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 right
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
loose-coupling. 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. There are many articles and research
reports indicates that failure rate in outsourcing is very high but at the
same time research indicates that successful outsourcing projects
adds tangible and intangible benefits to the service consumer.
Business executives and policy makers in the west should not afraid
of outsourcing but they should choose the right strategy through the
use of emerging technology to significantly reduce the failure rate in
outsourcing.
Abstract: In this paper we introduce a novel method for
the characterization of synchronziation and coupling effects
in multivariate time series that can be used for the analysis
of EEG or ECoG signals recorded during epileptic seizures.
The method allows to visualize the spatio-temporal evolution
of synchronization and coupling effects that are characteristic
for epileptic seizures. Similar to other methods proposed for
this purpose our method is based on a regression analysis.
However, a more general definition of the regression together
with an effective channel selection procedure allows to use the
method even for time series that are highly correlated, which
is commonly the case in EEG/ECoG recordings with large
numbers of electrodes. The method was experimentally tested
on ECoG recordings of epileptic seizures from patients with
temporal lobe epilepsies. A comparision with the results from
a independent visual inspection by clinical experts showed
an excellent agreement with the patterns obtained with the
proposed method.
Abstract: A sequential decision problem, based on the task ofidentifying the species of trees given acoustic echo data collectedfrom them, is considered with well-known stochastic classifiers,including single and mixture Gaussian models. Echoes are processedwith a preprocessing stage based on a model of mammalian cochlearfiltering, using a new discrete low-pass filter characteristic. Stoppingtime performance of the sequential decision process is evaluated andcompared. It is observed that the new low pass filter processingresults in faster sequential decisions.
Abstract: This study describes a capillary-based device
integrated with the heating and cooling modules for polymerase chain
reaction (PCR). The device consists of the reaction
polytetrafluoroethylene (PTFE) capillary, the aluminum blocks, and is
equipped with two cartridge heaters, a thermoelectric (TE) cooler, a
fan, and some thermocouples for temperature control. The cartridge
heaters are placed into the heating blocks and maintained at two
different temperatures to achieve the denaturation and the extension
step. Some thermocouples inserted into the capillary are used to obtain
the transient temperature profiles of the reaction sample during
thermal cycles. A 483-bp DNA template is amplified successfully in
the designed system and the traditional thermal cycler. This work
should be interesting to persons involved in the high-temperature
based reactions and genomics or cell analysis.
Abstract: In this paper, a new proposed system for Persian
printed numeral characters recognition with emphasis on
representation and recognition stages is introduced. For the first time,
in Persian optical character recognition, geometrical central moments
as character image descriptor and fuzzy min-max neural network for
Persian numeral character recognition has been used. Set of different
experiments on binary images of regular, translated, rotated and
scaled Persian numeral characters has been done and variety of
results has been presented. The best result was 99.16% correct
recognition demonstrating geometrical central moments and fuzzy
min-max neural network are adequate for Persian printed numeral
character recognition.
Abstract: Vernonia divergens Benth., commonly known as
“Insulin Plant” (Fam: Asteraceae) is a potent sugar killer. Locally the
leaves of the plant, boiled in water are successfully administered to a
large number of diabetic patients. The present study evaluates the
putative anti-diabetic ingredients, isolated from the in vivo and in
vitro grown plantlets of V. divergens for their antimicrobial and
anticancer activities. Sterilized explants of nodal segments were
cultured on MS (Musashige and Skoog, 1962) medium in presence of
different combinations of hormones. Multiple shoots along with
bunch of roots were regenerated at 1mg l-1 BAP and 0.5 mg l-1 NAA.
Micro-plantlets were separated and sub-cultured on the double
strength (2X) of the above combination of hormones leading to
increased length of roots and shoots. These plantlets were
successfully transferred to soil and survived well in nature. The
ethanol extract of plantlets from both in vivo & in vitro sources were
prepared in soxhlet extractor and then concentrated to dryness under
reduced pressure in rotary evaporator. Thus obtainedconcentrated
extracts showed significant inhibitory activity against gram
negative bacteria like Escherichia coli and Pseudomonas
aeruginosa but no inhibition was found against gram positive
bacteria. Further, these ethanol extracts were screened for in vitro
percentage cytotoxicity at different time periods (24 h, 48 h and 72 h)
of different dilutions. The in vivo plant extract inhibited the growth of
EAC mouse cell lines in the range of 65, 66, 78, and 88% at 100, 50,
25 & 12.5μg mL-1 but at 72 h of treatment. In case of the extract of in
vitro origin, the inhibition was found against EAC cell lines even at
48h. During spectrophotometric scanning, the extracts exhibited
different maxima (ʎ) - four peaks in in vitro extracts as against single
in in vivo preparation suggesting the possible change in the nature of
ingredients during micropropagation through tissue culture
techniques.
