Abstract: Business and IT alignment has continued as a
top concern for business and IT executives for almost three
decades. Many researchers have conducted empirical studies on
the relationship between business-IT alignment and performance.
Yet, these approaches, lacking a social perspective, have had little
impact on sustaining performance and competitive advantage. In
addition to the limited alignment literature that explores
organisational learning that is represented in shared understanding,
communication, cognitive maps and experiences.
Hence, this paper proposes an integrated process that enables
social and intellectual dimensions through the concept of
organisational learning. In particular, the feedback and feedforward
process which provide a value creation across dynamic
multilevel of learning. This mechanism enables on-going
effectiveness through development of individuals, groups and
organisations, which improves the quality of business and IT
strategies and drives to performance.
Abstract: Wavelet transforms is a very powerful tools for image compression. One of its advantage is the provision of both spatial and frequency localization of image energy. However, wavelet transform coefficients are defined by both a magnitude and sign. While algorithms exist for efficiently coding the magnitude of the transform coefficients, they are not efficient for the coding of their sign. It is generally assumed that there is no compression gain to be obtained from the coding of the sign. Only recently have some authors begun to investigate the sign of wavelet coefficients in image coding. Some authors have assumed that the sign information bit of wavelet coefficients may be encoded with the estimated probability of 0.5; the same assumption concerns the refinement information bit. In this paper, we propose a new method for Separate Sign Coding (SSC) of wavelet image coefficients. The sign and the magnitude of wavelet image coefficients are examined to obtain their online probabilities. We use the scalar quantization in which the information of the wavelet coefficient to belong to the lower or to the upper sub-interval in the uncertainly interval is also examined. We show that the sign information and the refinement information may be encoded by the probability of approximately 0.5 only after about five bit planes. Two maps are separately entropy encoded: the sign map and the magnitude map. The refinement information of the wavelet coefficient to belong to the lower or to the upper sub-interval in the uncertainly interval is also entropy encoded. An algorithm is developed and simulations are performed on three standard images in grey scale: Lena, Barbara and Cameraman. Five scales are performed using the biorthogonal wavelet transform 9/7 filter bank. The obtained results are compared to JPEG2000 standard in terms of peak signal to noise ration (PSNR) for the three images and in terms of subjective quality (visual quality). It is shown that the proposed method outperforms the JPEG2000. The proposed method is also compared to other codec in the literature. It is shown that the proposed method is very successful and shows its performance in term of PSNR.
Abstract: One of the main challenges for one phase anaerobic digestion processes is the high concentration of NH4+ and PO4 3- ions
in the digested sludge supernatant. This project focuses on enhancing the removal of nutrients during the anaerobic digestion process through fixing both NH4+ and PO4 3- ions in the form of struvite (magnesium ammonium phosphate, MAP, MgNH4PO4.6H2O) within the anaerobic sludge. Batch anaerobic digestion tests showed that Mg2+ concentration in the range 279 – 812 mg/L had insignificant effect on CGP but incurred a slight increase in COD removal. The reactor that had soluble Mg2+:NH4+:PO43- at a molar ratio of 1.28:1:00:1:00 achieved the best performance enhancement of 8% increase in COD removal and 32% reduction in NH4+ in the reactor supernatant. Overall, the results show that there is a potential to optimise conventional anaerobic digestion such that supernatant lean in P and N, and sludge rich in nutrients are obtained.
Abstract: This paper provides a key driver-based conceptual framework that can be used to improve a firm-s success in commercializing technology and in new product innovation resulting from collaboration with other organizations through strategic alliances. Based on a qualitative study using an interview approach, strategic alliances of entrepreneurs in the food processing industry in Thailand are explored. This paper describes factors affecting decisions to collaborate through alliances. It identifies four issues: maintaining the efficiency of the value chain for production capability, adapting to present and future competition, careful assessment of value of outcomes, and management of innovation. We consider five driving factors: resource orientation, assessment of risk, business opportunity, sharing of benefits and confidence in alliance partners. These factors will be of interest to entrepreneurs and policy makers with regard to further understanding of the direction of business strategies.
