Membrane application for recovery and reuse of water from treated tannery wastewater

Secondary treated tannery wastewater contains high concentrations of Total Dissolved Solids (TDS) and other residual organic impurities, which cannot be removed by conventional treatment method. A pilot plant membrane system with a designed processing capacity of 1 m³/h, comprising of nano and reverse osmosis (RO) membrane units, accompanied by several pre-treatment operations, was evaluated in order to further treat and reuse the tannery wastewater. The maximum TD S removal efficiency of the polyamide RO membrane was more than 98%. The permeate recovery of about 78% was achieved. The water recovered from the membrane system, which had very low TDS concentration, was reused for wet finishing process in the tanneries. The reject concentrate obtained from the operation was sent to solar evaporation pans. It was evident from the study that the membrane system can successfully be applied for recovery of water from secondary treated tannery effluent, provided a suitable and effective pretreatment system prior to membrane system is employed. Combining nano and RO membranes improved the life of the membranes and permeate recovery rate.     

Analysis and design of digital predictive controller for PFC Cuk converter

A digital predictive control strategy for Power Factor Correction (PFC) is presented in this paper. The duty cycles required to achieve unity power factor in one half line period are calculated in advance by using a predictive algorithm and implemented using low cost PIC Microcontroller. A single stage PFC circuit controlled by these pre-calculated duty cycles can achieve sinusoidal current waveform. The output voltage of PFC circuit is regulated by an outer PI controller. A low frequency, small signal model of the rectifier is developed in order to design a PI voltage controller. A prototype of front end AC–DC converter followed by DC–DC Cuk converter controlled by a PIC Microcontroller is developed. Both the simulation and experimental results reveal that the proposed digital predictive strategy provides low THD, high power factor and better performance due to its lower calculation requirement and simple implementation.     

Optimization techniques for spectrum handoff in cognitive radio networks using cluster based cooperative spectrum sensing

Wireless Networks - Spectrum handoff has an undesirable effect in utilizing the space for Secondary user (SU) in the spectrum, which causes a handoff delay in cognitive radio network. The SU...     

Determination of the structure and orientation of organic molecules tethered to flat graphitic carbon by ATR-FT-IR and Raman spectroscopy

Mono- and multilayers of nitroazobenzene (NAB), azobenzene (AB), nitrobiphenyl (NBP), biphenyl (BP), and fluorene (FL) were covalently bonded to flat pyrolyzed photoresist films (PPF) by electrochemical reduction of their diazonium derivatives. The structure and orientation of the molecular layers were probed with ATR-FT-IR and Raman spectroscopy. A hemispherical germanium ATR element used with p-polarized light at 65 degrees incidence angle yielded high signal/noise IR spectra for monolayer coverage of molecules on PPF. The IR spectra are dominated by in-plane vibrational modes in the 1000-2000-cm(-1) spectral range but also exhibit weaker out-of-plane deformations in the 650-1000-cm(-1) region. The average tilt angle with respect to the surface normal for the various molecules varied from 31.0 +/- 4.5 degrees for NAB to 44.2 +/- 5.4 degrees for FL with AB, NBP, and BP exhibiting intermediate adsorption geometries. Raman intensity ratios of NAB and AB for p- and s-polarized incident light support the conclusion that the chemisorbed molecules are in a predominantly upright orientation. The results unequivocally indicate that molecules electroreduced from their diazonium precursors are not chemisorbed flat on the PPF surface, but rather at an angle, similar to the behavior of Au/thiol self-assembled monolayers, Langmuir-Blodgett films, and porphyrin molecules chemisorbed thermally on silicon and PPF from alkyne and alkene precursors.     

Tuning of PEM fuel cell model parameters for prediction of steady state and dynamic performance under various operating conditions

Many models are available with various degrees of complexity to study the behaviour of Proton Exchange Membrane Fuel Cells (PEMFC) under varying operating conditions. To our knowledge no model has been developed from single cells to multiple cells with increased electrode area for PEMFC stacks along with power conditioners, by considering the dynamic characteristics of the fuel cells under the influence of stoichiometry, humidity ratio and their response during their integration with power conditioners. We have developed a model using Matlab to study the transient response of the cell for 30 cm², which has been extended to a multicell stack of 1.2 kW capacity of electrode area 150 cm². The developed model has been validated using PEMFC single cells and stacks, by considering partial pressure of hydrogen, oxygen, and water as three states, anode fuel utilization and all three losses. This model is proposed to evaluate the transient response of all the stacks developed at Centre for Fuel Cell Technology (CFCT) ranging from a few watts to 10 kW that are integrated with various power conditioners depending on the applications.     