Abstract: In order to make conventional implicit algorithm to be applicable in large scale parallel computers , an interface prediction and correction of discontinuous finite element method is presented to solve time-dependent neutron transport equations under 2-D cylindrical geometry. Domain decomposition is adopted in the computational domain.The numerical experiments show that our parallel algorithm with explicit prediction and implicit correction has good precision, parallelism and simplicity. Especially, it can reach perfect speedup even on hundreds of processors for large-scale problems.
Abstract: Energy dissipation in drops has been investigated by
physical models. After determination of effective parameters on the
phenomenon, three drops with different heights have been
constructed from Plexiglas. They have been installed in two existing
flumes in the hydraulic laboratory. Several runs of physical models
have been undertaken to measured required parameters for
determination of the energy dissipation. Results showed that the
energy dissipation in drops depend on the drop height and discharge.
Predicted relative energy dissipations varied from 10.0% to 94.3%.
This work has also indicated that the energy loss at drop is mainly
due to the mixing of the jet with the pool behind the jet that causes
air bubble entrainment in the flow. Statistical model has been
developed to predict the energy dissipation in vertical drops denotes
nonlinear correlation between effective parameters. Further an
artificial neural networks (ANNs) approach was used in this paper to
develop an explicit procedure for calculating energy loss at drops
using NeuroSolutions. Trained network was able to predict the
response with R2 and RMSE 0.977 and 0.0085 respectively. The
performance of ANN was found effective when compared to
regression equations in predicting the energy loss.
Abstract: This work presents an approach for the construction of a hybrid color-texture space by using mutual information. Feature extraction is done by the Laws filter with SVM (Support Vectors Machine) as a classifier. The classification is applied on the VisTex database and a SPOT HRV (XS) image representing two forest areas in the region of Rabat in Morocco. The result of classification obtained in the hybrid space is compared with the one obtained in the RGB color space.
Abstract: This paper analyses the unsteady, two-dimensional
stagnation point flow of an incompressible viscous fluid over a flat
sheet when the flow is started impulsively from rest and at the same
time, the sheet is suddenly stretched in its own plane with a velocity
proportional to the distance from the stagnation point. The partial
differential equations governing the laminar boundary layer forced
convection flow are non-dimensionalised using semi-similar
transformations and then solved numerically using an implicit finitedifference
scheme known as the Keller-box method. Results
pertaining to the flow and heat transfer characteristics are computed
for all dimensionless time, uniformly valid in the whole spatial region
without any numerical difficulties. Analytical solutions are also
obtained for both small and large times, respectively representing the
initial unsteady and final steady state flow and heat transfer.
Numerical results indicate that the velocity ratio parameter is found
to have a significant effect on skin friction and heat transfer rate at
the surface. Furthermore, it is exposed that there is a smooth
transition from the initial unsteady state flow (small time solution) to
the final steady state (large time solution).
