A Framework for Heterogeneous Resource Allocation in Sensor-Cloud Environment

Wireless Personal Communications - With the advent of sensor technologies, cloud applications are able to acquire sensed data from remotely located sensors which are geographically distributed....     

Synthesis of SBA 15 graphene oxide composite membrane using phenol–formaldehyde resin pore modifier for CO2 separation

Present study highlights the development of carbon-loaded SBA 15 membrane on clay-alumina tubular support and its performance on the CO₂ separation efficiencies from different mixture gases. To modify the large pores of SBA 15 by graphitic carbon, low molecular weight phenol–formaldehyde (PF) resin was incorporated into the mesoporous channel followed by calcination under inert atmosphere. The modified ordered pore structure of the membrane has been characterized by low-angle XRD, TEM, and pore size distribution analysis. The chemical state of the deposited carbon phase into the SBA 15 pores was analyzed by X-ray photoelectron and Raman spectroscopy. Carbon having graphitic nature mainly in graphene oxide has been deposited into the mesopore of SBA 15 resulting decrease in pore size from 8.9 to 1.0 nm. Finally, the developed SBA 15 carbon membranes were characterized by CO₂ permeation and separation selectivity of CO₂/CH₄, CO₂/CO. Highest CO₂/CH₄ separation factor was achieved as 16.9 with CO₂ permeance 13.6 × 10^–8 mol/m²/s/Pa at 200 kPa feed pressure by the 20% resin with 2 times coated membrane. In flue gas analysis, highest CO₂/CO separation factor of 32.8 was achieved. This study offers an observation on CO₂ separation from simulated BF gas for the first time and the results show the potential of the developed SBA 15/C composite membranes in commercial application.     

Ceria (La3+, Sr2+)/Carbonates Nanocomposite Electrolytes with High Electrical Conductivity for Low‐Temperature SOFCs

A series of ceria‐based nanocomposites consisting of lanthanum and strontium codoped ceria with composition Ce_0.89La_0.07Sr_0.04O_1.925 (CL7S4) and eutectic mixture of carbonates Li₂CO₃‐Na₂CO₃ (LNCO) have been prepared by mixing nanosize powders of CL7S4 and LNCO. Samples have been characterized using differential thermal analysis, X‐ray diffraction, scanning electron microscopy combined with energy‐dispersive spectroscopy, thermal expansion, and impedance spectroscopy. A sharp increase in ionic conductivity is observed in all the composite specimens corresponding to superionic transition. Sample containing 35 wt% of carbonate shows the maximum conductivity (2.56 × 10^?1 S/cm at 500°C) with activation energy of conduction, E_a 0.23 eV.     

A novel method of unburned hydrocarbons and NOx gases capture from vehicular exhaust using natural biosorbent

Automobile emissions are composed of NO_x and unburned hydrocarbon that contribute significantly to major environmental and health issues. In this study, encapsulated Moringa oleifera beads (EMBs) were synthesized using Moringa oleifera pod powder that was cross-linked with calcium alginate and used as a biosorbent for reducing the emission gas concentrations from the single-cylinder diesel engine. The breakthrough curve was attained from single and double stage of fixed bed column by the influence of temperature ranging from (80°C–120°C) ± 5°C with a feed flow rate varying from 8 to 10 kg hr^–1 and bed height varying from 15 to 30 cm. Based on the experimental results, the maximum biosorption capacity (q_o) was found to be 14.45 and 123.51 mg g^–1 for HC and NO_x, respectively, and was obtained at 80°C–90°C with double stage of BH–30cm under flow rate of 8 kg hr^–1. Further, breakthrough curves were investigated, and the experimental data were fitted using well-established models like Thomas, Yoon–Nelson, and Wang models. In addition, mass transfer models like Weber–Morris and Boyd were investigated to identify the rate-limiting step of the overall biosorption process.     