Abstract: When acid is pumped into damaged reservoirs for
damage removal/stimulation, distorted inflow of acid into the
formation occurs caused by acid preferentially traveling into highly
permeable regions over low permeable regions, or (in general) into
the path of least resistance. This can lead to poor zonal coverage and
hence warrants diversion to carry out an effective placement of acid.
Diversion is desirably a reversible technique of temporarily reducing
the permeability of high perm zones, thereby forcing the acid into
lower perm zones.
The uniqueness of each reservoir can pose several challenges to
engineers attempting to devise optimum and effective diversion
strategies. Diversion techniques include mechanical placement and/or
chemical diversion of treatment fluids, further sub-classified into ball
sealers, bridge plugs, packers, particulate diverters, viscous gels,
crosslinked gels, relative permeability modifiers (RPMs), foams,
and/or the use of placement techniques, such as coiled tubing (CT)
and the maximum pressure difference and injection rate (MAPDIR)
methodology.
It is not always realized that the effectiveness of diverters greatly
depends on reservoir properties, such as formation type, temperature,
reservoir permeability, heterogeneity, and physical well
characteristics (e.g., completion type, well deviation, length of
treatment interval, multiple intervals, etc.). This paper reviews the
mechanisms by which each variety of diverter functions and
discusses the effect of various reservoir properties on the efficiency
of diversion techniques. Guidelines are recommended to help
enhance productivity from zones of interest by choosing the best
methods of diversion while pumping an optimized amount of
treatment fluid. The success of an overall acid treatment often
depends on the effectiveness of the diverting agents.
Abstract: The improvement of a filer case utilized to purify the
let-out smoke and smell in the production of Benjarong Ceramic is
studied through Participatory Action Research (PAR). This research
is aimed to protect smell, dirty smoke, and air pollution which are
effects of incomplete combustion in the production of Benjarong
ceramic. This research was conducted at Jongjint Benjarong Ceramic
Factory in Plai Bang, Bang Kruai, Nonthaburi Province,Thailand,
also 12 employees were interviewed for data collection. All collected
data were analyzed to develop and create solution to protect smoke
and smell pollution from Benjarong ceramic production.
The results revealed that the employees who have used the
developed filer cases are moderately satisfied. In addition to the
efficiency of developed smoke-and-smell filer cases, it was found
that Overall, the respondents were satisfied moderately with
efficiency of modified smoke and smell filter cases.
Abstract: Protection and proper management of archaeological heritage are an essential process of studying and interpreting the generations present and future. Protecting the archaeological heritage is based upon multidiscipline professional collaboration. This study aims to gather data by different sources (Photogrammetry and Geographic Information System (GIS)) integrated for the purpose of documenting one the of significant archeological sites (Ahl-Alkahf, Jordan). 3D modeling deals with the actual image of the features, shapes and texture to represent reality as realistically as possible by using texture. The 3D coordinates that result of the photogrammetric adjustment procedures are used to create 3D-models of the study area. Adding Textures to the 3D-models surfaces gives a 'real world' appearance to the displayed models. GIS system combined all data, including boundary maps, indicating the location of archeological sites, transportation layer, digital elevation model and orthoimages. For realistic representation of the study area, 3D - GIS model prepared, where efficient generation, management and visualization of such special data can be achieved.
Abstract: Mapping between local and global coordinates is an
important issue in finite element method, as all calculations are
performed in local coordinates. The concern arises when subparametric
are used, in which the shape functions of the field variable
and the geometry of the element are not the same. This is particularly
the case for C* elements in which the extra degrees of freedoms
added to the nodes make the elements sub-parametric. In the present
work, transformation matrix for C1* (an 8-noded hexahedron
element with 12 degrees of freedom at each node) is obtained using
equivalent C0 elements (with the same number of degrees of
freedom). The convergence rate of 8-noded C1* element is nearly
equal to its equivalent C0 element, while it consumes less CPU time
with respect to the C0 element. The existence of derivative degrees
of freedom at the nodes of C1* element along with excellent
convergence makes it superior compared with it equivalent C0
element.
