Consistency of least squares estimators of AR(2) Model

In this paper, ordinary least squares (OLS) method will be used to estimate the parameters of the auto-regressive model without constant of order two. Moreover, the convergence in probability (the consistency property) of the estimates is proved

Design and constructability of funicular arched steel truss (FAST) false-work

The commercially available systems currently used in construction require high initial cost, take time to be erected and reduce the space in the construction site for the movement of material, equipment and labor as they prevent movement underneath them. The FAST system depends on developing a new false-work system depending on the concept of the funicular arch. It decreases the cost of the false-work as it uses less material and therefore needs lower initial cost than the commercially available systems. Further, the new system is environmentally friendly as it achieves a range between 45% and 50% saving in the amount of CO2 emitted to air due to the use of less material. The savings in the material used in the FAST system ranges between 45% to 51% depending on the covered area and it also provides more space in the construction site for the materials, equipment and workers to move underneath the system. The system also decreases the time needed for erection by range between 67% and 80% depending on the area and consequently helps in saving time and cost. To prove all of these advantages, experimental work is conducted on full scale models to study the mechanical and structural properties of the system

Low Complexity Selective Adaptive Multicarrier DS-CDMA Receiver

In this paper, selective adaptive (SA) receiver for Multicarrier Direct Sequence Code Division Multiple Access (MC DS-CDMA) system is presented. This receiver has high performance and at the same time reduces the multiple access interference (MAI) of the MC DS-CDMA) system with low computational complexity. The performance of SA receiver is measured in terms of the bit error rate (BER). An upper bound expression of the BER for the SA receiver under Rayleigh fading channel condition is derived and validated by computer simulations. Moreover, the implementation complexities of the SA receiver is compared with the Adaptive Parallel Interference Cancellation (APIC) receiver.

FROM RIVERS TO OCEANS: A COMPARISON OF CONTRASTING AQUATIC ECOSYSTEMS USING BENTHIC SIZE SPECTRA

This thesis uses a range of different size spectra to compare contrasting benthic habitats in the aquatic realm. Temporal and spatial variation in benthic size spectra were investigated across a full salinity gradient (i.e. from freshwater, through estuarine to marine) in the River Yealm, south Devon, in order to gauge the influence of large differences in taxonomy and evolutionary history. Abundance and biomass size spectra showed a similar pattern among sites in all seasons but winter, suggesting that the size structure of benthic communities may be similar in sites with very different community compositions. A subsequent study comparing size spectra across salinity by employing artificial substrata suggested that substratum type also had little effect on the size structure of these benthic communities. A technique was developed for obtaining microbial size distributions for benthic communities and showed that microbial size structures were also similar between the marine and freshwater sites within the Yealm system. A final study demonstrated that the shape of size spectra was clearly affected by metal contamination. Size spectra across a salinity gradient -(i.e. from freshwater to lower estuary) in the highly contaminated Fal system were very different to those in the uncontaminated Yealm, due mostly to the low macrofaunal abundance in the former. This thesis is the first to assess patterns in benthic size spectra across a full salinity range in the same system. It is hoped that it will provide a base line for further studies in this exciting research area in macroecology and that biomass spectra might also prove useful as metrics for biomonitoring.Plymouth Marine Laborator

Recursive Detection of M-Ary Signals over Fast Varying Mobile Communication Channel

          Mobile radio is characterized by a fast time varying channel. Conventional detectors which designed optimal for non-fading channel exhibit a limited performance in fast time varying channel. In this paper a recursive detector for M-ary signals over fast time varying mobile communication channel is introduced. The proposed detector continuously estimates the channel directly within the metric calculation of the log-likelihood function in a recursive manner. The estimation of the channel is performed by the covariance form of the recursive least square approach. The performance of the detector is evaluated in terms of the misdetection probability. The effects of timing and phase offsets on the performance of detector are examined by simulation. Simulation results show that the proposed detector can accommodate the fast time varying channel with adequate performance

Stability of a monotonic solution of a non-autonomous multidimensional delay differential equation of arbitrary (fractional) order

We are concerned here with the existence of monotonic and uniformly asymptotically stable solution of an initial-value problem of non-autonomous delay differential equations of arbitrary (fractional) orders

Multivariate discretization of continuous valued attributes.

The area of Knowledge discovery and data mining is growing rapidly. Feature Discretization is a crucial issue in Knowledge Discovery in Databases (KDD), or Data Mining because most data sets used in real world applications have features with continuously values. Discretization is performed as a preprocessing step of the data mining to make data mining techniques useful for these data sets. This thesis addresses discretization issue by proposing a multivariate discretization (MVD) algorithm. It begins withal number of common discretization algorithms like Equal width discretization, Equal frequency discretization, Naïve; Entropy based discretization, Chi square discretization, and orthogonal hyper planes. After that comparing the results achieved by the multivariate discretization (MVD) algorithm with the accuracy results of other algorithms. This thesis is divided into six chapters, covering a few common discretization algorithms and tests these algorithms on a real world datasets which varying in size and complexity, and shows how data visualization techniques will be effective in determining the degree of complexity of the given data set. We have examined the multivariate discretization (MVD) algorithm with the same data sets. After that we have classified discrete data using artificial neural network single layer perceptron and multilayer perceptron with back propagation algorithm. We have trained the Classifier using the training data set, and tested its accuracy using the testing data set. Our experiments lead to better accuracy results with some data sets and low accuracy results with other data sets, and this is subject ot the degree of data complexity then we have compared the accuracy results of multivariate discretization (MVD) algorithm with the results achieved by other discretization algorithms. We have found that multivariate discretization (MVD) algorithm produces good accuracy results in comparing with the other discretization algorithm