Abstract: Zirconium diamine and triamine complexes can possess biological activities. These complexes were synthesised via the reaction of equimolar quantities of 1,10-phenanthroline {NC3H3(C6H2)NC3H3} (L1) or 4-4-amino phenazone {ONC6H5(NH)CH(NH2} (L2) or diphenyl carbizon {HNNCO(NH)2(C6H5)} (L3) with a Zirconium Salt {ZrOCl2} in a 1:1 ratio to form complexes [{NC3H3(C6H2)NC3H3}ZrOCl2}] [ZrOCl2L1], [{(O2NC6H4(NH)(NH2)}ZrOCl2] [ZrOCl2L2] and [{HNNCO(NH)2(C6H5)ZrOCl2}] [ZrOCl2L3] respectively. They were characterised using Fourier Transform Infrared (FT-IR) and UV-Visible spectroscopy. Also a variable temperature study of these complexes was completed, using UV-Visible spectroscopy to observe electronic transitions under temperature control. Also a DFT study was done on these complexes via the information from FT-IR and UV-Visible spectroscopy.
These complexes were found to show different inhibition to the growth of bacterial strains of Bacillus spp. & Klebsiella spp. & E. coli & Proteus spp. & Pseudomona spp. at different concentrations (0.001, 0.2 and 1M). For better understanding these complexes were examined by using a Density Functional Theory (DFT) calculation.
Abstract: This paper argues that fostering mutual understanding in landscape planning is as much about the planners educating stakeholder groups as the stakeholders educating the planners. In other words it is an epistemological agreement as to the meaning and nature of place, especially where an effort is made to go beyond the quantitative aspects, which can be achieved by the phenomenological experience of the Virtual Reality (VR) environment. This education needs to be a bi-directional process in which distance can be both temporal as well as spatial separation of participants, that there needs to be a common framework of understanding in which neither 'side' is disadvantaged during the process of information exchange and it follows that a medium such as VR offers an effective way of overcoming some of the shortcomings of traditional media by taking advantage of continuing technological advances in Information, Technology and Communications (ITC). In this paper we make particular reference to this as an extension to Geographical Information Systems (GIS). VR as a two-way communication tool offers considerable potential particularly in the area of Public Participation GIS (PPGIS). Information rich virtual environments that can operate over broadband networks are now possible and thus allow for the representation of large amounts of qualitative and quantitative information 'side-by-side'. Therefore, with broadband access becoming standard for households and enterprises alike, distributed virtual reality environments have great potential to contribute to enabling stakeholder participation and mutual learning within the planning context.
Abstract: Requirements management is critical to software
delivery success and project lifecycle. Requirements management
and their traceability provide assistance for many software
engineering activities like impact analysis, coverage analysis,
requirements validation and regression testing. In addition
requirements traceability is the recognized component of many
software process improvement initiatives. Requirements traceability
also helps to control and manage evolution of a software system.
This paper aims to provide an evaluation of current requirements
management and traceability tools. Management and test managers
require an appropriate tool for the software under test. We hope,
evaluation identified here will help to select the efficient and
effective tool.
Abstract: Cytogenetic analysis still remains the gold standard method for prenatal diagnosis of trisomy 21 (Down syndrome, DS). Nevertheless, the conventional cytogenetic analysis needs live cultured cells and is too time-consuming for clinical application. In contrast, molecular methods such as FISH, QF-PCR, MLPA and quantitative Real-time PCR are rapid assays with results available in 24h. In the present study, we have successfully used a novel MGB TaqMan probe-based real time PCR assay for rapid diagnosis of trisomy 21 status in Down syndrome samples. We have also compared the results of this molecular method with corresponding results obtained by the cytogenetic analysis. Blood samples obtained from DS patients (n=25) and normal controls (n=20) were tested by quantitative Real-time PCR in parallel to standard G-banding analysis. Genomic DNA was extracted from peripheral blood lymphocytes. A high precision TaqMan probe quantitative Real-time PCR assay was developed to determine the gene dosage of DSCAM (target gene on 21q22.2) relative to PMP22 (reference gene on 17p11.2). The DSCAM/PMP22 ratio was calculated according to the formula; ratio=2 -ΔΔCT. The quantitative Real-time PCR was able to distinguish between trisomy 21 samples and normal controls with the gene ratios of 1.49±0.13 and 1.03±0.04 respectively (p value
Abstract: In this paper a new fast simplification method is
presented. Such method realizes Karnough map with large
number of variables. In order to accelerate the operation of the
proposed method, a new approach for fast detection of group
of ones is presented. Such approach implemented in the
frequency domain. The search operation relies on performing
cross correlation in the frequency domain rather than time one.