Membrane processing of used frying oils

Studies were conducted with used frying oils in a flat membrane batch cell using five different types of polymeric membranes to decrease the soluble degradation products. During membrane processing, triglycerides permeated preferentially compared to the majority of the polar compounds including oxidation products, polymers, and color compounds. Two of the composite membranes, NTGS-AX and NTGS-2200, selectively rejected polar compounds and oxidation products to the extent of 25–48% and 24–44% respectively. The reduction in Lovibond color values (5R+Y) was in the range of 83–93%. The viscosity of the used frying oil was reduced to the extent of 22%. The composite membranes were effective in reducing the soluble impurities, as well as insoluble particulates, without causing any undesirable changes to the oil. The membrane process appears to improve the life of used frying oils and does not have the disadvantages associated with the active filtration systems, however, for commercial application the permeate flux needs to be improved considerably.     

Sonochemical synthesis of LaMnO3 nano-powder

We report the preparation of LaMnO₃ nanosized powder by the sonochemical process. Sodium dodecyl sulphate (SDS) was used as surfactant, to prevent agglomeration. The particle size obtained in this method was 19–55 nm. The phase formation temperature of LaMnO₃ was 700 °C which is lower than other conventional processes. So sonochemical process is cost effective and it is more acceptable considering its ease of preparation in comparison to other conventional processes. Powder synthesized was characterized by measuring crystallite size, specific surface area, morphology and by thermal analysis. The particle sizes of the powders were controlled by calcinations schedule. Narrow size distribution and core and shell structure of the prepared powder was revealed by transmission electron microscopy.     

Structural features of arabinoxylans from Sonalika variety of wheat: comparison between whole wheat flour and wheat bran

Arabinoxylans (AX) were extracted from Sonalika variety of wheat (whole wheat flour and wheat bran) with barium hydroxide and sodium hydroxide and purified by a combination of alcohol precipitation and glucoamylase digestion. Structural features of purified AX were elucidated by methylation analysis, ¹³C NMR, FT‐IR, periodate oxidation and optical rotation measurements. The AX showed a backbone of xylose residues with β(1–4) linkages and were branched mainly through O‐3 of xylose residues. Completely branched xylosyl residues were also present. Copyright © 2003 Society of Chemical Industry     

LSALSA: accelerated source separation via learned sparse coding

Machine Learning - We propose an efficient algorithm for the generalized sparse coding (SC) inference problem. The proposed framework applies to both the single dictionary setting, where each data...     

Passenger flow prediction in bus transportation system using deep learning

The forecasting of bus passenger flow is important to the bus transit system’s operation. Because of the complicated structure of the bus operation system, it’s difficult to explain how passengers travel along different routes. Due to the huge number of passengers at the bus stop, bus delays, and irregularity, people are experiencing difficulties of using buses nowadays. It is important to determine the passenger flow in each station, and the transportation department may utilize this information to schedule buses for each region. In Our proposed system we are using an approach called the deep learning method with long short-term memory, recurrent neural network, and greedy layer-wise algorithm are used to predict the Karnataka State Road Transport Corporation (KSRTC) passenger flow. In the dataset, some of the parameters are considered for prediction are bus id, bus type, source, destination, passenger count, slot number, and revenue These parameters are processed in a greedy layer-wise algorithm to make it has cluster data into regions after cluster data move to the long short-term memory model to remove redundant data in the obtained data and recurrent neural network it gives the prediction result based on the iteration factors of the data. These algorithms are more accurate in predicting bus passengers. This technique handles the problem of passenger flow forecasting in Karnataka State Road Transport Corporation Bus Rapid Transit (KSRTCBRT) transportation, and the framework provides resource planning and revenue estimation predictions for the KSRTCBRT.

     

Improved phase estimation based on complete bispectrum and modified group delay

In this paper, a new method for extracting the system phase from the bispectrum of the system output has been proposed. This is based on the complete bispectral data computed in the frequency domain and modified group delay. The frequency domain bispectrum computation improves the frequency resolution and the modified group delay reduces the variance preserving the frequency resolution. The use of full bispectral data also reduces the variance as it is used for averaging. For the proposed method at a signal to noise ratio of 5dB, the reduction in root mean square error is in the range of 1.5–7 times over the other methods considered.