Abstract: Mobile Picture Puzzle is a mobile game application where the player use existing images stored in the mobile phone to create a puzzle to be played. This traditional picture puzzle is not so challenging once the player is familiar with the game. The objective of the developed mobile game application is to have a similar mobile game application that can provide the player with more challenging gaming experience. The developed mobile game application is also a mobile picture puzzle game application to create a puzzle to be played but instead of just using existing images that are stored, the personalised capability allows the player to use the built-in camera phone to capture an image and use the newly captured image to create the puzzle. The development of the mobile game application uses Symbian Operating System (OS), Mobile Media API (Application Programming Interface), Record Management System (RMS) storage and TiledLayer class from Game API.
Abstract: Many digital signal processing, techniques have been used to automatically distinguish protein coding regions (exons) from non-coding regions (introns) in DNA sequences. In this work, we have characterized these sequences according to their nonlinear dynamical features such as moment invariants, correlation dimension, and largest Lyapunov exponent estimates. We have applied our model to a number of real sequences encoded into a time series using EIIP sequence indicators. In order to discriminate between coding and non coding DNA regions, the phase space trajectory was first reconstructed for coding and non-coding regions. Nonlinear dynamical features are extracted from those regions and used to investigate a difference between them. Our results indicate that the nonlinear dynamical characteristics have yielded significant differences between coding (CR) and non-coding regions (NCR) in DNA sequences. Finally, the classifier is tested on real genes where coding and non-coding regions are well known.
Abstract: Saturated two-phase fluid flows are often subject to
pressure induced oscillations. Due to compressibility the vapor
bubbles act as a spring with an asymmetric non-linear characteristic.
The volume of the vapor bubbles increases or decreases differently if
the pressure fluctuations are compressing or expanding;
consequently, compressing pressure fluctuations in a two-phase pipe
flow cause less displacement in the direction of the pipe flow than
expanding pressure fluctuations. The displacement depends on the
ratio of liquid to vapor, the ratio of pressure fluctuations over average
pressure and on the exciting frequency of the pressure fluctuations.
In addition, pressure fluctuations in saturated vapor bubbles cause
condensation and evaporation within the bubbles and change
periodically the ratio between liquid to vapor, and influence the
dynamical parameters for the oscillation. The oscillations are
conforming to an isenthalpic process at constant enthalpy with no
heat transfer and no exchange of work.
The paper describes the governing non-linear equation for twophase
fluid oscillations with condensation and evaporation, and
presents steady state approximate solutions for free and for pressure
induced oscillations. Resonance criteria and stability are discussed.
Abstract: Project selection problems on management
information system (MIS) are often considered a multi-criteria
decision-making (MCDM) for a solving method. These problems
contain two aspects, such as interdependencies among criteria and
candidate projects and qualitative and quantitative factors of projects.
However, most existing methods reported in literature consider these
aspects separately even though these two aspects are simultaneously
incorporated. For this reason, we proposed a hybrid method using
analytic network process (ANP) and fuzzy logic in order to represent
both aspects. We then propose a goal programming model to conduct
an optimization for the project selection problems interpreted by a
hybrid concept. Finally, a numerical example is conducted as
verification purposes.
Abstract: Technology of thin film deposition is of interest in
many engineering fields, from electronic manufacturing to corrosion
protective coating. A typical deposition process, like that developed
at the University of Eindhoven, considers the deposition of a thin,
amorphous film of C:H or of Si:H on the substrate, using the
Expanding Thermal arc Plasma technique. In this paper a computing
procedure is proposed to simulate the flow field in a deposition
chamber similar to that at the University of Eindhoven and a
sensitivity analysis is carried out in terms of: precursor mass flow
rate, electrical power, supplied to the torch and fluid-dynamic
characteristics of the plasma jet, using different nozzles. To this
purpose a deposition chamber similar in shape, dimensions and
operating parameters to the above mentioned chamber is considered.