It is proved mathematically and practically that the number of
computation steps required for the presented method is less
than that needed by conventional cross correlation. Simulation
results using MATLAB confirm the theoretical computations.
Furthermore, a powerful solution for realization of complex
functions is given. The simplified functions are implemented
by using a new desigen for neural networks. Neural networks
are used because they are fault tolerance and as a result they
can recognize signals even with noise or distortion. This is
very useful for logic functions used in data and computer
communications. Moreover, the implemented functions are
realized with minimum amount of components. This is done
by using modular neural nets (MNNs) that divide the input
space into several homogenous regions. Such approach is
applied to implement XOR function, 16 logic functions on one
bit level, and 2-bit digital multiplier. Compared to previous
non- modular designs, a clear reduction in the order of
computations and hardware requirements is achieved.
Abstract: In this paper a functional interpretation of quantum
theory (QT) with emphasis on quantum field theory (QFT) is proposed.
Besides the usual statements on relations between a functions
initial state and final state, a functional interpretation also contains
a description of the dynamic evolution of the function. That is, it
describes how things function. The proposed functional interpretation
of QT/QFT has been developed in the context of the author-s work
towards a computer model of QT with the goal of supporting
the largest possible scope of QT concepts. In the course of this
work, the author encountered a number of problems inherent in the
translation of quantum physics into a computer program. He came
to the conclusion that the goal of supporting the major QT concepts
can only be satisfied, if the present model of QT is supplemented
by a "functional interpretation" of QT/QFT. The paper describes a
proposal for that
Abstract: Rounding of coefficients is a common practice in
hardware implementation of digital filters. Where some coefficients
are very close to zero or one, as assumed in this paper, this rounding
action also leads to some computation reduction. Furthermore, if the
discarded coefficient is of high order, a reduced order filter is
obtained, otherwise the order does not change but computation is
reduced. In this paper, the Least Squares approximation to rounded
(or discarded) coefficient FIR filter is investigated. The result also
succinctly extended to general type of FIR filters.
Abstract: Neural networks are well known for their ability to
model non linear functions, but as statistical methods usually does,
they use a no parametric approach thus, a priori knowledge is not
obvious to be taken into account no more than the a posteriori
knowledge. In order to deal with these problematics, an original way
to encode the knowledge inside the architecture is proposed. This
method is applied to the problem of the evapotranspiration inside
karstic aquifer which is a problem of huge utility in order to deal
with water resource.
Abstract: In this study, any possible differences between mathematics beliefs and anxiety of prospective elementary mathematics teachers have been investigated according to their gender. In this purpose, 1st, 2nd, 3rd and 4th grade students from a Government University in Turkey were selected as a sample. Mathematics Teaching Anxiety Scale (MATAS) and Beliefs About Mathematics Survey (BAMS) has been used as data collection tools. As a result of the study, it has been observed that prospective male teachers have more instrumentalist approach in learning mathematics than females according to their mathematical beliefs. On the other hand, females have more mathematics teaching anxiety than males especially, for subject knowledge in mathematics and selfconfidence.
Abstract: In this paper, a new learning algorithm based on a
hybrid metaheuristic integrating Differential Evolution (DE) and
Reduced Variable Neighborhood Search (RVNS) is introduced to train
the classification method PROAFTN. To apply PROAFTN, values of
several parameters need to be determined prior to classification. These
parameters include boundaries of intervals and relative weights for
each attribute. Based on these requirements, the hybrid approach,
named DEPRO-RVNS, is presented in this study. In some cases, the
major problem when applying DE to some classification problems
was the premature convergence of some individuals to local optima.
