Estimating windblown PM-10 emissions from vacant urban land using GIS

This paper presents a Geographic Information Systems (GIS)-based methodology to estimate annual area-wide airborne particulate matter with an aerodynamic diameter of less than 10 microm (PM-10) emissions, and identify zones with high emissions in order to efficiently implement mitigation strategies. Application of the methodology is demonstrated using the land disposal boundary within Clark County, NV as the study area, which is currently classified as a non-attainment area by United States Environmental Protection Agency (US EPA). The estimated PM-10 emissions depend on the extent of disturbed vacant land area, undisturbed vacant land area, emission factors by soil group, and wind speeds. Portable wind tunnel field test data were used to estimate emission factors at 78 sites in the study area. Portable wind tunnel results were categorized by the wind speed range and the corresponding site soil group in order to estimate emission factors by soil group and the wind speed range. Wind speed data were obtained from the Clark County Health District's air quality monitoring stations. The proximal area over which the wind speeds are same is obtained by constructing "Thiessen" polygons around each wind speed monitoring station. PM-10 emissions were estimated as a function of the extent of disturbed vacant lands, the measured or estimated erodibility of the soil surfaces, and the intensity, duration and frequency of erosive wind events.     

A new configuration of two-level 48-pulse VSCs based STATCOM for voltage regulation

In this paper, a new configuration of STATCOM (Static Compensator) with constant DC link voltage is proposed for the voltage regulation. The proposed STATCOM consists of eight sets of two-level double-way Voltage Source Converters (VSCs). Each double-way VSC consists of two six-pulse VSCs connected through an open winding transformer unit. The phase-angle difference between these two VSCs is varied for the reactive power control. The proposed STATCOM model is developed using MATLAB/Simulink, SimPowerSystems (SPS) toolboxes and dynamic performance is studied for the change in the reference reactive power, the terminal voltage reference and voltage control under switching on an inductive and a capacitive loads. Simulation results are presented to demonstrate the voltage regulation capability of the STATCOM under these conditions.     

Gene dosage effect on starch structure studied using maize polygenic model containing ae and su1 mutant alleles

The aim of this work was to enhance our understanding on the gene dosage effect on starch structure. Two mutant alleles, ae and su1, were selected for this study. With regard to their genetic functions, ae and su1 mutations are at two opposite extremes; therefore ae and su1 constituted an ideal pair of mutant alleles for manipulating starch structures. A full set of dosage combinations of ae and su1 were constructed in the maize W64A inbred line, and matured kernels were subjected to starch structure analysis. Scanning electron microscopy showed that starch granule morphology was affected by high doses of ae and su1 alleles. X-ray powder diffraction showed that 3 doses of su1 were not able to change the crystalline pattern of starch, whereas 3 doses of ae transformed A-type pattern to B-type. Size-exclusion chromatography showed that homozygous ae, su1, and ae su1 led to drastic change of starch structure from that of non-mutant. In addition, starches from certain ae and su1 dosage combinations were different from those of homozygous genotypes. This study will lay further foundation towards genetic modification of starch for desirable functional properties in food.     

Correction to: Performance Analysis of Cooperative Spectrum Sensing Network Using Optimization Technique in Different Fading Channels

Wireless Personal Communications - In order to reduce the cost of logistics distribution, a capacitated open vehicle routing problem with split deliveries by order is studied. According to the...     

Physical layer impairment-aware shared path protection in wavelength-routed optical networks

The Journal of Supercomputing - In this paper, physical layer impairment (PLI)-aware shared path protection (SPP) scheme for single-link failures in transparent optical WDM mesh networks is...     

Detection of shellcodes in drive-by attacks using kernel machines

In this paper, we propose a light-weight framework using kernel machines for the detection of shellcodes used in drive-by download attacks. As the shellcodes are passed in webpages as JavaScript strings, we studied the effectiveness of the proposed approach on about 9850 shellcodes and 10000 JavaScript strings collected from the wild. Our analysis shows that the trained SVMs (Support Vector Machines) classified with an accuracy of over 99 %. Our evaluation of the trained SVM models with different proportions of training datasets proved to perform consistently with an average accuracy of 99.51 % and the proposed static approach proved to be effective against detecting even the polymorphic shellcode variants. The performance of our approach was compared to an emulation based approach and observed that our approach performed with slightly better accuracies by consuming about 33 % of the time consumed by the emulation based approach.     

Prioritizing Groundwater Monitoring in Data Sparse Regions using Atanassov Intuitionistic Fuzzy Sets (A-IFS)

Water quality index (WQI) is a single measure that is commonly used to prioritize water wells and manage groundwater resources. WQI is pragmatic as it combines several water quality parameters into a single index. However, the process of aggregation is imprecise and suffers from uncertainties in measurements and subjective specification of weights. The goal of this study is to demonstrate how Atanassov’s Intuitionistic Fuzzy Sets (A-IFS) can be used to aggregate water quality parameters into a composite index to rank and prioritize groundwater wells. The A-IFS weighted geometric mean (A-IFS-WGM) method and the A-IFS based Technique for Order of Preference by Similarity to Ideal Solution (A-IFS-TOPSIS) using Euclidean (A-IFS-TOPSIS-E) and Hamming (A-IFS-TOPSIS-H) are introduced and illustrated to prioritize and rank water supply wells in a fast growing yet poorly studied area in Guntur, Andhra Pradesh, India. The concept of A-IFS entropy is also presented to directly ascertain weights from the data. This objective selection of weights from the data eliminates the subjectivity and difficulties associated with assigning relative importance to different water quality parameters. The results of the study indicate that the weights obtained using the entropy methods are consistent with the geochemical characteristics of the regional aquifer. The A-IFS-WGM method is more sensitive to weights compared to the A-IFS-TOPSIS methods which are influenced to a larger extent by the membership and non-membership values (ratings). Special consideration must be placed on ascribing the hesitation margin of the decision maker and identifying the membership values for non-preference as the methods exhibit greater sensitivity to these factors. The developed methods provide pragmatic data-driven approaches to prioritize and rank groundwater wells within a monitoring network.     

“String and bead” model of copper modified polycarbosilane: synthesis and applications

Journal of Materials Science - The synthesis of metal modified polycarbosilanes is currently an area of significant activity. These polymers can be processed to advanced materials such as ceramic...