Sensing Methods for Two-Target and Four-Target Detection in Time-Constrained Vector Poisson and Gaussian Channels

In this dissertation we consider a sensor scheduling or resource management problem for a vector Poisson and Gaussian channels. The input is a binary random vector and the output is a set of conditionally independent Poisson or Gaussian random variables. The objective is to design a scaling matrix, which is a linear transformation whose purpose is to entangle the different inputs, under a total given energy/time constraint. The two metrics are adopted to quantify the performance of the designed scaling matrix: mutual information and Bayesian inference. In other words, it is an experimental design problem where the objective is to glean the information about the binary inputs and perform the classification of the input random vector in a fixed time-resource, that is transmitted through a vector Poisson and Gaussian channel, based on the output observations. No optimal solution is claimed in this dissertation for the above problem for either of the Poisson or Gaussian channels; from either of the two perspectives: mutual information or Bayes detection. However, time-symmetry does exist in the said problem. It is further noted that the problem is concave in its domain (i.e. sensing times) from mutual information criterion; and this is based on the observations in the computational results. If this concavity does exist in the problem then together with the time-symmetry result; it can be deduced that the optimal solution has a symmetry too; and that would reduce the exponentially rising dimensionality of the search-space to the linear one (w.r.t dimension of the input random vector). However, concavity of the objective function in the Bayes framework does not exist. Further, it is noted that the classification criterion in the above two channels; and mutual information criterion do not generally lead to the same solution when subjected to the same fixed time constraint and model parameters. It is also noted that the combinatorial explosion is inevitable, that occurs while addressing the problem through computational means, even with exploiting the inherent time-symmetry and the concavity in the objective. This curse of the dimensionality is the main obstacle in exploring the problem for targets greater than four (i.e. for dimension of the input vector greater than 4)

Novel support materials for jetting-based additive manufacturing processes

Inkjet printing (jetting) technology, due to its high speed of operation and accuracy, is utilised in Additive Manufacturing (AM) of three dimensional parts. Commercially available AM processes that use jetting technology include three dimensional printing (3DP by Z-Corporation), Polyjet (by Objet), Multi Jet Modelling (MJM by 3D Systems) and three dimensional printing by Solidscape. Apart from 3D Printing by Z-corporation, all the other jetting based processes require a support material to successfully build a part. The support material provides a base to facilitate the removal of the part from the build platform and it helps manufacturing of cavities, holes and overhanging features. These support materials present challenges in terms of their removability and reusability. This research is therefore, aimed towards finding a support material composition that can be used with jetting based AM processes. The support material should be easily removable either by melting or by dissolution and also, if possible, it should be reusable. AM processes often process materials with poor mechanical properties and therefore, the parts produced by these processes have limited functionality. In an attempt to obtain complex shaped, functional parts made of nylon (i.e. Polyamide 6), a new jetting based AM process is under research at Loughborough University. The process uses two different mixtures of caprolactam (i.e. the monomer used to produce polyamide). These mixtures are to be jetted using inkjet heads and subsequently polymerised into polyamide 6. Therefore, another aim of this research was to consider the support material s suitability for jetting of caprolactam. Two different polymers were researched which included Pluronic F-127 and methylcellulose (MC). Both these polymers are known for gel formation upon heating in aqueous solutions. Due to the inhibition of polymerisation of polyamide 6 by the presence of water, non-aqueous solvents such as ethylene glycol, propylene glycol and butylene glycol were studied. Since both F-127 and MC in the glycols mentioned above had not been studied before, all the compositions prepared and investigated in this report were novel. F-127 did not show gel formation in propylene and butylene glycol but formed a gel in ethylene glycol at a concentration of 25% (w/w) F-127. MC, on the other hand, showed gel formation upon cooling in all the three glycols at concentrations as low as 5% for ethylene glycol and 1% for both propylene and butylene glycol. These compositions were characterized using experimental techniques such as Fourier Transform Infrared (FTIR) spectroscopy, hot stage microscopy, differential scanning calorimetry (DSC) and X-ray diffraction (XRD). A mechanism of gelation for both F-127 and MC in glycols is presented based on the results of these characterisation techniques. Viscosity and surface tension measurements along with the texture analysis of selected compositions were also performed to evaluate their suitability for jetting. All these compositions, due to their water solubility and/or low melting temperatures (i.e. near 500C) present the advantage of ease of removal. Removal by melting at low temperatures can also provide reusability of these support materials and thus advantages such as reduction in build cost and environmental effect can be achieved

Determinants of working capital management efficiency: Case study of Pakistani automotive and engineering firms listed in Karachi Stock Exchange

This Study is conducted to determine the determinants of working capital management efficiency of automotive and engineering firms listed in Karachi Stock Exchange of Pakistan. Cash Conversion Cycle, Days sales Inventory, Days Payable Outstanding and Days Sales Outstanding are the explanatory variables. Whereas the descriptive statistics, Pearson’s Bivariate correlation analysis and ordinary pooled least square with fixed effect model are applied to investigate the significance of panel data set. It is quarterly based and secondary data in nature that comprises of 9 firms for 5 years. The observations are taken from financial years 2006 to 2010 of the listed firms. In spite of these a questionnaire is also filled by the firm’s financial representatives during the research on Enterprise Resource Planning (ERP) which shows positive results or the efficiency of working capital management. It is concluded that to keep the working capital efficient cash conversion cycle must be shortest. For this there is need of tight collection policy and liberal payment policy while the inventory management must be efficient by reviewing the inventory policy