To eliminate this shortcoming and to improve the exploration and
exploitation capabilities of DE, such individuals were set to iteratively
re-explored using RVNS. Based on the generated results on
both training and testing data, it is shown that the performance of
PROAFTN is significantly improved. Furthermore, the experimental
study shows that DEPRO-RVNS outperforms well-known machine
learning classifiers in a variety of problems.
Abstract: Morphogenesis is the process that underpins the selforganised development and regeneration of biological systems. The ability to mimick morphogenesis in artificial systems has great potential for many engineering applications, including production of biological tissue, design of robust electronic systems and the co-ordination of parallel computing. Previous attempts to mimick these complex dynamics within artificial systems have relied upon the use of evolutionary algorithms that have limited their size and complexity. This paper will present some insight into the underlying dynamics of morphogenesis, then show how to, without the assistance of evolutionary algorithms, design cellular architectures that converge to complex patterns.
Abstract: This work presents a new approach of securing a
wireless network. The configuration is focused on securing &
Protecting wireless network traffic for a small network such as a
home or dorm room. The security Mechanism provided both
authentication, allowing only known authorized users access to the
wireless network, and encryption, preventing anyone from reading
the wireless traffic. The mentioned solution utilizes the open source
free S/WAN software which implements the Internet Protocol
Security –IPSEC. In addition to wireless components, wireless NIC
in PC and wireless access point needs a machine running Linux to act
as security gateway. While the current configuration assumes that the
wireless PC clients are running Linux, Windows XP/VISTA/7 based
machines equipped with VPN software which will allow to interface
with this configuration.
Abstract: Postgraduate education is generally aimed at providing in-depth knowledge and understanding that include general philosophy in the world sciences, management, technologies, applications and other elements closely related to specific areas. In most universities, besides core and non-core subjects, a thesis is one of the requirements for the postgraduate student to accomplish before graduating. This paper reports on the empirical investigation into attributes that are associated with the obstacles to thesis accomplishment among postgraduate students. Using the quantitative approach the experiences of postgraduate students were tapped. Findings clearly revealed that information seeking, writing skills and other factors which refer to supervisor and time management, in particular, are recognized as contributory factors which positively or negatively influence postgraduates’ thesis accomplishment. Among these, writing skills dimensions were found to be the most difficult process in thesis accomplishment compared to information seeking and other factors. This pessimistic indication has provided some implications not only for the students but supervisors and institutions as a whole.
Abstract: This paper investigates the problem of spreading
sequence and receiver code synchronization techniques for satellite
based CDMA communications systems. The performance of CDMA
system depends on the autocorrelation and cross-correlation
properties of the used spreading sequences. In this paper we propose
the uses of chaotic Lu system to generate binary sequences for
spreading codes in a direct sequence spread CDMA system. To
minimize multiple access interference (MAI) we propose the use of
genetic algorithm for optimum selection of chaotic spreading
sequences. To solve the problem of transmitter-receiver
synchronization, we use the passivity controls. The concept of
semipassivity is defined to find simple conditions which ensure
boundedness of the solutions of coupled Lu systems. Numerical
results are presented to show the effectiveness of the proposed
approach.
Abstract: Consider a mass production of HDD arms where
hundreds of CNC machines are used to manufacturer the HDD arms.
According to an overwhelming number of machines and models of
arm, construction of separate control chart for monitoring each HDD
arm model by each machine is not feasible. This research proposed a
strategy to optimize the SPC management on shop floor. The
procedure started from identifying the clusters of the machine with
similar manufacturing performance using clustering technique. The
three way control chart ( I - MR - R ) is then applied to each
clustered group of machine. This proposed research has
advantageous to the manufacturer in terms of not only better
performance of the SPC but also the quality management paradigm.