Abstract: Cosmic showers, during the transit through space, produce
sub - products as a result of interactions with the intergalactic
or interstellar medium which after entering earth generate secondary
particles called Extensive Air Shower (EAS). Detection and analysis
of High Energy Particle Showers involve a plethora of theoretical and
experimental works with a host of constraints resulting in inaccuracies
in measurements. Therefore, there exist a necessity to develop a
readily available system based on soft-computational approaches
which can be used for EAS analysis. This is due to the fact that soft
computational tools such as Artificial Neural Network (ANN)s can be
trained as classifiers to adapt and learn the surrounding variations. But
single classifiers fail to reach optimality of decision making in many
situations for which Multiple Classifier System (MCS) are preferred
to enhance the ability of the system to make decisions adjusting
to finer variations. This work describes the formation of an MCS
using Multi Layer Perceptron (MLP), Recurrent Neural Network
(RNN) and Probabilistic Neural Network (PNN) with data inputs
from correlation mapping Self Organizing Map (SOM) blocks and
the output optimized by another SOM. The results show that the setup
can be adopted for real time practical applications for prediction
of primary energy and location of EAS from density values captured
using detectors in a circular grid.
Abstract: In Image processing the Image compression can improve
the performance of the digital systems by reducing the cost and
time in image storage and transmission without significant reduction
of the Image quality. This paper describes hardware architecture of
low complexity Discrete Cosine Transform (DCT) architecture for
image compression[6]. In this DCT architecture, common computations
are identified and shared to remove redundant computations
in DCT matrix operation. Vector processing is a method used for
implementation of DCT. This reduction in computational complexity
of 2D DCT reduces power consumption. The 2D DCT is performed
on 8x8 matrix using two 1-Dimensional Discrete cosine transform
blocks and a transposition memory [7]. Inverse discrete cosine
transform (IDCT) is performed to obtain the image matrix and
reconstruct the original image. The proposed image compression
algorithm is comprehended using MATLAB code. The VLSI design
of the architecture is implemented Using Verilog HDL. The proposed
hardware architecture for image compression employing DCT was
synthesized using RTL complier and it was mapped using 180nm
standard cells. . The Simulation is done using Modelsim. The
simulation results from MATLAB and Verilog HDL are compared.
Detailed analysis for power and area was done using RTL compiler
from CADENCE. Power consumption of DCT core is reduced to
1.027mW with minimum area[1].
Abstract: The SOM has several beneficial features which make
it a useful method for data mining. One of the most important
features is the ability to preserve the topology in the projection.
There are several measures that can be used to quantify the goodness
of the map in order to obtain the optimal projection, including the
average quantization error and many topological errors. Many
researches have studied how the topology preservation should be
measured. One option consists of using the topographic error which
considers the ratio of data vectors for which the first and second best
BMUs are not adjacent. In this work we present a study of the
behaviour of the topographic error in different kinds of maps. We
have found that this error devaluates the rectangular maps and we
have studied the reasons why this happens. Finally, we suggest a new
topological error to improve the deficiency of the topographic error.
Abstract: On-line (near infrared) spectroscopy is widely used to support the operation of complex process systems. Information extracted from spectral database can be used to estimate unmeasured product properties and monitor the operation of the process. These techniques are based on looking for similar spectra by nearest neighborhood algorithms and distance based searching methods. Search for nearest neighbors in the spectral space is an NP-hard problem, the computational complexity increases by the number of points in the discrete spectrum and the number of samples in the database. To reduce the calculation time some kind of indexing could be used. The main idea presented in this paper is to combine indexing and visualization techniques to reduce the computational requirement of estimation algorithms by providing a two dimensional indexing that can also be used to visualize the structure of the spectral database. This 2D visualization of spectral database does not only support application of distance and similarity based techniques but enables the utilization of advanced clustering and prediction algorithms based on the Delaunay tessellation of the mapped spectral space. This means the prediction has not to use the high dimension space but can be based on the mapped space too. The results illustrate that the proposed method is able to segment (cluster) spectral databases and detect outliers that are not suitable for instance based learning algorithms.