Furthermore, a method is proposed for a very preliminary evaluation
of the film thickness distribution on the substrate. The computing
procedure relies on two codes working in tandem; the output from
the first code is the input to the second one. The first code simulates
the flow field in the torch, where Argon is ionized according to the
Saha-s equation, and in the nozzle. The second code simulates the
flow field in the chamber. Due to high rarefaction level, this is a
(commercial) Direct Simulation Monte Carlo code. Gas is a mixture
of 21 chemical species and 24 chemical reactions from Argon plasma
and Acetylene are implemented in both codes. The effects of the
above mentioned operating parameters are evaluated and discussed
by 2-D maps and profiles of some important thermo-fluid-dynamic
parameters, as per Mach number, velocity and temperature. Intensity,
position and extension of the shock wave are evaluated and the
influence of the above mentioned test conditions on the film
thickness and uniformity of distribution are also evaluated.
Abstract: The accelerated growth in aircraft industries desire
effectual schemes, programs, innovative designs of advanced systems
to accomplishing the augmenting need for home-free air
transportation. In this paper, a contemporary conceptual design of an
airplane has been proposed without landing gear systems in order to
reducing accidents, time consumption, and to eliminating drawbacks
by using superconducting levitation phenomenon. This invention of
an airplane with superconductive material coating, on the solar plexus
region assist to reduce weight by approximately 4% of the total takeoff
weight, and cost effective. Moreover, we conjectured that
superconductor landing system reduces ground friction, mission fuel,
total drag, take-off and landing distance.
Abstract: This research focus on the intrusion detection system (IDS) development which using artificial immune system (AIS) with population based incremental learning (PBIL). AIS have powerful distinguished capability to extirpate antigen when the antigen intrude into human body. The PBIL is based on past learning experience to adjust new learning. Therefore we propose an intrusion detection system call PBIL-AIS which combine two approaches of PBIL and AIS to evolution computing. In AIS part we design three mechanisms such as clonal selection, negative selection and antibody level to intensify AIS performance. In experimental result, our PBIL-AIS IDS can capture high accuracy when an intrusion connection attacks.
Abstract: The purpose of this paper is to develop models that would enable predicting student success. These models could improve allocation of students among colleges and optimize the newly introduced model of government subsidies for higher education. For the purpose of collecting data, an anonymous survey was carried out in the last year of undergraduate degree student population using random sampling method. Decision trees were created of which two have been chosen that were most successful in predicting student success based on two criteria: Grade Point Average (GPA) and time that a student needs to finish the undergraduate program (time-to-degree). Decision trees have been shown as a good method of classification student success and they could be even more improved by increasing survey sample and developing specialized decision trees for each type of college. These types of methods have a big potential for use in decision support systems.
Abstract: In today-s information age, numbers of organizations
are still arguing on capitalizing the values of Information Technology
(IT) and Knowledge Management (KM) to which individuals can
benefit from and effective communication among the individuals can
be established. IT exists in enabling positive improvement for
communication among knowledge workers (k-workers) with a
number of social network technology domains at workplace. The
acceptance of digital discourse in sharing of knowledge and
facilitating the knowledge and information flows at most of the
organizations indeed impose the culture of knowledge sharing in
Digital Social Networks (DSN). Therefore, this study examines
whether the k-workers with IT background would confer an effect on
the three knowledge characteristics -- conceptual, contextual, and
operational. Derived from these three knowledge characteristics, five
potential factors will be examined on the effects of knowledge
exchange via e-mail domain as the chosen query. It is expected, that
the results could provide such a parameter in exploring how DSN
contributes in supporting the k-workers- virtues, performance and
qualities as well as revealing the mutual point between IT and KM.
Abstract: In this paper, a fuzzy algorithm and a fuzzy multicriteria
decision framework are developed and used for a practical
question of optimizing biofuels policy making. The methodological
framework shows how to incorporate fuzzy set theory in a decision
process of finding a sustainable biofuels policy among several policy
options. Fuzzy set theory is used here as a tool to deal with
uncertainties of decision environment, vagueness and ambiguities of
policy objectives, subjectivities of human assessments and imprecise
and incomplete information about the evaluated policy instruments.