Abstract: Estimation of runoff water quality parameters is required to determine appropriate water quality management options. Various models are used to estimate runoff water quality parameters. However, most models provide event-based estimates of water quality parameters for specific sites. The work presented in this paper describes the development of a model that continuously simulates the accumulation and wash-off of water quality pollutants in a catchment. The model allows estimation of pollutants build-up during dry periods and pollutants wash-off during storm events. The model was developed by integrating two individual models; rainfall-runoff model, and catchment water quality model. The rainfall-runoff model is based on the time-area runoff estimation method. The model allows users to estimate the time of concentration using a range of established methods. The model also allows estimation of the continuing runoff losses using any of the available estimation methods (i.e., constant, linearly varying or exponentially varying). Pollutants build-up in a catchment was represented by one of three pre-defined functions; power, exponential, or saturation. Similarly, pollutants wash-off was represented by one of three different functions; power, rating-curve, or exponential. The developed runoff water quality model was set-up to simulate the build-up and wash-off of total suspended solids (TSS), total phosphorus (TP) and total nitrogen (TN). The application of the model was demonstrated using available runoff and TSS field data from road and roof surfaces in the Gold Coast, Australia. The model provided excellent representation of the field data demonstrating the simplicity yet effectiveness of the proposed model.
Abstract: As a method of expanding a higher-order tensor data to tensor products of vectors we have proposed the Third-order Orthogonal Tensor Product Expansion (3OTPE) that did similar expansion as Higher-Order Singular Value Decomposition (HOSVD). In this paper we provide a computation algorithm to improve our previous method, in which SVD is applied to the matrix that constituted by the contraction of original tensor data and one of the expansion vector obtained. The residual of the improved method is smaller than the previous method, truncating the expanding tensor products to the same number of terms. Moreover, the residual is smaller than HOSVD when applying to color image data. It is able to be confirmed that the computing time of improved method is the same as the previous method and considerably better than HOSVD.
Abstract: AAM has been successfully applied to face alignment,
but its performance is very sensitive to initial values. In case the initial
values are a little far distant from the global optimum values, there
exists a pretty good possibility that AAM-based face alignment may
converge to a local minimum. In this paper, we propose a progressive
AAM-based face alignment algorithm which first finds the feature
parameter vector fitting the inner facial feature points of the face and
later localize the feature points of the whole face using the first
information. The proposed progressive AAM-based face alignment
algorithm utilizes the fact that the feature points of the inner part of the
face are less variant and less affected by the background surrounding
the face than those of the outer part (like the chin contour). The
proposed algorithm consists of two stages: modeling and relation
derivation stage and fitting stage. Modeling and relation derivation
stage first needs to construct two AAM models: the inner face AAM
model and the whole face AAM model and then derive relation matrix
between the inner face AAM parameter vector and the whole face
AAM model parameter vector. In the fitting stage, the proposed
algorithm aligns face progressively through two phases. In the first
phase, the proposed algorithm will find the feature parameter vector
fitting the inner facial AAM model into a new input face image, and
then in the second phase it localizes the whole facial feature points of
the new input face image based on the whole face AAM model using
the initial parameter vector estimated from using the inner feature
parameter vector obtained in the first phase and the relation matrix
obtained in the first stage. Through experiments, it is verified that the
proposed progressive AAM-based face alignment algorithm is more
robust with respect to pose, illumination, and face background than the
conventional basic AAM-based face alignment algorithm.
Abstract: In this work we present an efficient approach for face
recognition in the infrared spectrum. In the proposed approach
physiological features are extracted from thermal images in order to
build a unique thermal faceprint. Then, a distance transform is used
to get an invariant representation for face recognition. The obtained
physiological features are related to the distribution of blood vessels
under the face skin. This blood network is unique to each individual
and can be used in infrared face recognition. The obtained results are
promising and show the effectiveness of the proposed scheme.
Abstract: This paper investigates the effects of knowledge-based acceleration feedback control integrated with Automatic Generation Control (AGC) to enhance the quality of frequency control of governing system. The Intelligent Acceleration Feedback Controller (IAFC) is proposed to counter the over and under frequency occurrences due to major load change in power system network. Therefore, generator tripping and load shedding operations can be reduced. Meanwhile, the integration of IAFC with AGC, a well known Load-Frequency Control (LFC) is essential to ensure the system frequency is restored to the nominal value. Computer simulations of frequency response of governing system are used to optimize the parameters of IAFC. As a result, there is substantial improvement on the LFC of governing system that employing the proposed control strategy.