Abstract: An effective approach for realizing the binary tree structure, representing a combinational logic functionality with enhanced throughput, is discussed in this paper. The optimization in maximum operating frequency was achieved through delay minimization, which in turn was possible by means of reducing the depth of the binary network. The proposed synthesis methodology has been validated by experimentation with FPGA as the target technology. Though our proposal is technology independent, yet the heuristic enables better optimization in throughput even after technology mapping for such Boolean functionality; whose reduced CNF form is associated with a lesser literal cost than its reduced DNF form at the Boolean equation level. For cases otherwise, our method converges to similar results as that of [12]. The practical results obtained for a variety of case studies demonstrate an improvement in the maximum throughput rate for Spartan IIE (XC2S50E-7FT256) and Spartan 3 (XC3S50-4PQ144) FPGA logic families by 10.49% and 13.68% respectively. With respect to the LUTs and IOBUFs required for physical implementation of the requisite non-regenerative logic functionality, the proposed method enabled savings to the tune of 44.35% and 44.67% respectively, over the existing efficient method available in literature [12].
Abstract: The whole work is based on possibility to use Lego Mindstorms robotics systems to reduce costs. Lego Mindstorms consists of a wide variety of hardware components necessary to simulate, programme and test of robotics systems in practice. To programme algorithm, which simulates space using the ultrasonic sensor, was used development environment supplied with kit. Software Matlab was used to render values afterwards they were measured by ultrasonic sensor. The algorithm created for this paper uses theoretical knowledge from area of signal processing. Data being processed by algorithm are collected by ultrasonic sensor that scans 2D space in front of it. Ultrasonic sensor is placed on moving arm of robot which provides horizontal moving of sensor. Vertical movement of sensor is provided by wheel drive. The robot follows map in order to get correct positioning of measured data. Based on discovered facts it is possible to consider Lego Mindstorm for low-cost and capable kit for real-time modelling.
Abstract: Unsteady magnetohydrodynamics (MHD) boundary
layer flow and heat transfer over a continuously stretching surface in
the presence of radiation is examined. By similarity transformation,
the governing partial differential equations are transformed to a set of
ordinary differential equations. Numerical solutions are obtained by
employing the Runge-Kutta-Fehlberg method scheme with shooting
technique in Maple software environment. The effects of
unsteadiness parameter, radiation parameter, magnetic parameter and
Prandtl number on the heat transfer characteristics are obtained and
discussed. It is found that the heat transfer rate at the surface
increases as the Prandtl number and unsteadiness parameter increase
but decreases with magnetic and radiation parameter.
Abstract: In this paper, we construct and implement a new
Steganography algorithm based on learning system to hide a large
amount of information into color BMP image. We have used adaptive
image filtering and adaptive non-uniform image segmentation with
bits replacement on the appropriate pixels. These pixels are selected
randomly rather than sequentially by using new concept defined by
main cases with sub cases for each byte in one pixel. According to
the steps of design, we have been concluded 16 main cases with their
sub cases that covere all aspects of the input information into color
bitmap image. High security layers have been proposed through four
layers of security to make it difficult to break the encryption of the
input information and confuse steganalysis too. Learning system has
been introduces at the fourth layer of security through neural
network. This layer is used to increase the difficulties of the statistical
attacks. Our results against statistical and visual attacks are discussed
before and after using the learning system and we make comparison
with the previous Steganography algorithm. We show that our
algorithm can embed efficiently a large amount of information that
has been reached to 75% of the image size (replace 18 bits for each
pixel as a maximum) with high quality of the output.
