Development of an innovative and environmentally sustainable solid waste stream treatment process.

Oily sludges and oil contaminated solid wastes are generated from various sources such as from a) interceptors in petrol stations, automobile garages and rail service stations b) tank oil bottoms from crude oil storage tanks c) drill cuttings from oil and gas exploration and d) Oil based drilling muds . The petroleum sludge wastes typically are water-in-oil emulsion that are stabilised by fine solids. The Hazardous Waste Directive classifies oily sludges and oil contaminated solids as hazardous waste due to its carcinogenic nature. The directive specifies that an oil concentration of more than 0.1% in solids have a risk of causing cancer to humans making it hazardous. Traditionally such wastes have been landfilled. Hazardous waste such as the above has higher landfill costs charged by the landfill operators and also higher landfill tax compared to non-hazardous waste. Such wastes generated throughout Scotland needs to be transported to England and Wales for suitable disposal or treatment and recovery. With the implementation of new legislations such as EU landfill directive the existing option of transportation and disposal turns out to be costly to the tune of £300 per tonne. Hence it is important to find an alternative option for treating such wastes locally in order to avoid transportation of these wastes and also position industries to offer an environmentally sustainable solid waste treatment system. This thesis reports a study of various technologies examined in the development of an oily sludge treatment process and summarises results from lab trials, site trials and site visits to technology suppliers. In addition to developing a treatment chain this report concludes by recommending that treatment of oily sludge from hazardous waste to inert waste standards can only be achieved utilising thermal treatment methods. This can either be plasma, microwave or infrared technology based thermal treatment and needs to be decided on a case to case basis. An indicative cost benefit analysis presented provides an indication of capital and operational expenditure for the above technology

Fuzzy information graph of epileptic seizures

The mathematical modelling of EEG signals provides valuable data to neurologists, and is heavily utilized in the diagnosis and treatment of epilepsy. The erratic nature of these signals, coupled with their lack of a consistent visible trend results in a high degree of difficulty in forming a statistical model to describe seizures. Working with Delia-normalized signals, the authors compute the associated Shannon entropies for three sets of data, and show via construction that the information flow during an epileptic seizure can be viewed as a type-2 fuzzy graph

A Peer-to-Peer Associative Memory Network for Intelligent Information Systems

The paper describes a highly-scalable associative memory network capable of handling multiple streams of input, which are processed and matched with the historical data (available within the network). The essence of the associative memory algorithm lies with in its highly parallel structure, which changes the emphasis from the high speed CPU based processing to network processing; capable of utilising a large number of low performance processors in a fully connected configuration. The approach is expected to facilitate the development of information systems capable of correlating multi-dimensional data inputs into human thought like constructs and thus exhibiting a level of self-awareness

Intuitionistic L-fuzzy sets and Intuitionistic N-fuzzy sets

In this paper we prove that the concept of intuitionistic N-fuzzy sets (briefly INFS) proposed by Akram et al in [5] is equivalent to ILFS and it’s not a generalization of IFS we concluded that IFS, ILFS, INFS and L-fuzzy sets are all equivalent

Multiple Access Channel Simulation

We study the problem of simulating a two-user multiple access channel over a multiple access network of noiseless links. Two encoders observe independent and identically distributed (i.i.d.) copies of a source random variable each, while a decoder observes i.i.d. copies of a side-information random variable. There are rate-limited noiseless communication links and independent pairwise shared randomness resources between each encoder and the decoder. The decoder has to output approximately i.i.d. copies of another random variable jointly distributed with the two sources and the side information. We are interested in the rate tuples which permit this simulation. This setting can be thought of as a multi-terminal generalization of the point-to-point channel simulation problem studied by Bennett et al. (2002) and Cuff (2013). General inner and outer bounds on the rate region are derived. For the specific case where the sources at the encoders are conditionally independent given the side-information at the decoder, we completely characterize the rate region. Our bounds recover the existing results on function computation over such multi-terminal networks. We then show through an example that an additional independent source of shared randomness between the encoders strictly improves the communication rate requirements, even if the additional randomness is not available to the decoder. Furthermore, we provide inner and outer bounds for this more general setting with independent pairwise shared randomness resources between all the three possible node pairs.Comment: 33 pages, 3 figure

Temporal discrete Z-number and its application in assessing EEG signal data of epileptic seizure

Analysis and modeling of a complex physical system, particularly EEG signals involved vague and uncertain information. The approach introduced by Kosanovic using temporal fuzzy set to model a complex system particularly the EEG signal does not address the problem of uncertainty for the time of occurrence. In this paper, an ordered discrete Z-number is used to construct temporal discrete Z-number to assess EEG signal data of an epileptic seizure for the first time. The proposed temporal discrete Z-number is able to accommodate the problem of uncertainty with regards to the time of occurrence for a given seizure by using and modifying the method for measuring the uncertainty of Z-number

Deep eutectic solvent pretreatment of water hyacinth for improved holocellulosic saccharification and fermentative co-production of xylitol and lipids using Rhodosporidium toruloides NCIM 3547

In this study, delignification of water hyacinth (WH) using a mild ionic liquid-like chemical deep eutectic solvent (DES) synthesized using choline chloride and urea was conducted and the process parameters were optimized by Box–Behnken design (BBD)-based response surface methodology (RSM). From the results, a delignification of 64.32 ± 4.08% (w/w) was obtained under 1:12.5 (biomass:DES ratio), 4.63 h (time) and 87 °C (temperature). Further, a dilute sulphuric acid (2%, v/v) hydrolysis was carried out to destabilize the hemicellulose that resulted in 23.7 ± 0.50 g/L of xylose. Fermentation of the obtained xylose was carried out using a red oleaginous yeast, Rhodosporidium toruloides NCIM 3547, with free and Ca2+-alginate-immobilized cells for xylitol production under microaerophilic conditions and obtained yields of 4.73 ± 0.40 g/L (168 h) and 9.18 ± 0.10 g/L (packed bed reactor with a retention time of 18 h), respectively. Further, when the same fermentation was performed under aerobic conditions about 40.93 ± 0.73% lipid accumulation was observed with free cells. For saccharification, Aspergillus-niger-derived cellulase was used and this resulted in a yield of 27.45 ± 0.04 g/L of glucose. The glucose-enriched hydrolysate was supplemented for fermentation under nitrogen starved conditions from which 46.81 ± 2.60% (w/w) lipid content was obtained