge for the protection of High Voltage DC (HVDC) transmission lines. In this paper, the Teager–Kaiser Energy Operator (TKEO) algorithm associated with a decision tree-based fault classi f ier is proposed to detect and classify various DC faults. The Change Identification Filter is applied to the average and differential current components, to detect the first instant of fault occurrence (above threshold) and register a Change Identified Point (CIP). Further, if a CIP is registered for a positive or negative line, only three samples of currents (i.e., CIP and each side of CIP) are sent to the proposed TKEO algorithm, which produces their respective 8 indices through which the, fault can be detected along with its classification. The new approach enables quicker detection allowing utility grids to be restored as soon as possible. This novel approach also reduces computing complexity and the time required to identify faults with classification. The importance and accuracy of the proposed scheme are also thor oughly tested and compared with other methods for various faults on HVDC transmission lines.     

The synthesis of pixelated metamaterial cross polarizer using binary wind driven optimization algorithm

Microsystem Technologies - In this paper synthesis of two wideband Metamaterial Cross Polarizer (MCPs) is proposed. The synthesis of proposed MCPs is done by using Binary Wind Driven Optimization...