Streptococcus thermophilus strains of plant origin as dairy starters: Isolation and characterisation

Streptococcus thermophilus strains have been isolated mainly from dairy environments. To prospect for new strains of S. thermophilus, isolation was made from different plant sources. In this study, 74 plant isolates were characterised as S. thermophilus by a polyphasic approach and by 16S rRNA sequencing. The isolates were further evaluated for their physiological and biochemical properties. Plant isolates exhibited good acid production and varying proteolytic activity. All the isolates showed acetaldehyde and capsular exopolysaccharide (EPS) production and few revealed diacetyl production. In contrast to industrial strains, six isolates were able to ferment galactose and 25 were found to have no urease activity. Both the plant isolates and reference dairy cultures were found to possess similar physiological and biochemical properties and can be considered for developing new starters.     

Capsule network‐based data pruning in wireless sensor networks

The development of the wireless sensor networks (WSN) being deployed among numerous application for its sensing capabilities is increasing at a very fast tread. Its distributed nature and ability to extend communication even to the inaccessible areas beyond communication range that lacks human intervention has made it even more attractive in a wide space of applications. Confined with numerous sensing nodes distributed over a wide area, the WSN incurs certain limitations as it is battery powered. Many developed routing enhancements with power and energy efficiency lacked in achieving the significant improvement in the performance. So, the paper proposes a machine learning system (capsule network) and technique (data pruning) for WSN involved in the real world observations to have knowledge‐based learning from the experience for an intelligent way of handling the dynamic and real environment without the intervention of the humans. The WSN cluster‐based routing aided with capsule network and data pruning proffered in paper enables the WSN to have a prolonged network lifetime, energy efficiency, minimized delay, and enhanced throughput by reducing the energy usage and extending communication within the limited battery availability. The proposed system is validated in the network simulator and compared with the WSN without ML to check for the performance enhancements of the WSN with ML inclusions in terms of quality of service enhancements, network lifetime, packet delivery ratio, and energy to evince the efficacy of the WSN with capsule network‐based data pruning.     

Assessment of white layer in hardened AISI 52100 steel and its prediction using grinding power

In the present work, the effect of various grinding mechanisms on white layer (WL) formation in AISI 52100 steel is studied using two types of alumina grains, one produced by sol–gel process and the other by conventional fusion. Further, a novel approach is proposed on predicting the WL formation using grinding power. This study correlates the power variation with the change in the metallurgical aspects of the work material. WL of about 56 µm thickness is observed in the material ground by worn out sol–gel alumina wheel. However, no WL is present in the material ground by fused alumina wheel. High toughness in sol–gel alumina led to generation of wear flats with increasing grinding passes and transformed the dominant grinding mechanism from shearing to plowing and sliding. This increases the temperature in the grinding zone, which was the reason for WL formation. Change in the dominant grinding mechanisms from shearing is found to increase the grinding power. Since the change in dominant grinding mechanisms is the cause for WL formation, the increase in grinding power is found to be a good measure in predicting the WL formation. The predictability of WL formation by grinding power is further validated by comparing the power variation in grinding process by both the grinding wheels.     

Green-Inspired Fabrication of Silver Nanoparticles and Examine its Potential In-Vitro Cytotoxic and Antibacterial Activities

Journal of Inorganic and Organometallic Polymers and Materials - The present work demonstrates the non-hazardous and environmentally benevolent green fabrication of silver nanoparticles using...     

An Efficient Optimized Handover in Cognitive Radio Networks Using Cooperative Spectrum Sensing

Cognitive radio systems necessitate the incorporation of cooperative spectrum sensing among cognitive users to increase the reliability of detection. We have found that cooperative spectrum sensing is not only advantageous, but is also essential to avoid interference with any primary users. Interference by licensed users becomes a chief concern and issue, which affects primary as well as secondary users leading to restrictions in spectrum sensing in cognitive radios. When the number of cognitive users increases, the overheads of the systems, which are meant to report the sensing results to the common receiver, which becomes massive. When the spectrum, which is in use becomes unavailable or when the licensed user takes the allocated band, these networks have the capability of changing their operating frequencies. In addition, cognitive radio networks are seen to have the unique capability of sensing the spectrum range and detecting any spectrum, which has been left underutilized. Further this capability of recognizing the spectrum range based on the dimensions detected, allows for determination of the band, which may be utilized. The main objective of this paper is to analyze the cognitive radio’s spectrum sensing ability and evolving a self-configured system with dynamic intelligence networks without causing any interference to the primary user. The paper also brings focus to the quantitative analysis of the two spectrum sensing techniques namely; Energy Detection and Band Limited White Noise Detection. The estimation technique for detecting spectrum noise is based on the detection of probability and probability of false alarms at different Signal-to-Noise Ratio (SNR) levels using Additive White Gaussian Noise signal (AWGN). The efficiency of the proposed Cooperative CUSUM spectrum sensing algorithm performs better than existing optimal rules based on a single observation spectrum sensing techniques under cooperative networks.