Abstract: With optimized bandwidth and latency discrepancy ratios, Node Gain Scores (NGSs) are determined and used as a basis for shaping the max-heap overlay. The NGSs - determined as the respective bandwidth-latency-products - govern the construction of max-heap-form overlays. Each NGS is earned as a synergy of discrepancy ratio of the bandwidth requested with respect to the estimated available bandwidth, and latency discrepancy ratio between the nodes and the source node. The tree leads to enhanceddelivery overlay multicasting – increasing packet delivery which could, otherwise, be hindered by induced packet loss occurring in other schemes not considering the synergy of these parameters on placing the nodes on the overlays. The NGS is a function of four main parameters – estimated available bandwidth, Ba; individual node's requested bandwidth, Br; proposed node latency to its prospective parent (Lp); and suggested best latency as advised by source node (Lb). Bandwidth discrepancy ratio (BDR) and latency discrepancy ratio (LDR) carry weights of α and (1,000 - α ) , respectively, with arbitrary chosen α ranging between 0 and 1,000 to ensure that the NGS values, used as node IDs, maintain a good possibility of uniqueness and balance between the most critical factor between the BDR and the LDR. A max-heap-form tree is constructed with assumption that all nodes possess NGS less than the source node. To maintain a sense of load balance, children of each level's siblings are evenly distributed such that a node can not accept a second child, and so on, until all its siblings able to do so, have already acquired the same number of children. That is so logically done from left to right in a conceptual overlay tree. The records of the pair-wise approximate available bandwidths as measured by a pathChirp scheme at individual nodes are maintained. Evaluation measures as compared to other schemes – Bandwidth Aware multicaSt architecturE (BASE), Tree Building Control Protocol (TBCP), and Host Multicast Tree Protocol (HMTP) - have been conducted. This new scheme generally performs better in terms of trade-off between packet delivery ratio; link stress; control overhead; and end-to-end delays.
Abstract: In this article, we present a web server based solution
for implementing a system for intelligent navigation. In this solution
we use real time collected data and traffic history to establish the best
route for navigation. This is a low cost solution that is easily to
implement and extend. There is no need any infrastructure at road
network level except only a device that collect data about traffic in
key road crossing. The presented solution creates a strong base for
traffic pursuit and offers an infrastructure for navigation applications.
Abstract: Unsatisfactory effectiveness of software systems
development and enhancement projects is one of the main reasons
why in software engineering there are attempts being made to use
experiences coming from other engineering disciplines. In spite of
specificity of software product and process a belief had come out that
the execution of software could be more effective if these objects
were subject to measurement – as it is true in other engineering
disciplines for which measurement is an immanent feature. Thus
objective and reliable approaches to the measurement of software
processes and products have been sought in software engineering for
several dozens of years already. This may be proved, among others,
by the current version of CMMI for Development model. This paper
is aimed at analyzing the approach to the software processes and
products measurement proposed in the latest version of this very
model, indicating growing acceptance for this issue in software
engineering.
Abstract: In this paper we propose a new knowledge model using
the Dempster-Shafer-s evidence theory for image segmentation and
fusion. The proposed method is composed essentially of two steps.
First, mass distributions in Dempster-Shafer theory are obtained from
the membership degrees of each pixel covering the three image
components (R, G and B). Each membership-s degree is determined by
applying Fuzzy C-Means (FCM) clustering to the gray levels of the
three images. Second, the fusion process consists in defining three
discernment frames which are associated with the three images to be
fused, and then combining them to form a new frame of discernment.
The strategy used to define mass distributions in the combined
framework is discussed in detail. The proposed fusion method is
illustrated in the context of image segmentation. Experimental
investigations and comparative studies with the other previous methods
are carried out showing thus the robustness and superiority of the
proposed method in terms of image segmentation.
Abstract: In this work, I present a review on Sparse Distributed
Memory for Small Cues (SDMSCue), a variant of Sparse Distributed
Memory (SDM) that is capable of handling small cues. I then conduct
and show some cognitive experiments on SDMSCue to test its
cognitive soundness compared to SDM. Small cues refer to input
cues that are presented to memory for reading associations; but have
many missing parts or fields from them. The original SDM failed to
handle such a problem. SDMSCue handles and overcomes this
pitfall. The main idea in SDMSCue; is the repeated projection of the
semantic space on smaller subspaces; that are selected based on the
input cue length and pattern. This process allows for Read/Write
operations using an input cue that is missing a large portion.
SDMSCue is augmented with the use of genetic algorithms for
memory allocation and initialization. I claim that SDM functionality
is a subset of SDMSCue functionality.
Abstract: In a none-super-competitive environment the concepts
of closed system, management control remains to be the dominant
guiding concept to management. The merits of closed loop have been
the sources of most of the management literature and culture for
many decades. It is a useful exercise to investigate and poke into the
dynamics of the control loop phenomenon and draws some lessons to
use for refining the practice of management. This paper examines the
multitude of lessons abstracted from the behavior of the Input /output
/feedback control loop model, which is the core of control theory.