Abstract: In this paper, we propose a new image segmentation approach for colour textured images. The proposed method for image segmentation consists of two stages. In the first stage, textural features using gray level co-occurrence matrix(GLCM) are computed for regions of interest (ROI) considered for each class. ROI acts as ground truth for the classes. Ohta model (I1, I2, I3) is the colour model used for segmentation. Statistical mean feature at certain inter pixel distance (IPD) of I2 component was considered to be the optimized textural feature for further segmentation. In the second stage, the feature matrix obtained is assumed to be the degraded version of the image labels and modeled as Markov Random Field (MRF) model to model the unknown image labels. The labels are estimated through maximum a posteriori (MAP) estimation criterion using ICM algorithm. The performance of the proposed approach is compared with that of the existing schemes, JSEG and another scheme which uses GLCM and MRF in RGB colour space. The proposed method is found to be outperforming the existing ones in terms of segmentation accuracy with acceptable rate of convergence. The results are validated with synthetic and real textured images.
Abstract: Cluster analysis is the name given to a diverse collection of techniques that can be used to classify objects (e.g. individuals, quadrats, species etc). While Kohonen's Self-Organizing Feature Map (SOFM) or Self-Organizing Map (SOM) networks have been successfully applied as a classification tool to various problem domains, including speech recognition, image data compression, image or character recognition, robot control and medical diagnosis, its potential as a robust substitute for clustering analysis remains relatively unresearched. SOM networks combine competitive learning with dimensionality reduction by smoothing the clusters with respect to an a priori grid and provide a powerful tool for data visualization. In this paper, SOM is used for creating a toroidal mapping of two-dimensional lattice to perform cluster analysis on results of a chemical analysis of wines produced in the same region in Italy but derived from three different cultivators, referred to as the “wine recognition data" located in the University of California-Irvine database. The results are encouraging and it is believed that SOM would make an appealing and powerful decision-support system tool for clustering tasks and for data visualization.
Abstract: This article is an extension and a practical application
approach of Wheeler-s NEBIC theory (Net Enabled Business
Innovation Cycle). NEBIC theory is a new approach in IS research
and can be used for dynamic environment related to new technology.
Firms can follow the market changes rapidly with support of the IT
resources. Flexible firms adapt their market strategies, and respond
more quickly to customers changing behaviors. When every leading
firm in an industry has access to the same IT resources, the way that
these IT resources are managed will determine the competitive
advantages or disadvantages of firm. From Dynamic Capabilities
Perspective and from newly introduced NEBIC theory by Wheeler,
we know that only IT resources cannot deliver customer value but
good configuration of those resources can guarantee customer value
by choosing the right emerging technology, grasping the economic
opportunities through business innovation and growth. We found
evidences in literature that SOA (Service Oriented Architecture) is a
promising emerging technology which can deliver the desired
economic opportunity through modularity, flexibility and loosecoupling.
SOA can also help firms to connect in network which can
open a new window of opportunity to collaborate in innovation and
right kind of outsourcing
Abstract: The paper deals with cartographic visualisation of
results of transport accessibility monitoring with the use of a semiautomated
method of unipolar anamorphosis, developed by the
authors in the GIS environment. The method is based on
transformation of distance in the map to values of a geographical
phenomenon. In the case of time accessibility it is based on
transformation of isochrones converted into the form of concentric
circles, taking into account selected topographic and thematic
elements in the map. The method is most suitable for analyses of
accessibility to or from a centre and for modelling its long-term
context.
The paper provides a detailed analysis of the procedures and
functionality of the method, discussing the issues of coordinates,
transformation, scale and visualisation. It also offers a discussion of
possible problems and inaccuracies. A practical application of the
method is illustrated by previous research results by the authors in
the filed of accessibility in Czechia.