There are numerous lessons that can be learned from the insights this
model would provide and how it parallels the management dynamics
of the organization. It is assumed that an organization is basically a
living system that interacts with the internal and external variables. A
viable control loop is the one that reacts to the variation in the
environment and provide or exert a corrective action. In managing
organizations this is reflected in organizational structure and
management control practices. This paper will report findings that
were a result of examining several abstract scenarios that are
exhibited in the design, operation, and dynamics of the control loop
and how they are projected on the functioning of the organization.
Valuable lessons are drawn in trying to find parallels and new
paradigms, and how the control theory science is reflected in the
design of the organizational structure and management practices. The
paper is structured in a logical and perceptive format. Further
research is needed to extend these findings.
Abstract: In today-s hip hop world where everyone is running
short of time and works hap hazardly,the similar scene is common on
the roads while in traffic.To do away with the fatal consequences of
such speedy traffics on rushy lanes, a software to analyse and keep
account of the traffic and subsequent conjestion is being used in the
developed countries. This software has being implemented and used
with the help of a suppprt tool called Critical Analysis Reporting
Environment.There has been two existing versions of this tool.The
current research paper involves examining the issues and probles
while using these two practically. Further a hybrid architecture is
proposed for the same that retains the quality and performance of
both and is better in terms of coupling of components , maintainence
and many other features.
Abstract: Electronics Products that achieve high levels of integrated communications, computing and entertainment, multimedia features in small, stylish and robust new form factors are winning in the market place. Due to the high costs that an industry may undergo and how a high yield is directly proportional to high profits, IC (Integrated Circuit) manufacturers struggle to maximize yield, but today-s customers demand miniaturization, low costs, high performance and excellent reliability making the yield maximization a never ending research of an enhanced assembly process. With factors such as minimum tolerances, tighter parameter variations a systematic approach is needed in order to predict the assembly process. In order to evaluate the quality of upcoming circuits, yield models are used which not only predict manufacturing costs but also provide vital information in order to ease the process of correction when the yields fall below expectations. For an IC manufacturer to obtain higher assembly yields all factors such as boards, placement, components, the material from which the components are made of and processes must be taken into consideration. Effective placement yield depends heavily on machine accuracy and the vision of the system which needs the ability to recognize the features on the board and component to place the device accurately on the pads and bumps of the PCB. There are currently two methods for accurate positioning, using the edge of the package and using solder ball locations also called footprints. The only assumption that a yield model makes is that all boards and devices are completely functional. This paper will focus on the Monte Carlo method which consists in a class of computational algorithms (information processed algorithms) which depends on repeated random samplings in order to compute the results. This method utilized in order to recreate the simulation of placement and assembly processes within a production line.
Abstract: Colored Petri Nets (CPN) are very known kind of
high level Petri nets. With sound and complete semantics, rewriting
logic is one of very powerful logics in description and verification of
non-deterministic concurrent systems. Recently, CPN semantics are
defined in terms of rewriting logic, allowing us to built models by
formal reasoning. In this paper, we propose an automatic translation
of CPN to the rewriting logic language Maude. This tool allows
graphical editing and simulating CPN. The tool allows the user
drawing a CPN graphically and automatic translating the graphical
representation of the drawn CPN to Maude specification. Then,
Maude language is used to perform the simulation of the resulted
Maude specification. It is the first rewriting logic based environment
for this category of Petri Nets.
Abstract: The objective of this research is to develop an advanced driver assistance system characterized with the functions of lane departure warning (LDW), forward collision warning (FCW) and adaptive front-lighting system (AFS). The system is mainly configured a CCD/CMOS camera to acquire the images of roadway ahead in association with the analysis made by an image-processing unit concerning the lane ahead and the preceding vehicles. The input image captured by a camera is used to recognize the lane and the preceding vehicle positions by image detection and DROI (Dynamic Range of Interesting) algorithms. Therefore, the system is able to issue real-time auditory and visual outputs of warning when a driver is departing the lane or driving too close to approach the preceding vehicle unwittingly so that the danger could be prevented from occurring. During the nighttime, in addition to the foregoing warning functions, the system is able to control the bending light of headlamp to provide an immediate light illumination when making a turn at a curved lane and adjust the level automatically to reduce the lighting interference against the oncoming vehicles driving in the opposite direction by the curvature of lane and the vanishing point estimations. The experimental results show that the integrated vehicle image system is robust to most environments such as the lane detection and preceding vehicle detection average accuracy performances are both above 90 %.