Abstract: Over last two decades, due to hostilities of environment
over the internet the concerns about confidentiality of information
have increased at phenomenal rate. Therefore to safeguard the information
from attacks, number of data/information hiding methods have
evolved mostly in spatial and transformation domain.In spatial domain
data hiding techniques,the information is embedded directly on
the image plane itself. In transform domain data hiding techniques the
image is first changed from spatial domain to some other domain and
then the secret information is embedded so that the secret information
remains more secure from any attack. Information hiding algorithms
in time domain or spatial domain have high capacity and relatively
lower robustness. In contrast, the algorithms in transform domain,
such as DCT, DWT have certain robustness against some multimedia
processing.In this work the authors propose a novel steganographic
method for hiding information in the transform domain of the gray
scale image.The proposed approach works by converting the gray
level image in transform domain using discrete integer wavelet
technique through lifting scheme.This approach performs a 2-D
lifting wavelet decomposition through Haar lifted wavelet of the cover
image and computes the approximation coefficients matrix CA and
detail coefficients matrices CH, CV, and CD.Next step is to apply the
PMM technique in those coefficients to form the stego image. The
aim of this paper is to propose a high-capacity image steganography
technique that uses pixel mapping method in integer wavelet domain
with acceptable levels of imperceptibility and distortion in the cover
image and high level of overall security. This solution is independent
of the nature of the data to be hidden and produces a stego image
with minimum degradation.
Abstract: Recent advances in both the testing and verification of software based on formal specifications of the system to be built have reached a point where the ideas can be applied in a powerful way in the design of agent-based systems. The software engineering research has highlighted a number of important issues: the importance of the type of modeling technique used; the careful design of the model to enable powerful testing techniques to be used; the automated verification of the behavioural properties of the system; the need to provide a mechanism for translating the formal models into executable software in a simple and transparent way. This paper introduces the use of the X-machine formalism as a tool for modeling biology inspired agents proposing the use of the techniques built around X-machine models for the construction of effective, and reliable agent-based software systems.
Abstract: Roadways in Amman city face many problems consequent upon poor drainage systems. Evaluation tools are necessary to identify those roads needing improvement in their drainage system, and those needing regular maintenance. This work aims at evaluating drainage conditions in selected roadways in Amman city with the intent of identifying the problems encountered in their drainage systems. Three sites in the vicinity of Amman city have been selected and then inspected via several field visits to determine the state of their existing drainage systems and define the major problems encountered in these systems. The evaluation tool used in this study is based on visual inspection supported by photographs that depicted the defined problems. Following the field assessment, the drainage system in each road was rated as excellent, fair, good, or poor. The study reveals that more than 60% of the roadways in the selected sites were in poor drainage conditions, which lead to tremendous environmental problems. This assessment serves as a guide for local decision makers to help plan for the maintenance of Amman city roadways drainage systems, and propose ways of managing the associated problems.
Abstract: This study explores perceptions of English as a Foreign
Language (EFL) learners on using computer mediated communication
technology in their learner of English. The data consists of
observations of both synchronous and asynchronous communication
participants engaged in for over a period of 4 months, which included
online, and offline communication protocols, open-ended interviews
and reflection papers composed by participants.
Content analysis of interview data and the written documents listed
above, as well as, member check and triangulation techniques are the
major data analysis strategies. The findings suggest that participants
generally do not benefit from computer-mediated communication in
terms of its effect in learning a foreign language. Participants regarded
the nature of CMC as artificial, or pseudo communication that did not
aid their authentic communicational skills in English. The results of
this study sheds lights on insufficient and inconclusive findings, which
most quantitative CMC studies previously generated.
Abstract: This paper proposes new enhancement models to the
methods of nonlinear anisotropic diffusion to greatly reduce speckle
and preserve image features in medical ultrasound images. By
incorporating local physical characteristics of the image, in this case
scatterer density, in addition to the gradient, into existing tensorbased
image diffusion methods, we were able to greatly improve the
performance of the existing filtering methods, namely edge
enhancing (EE) and coherence enhancing (CE) diffusion. The new
enhancement methods were tested using various ultrasound images,
including phantom and some clinical images, to determine the
amount of speckle reduction, edge, and coherence enhancements.
Scatterer density weighted nonlinear anisotropic diffusion
(SDWNAD) for ultrasound images consistently outperformed its
traditional tensor-based counterparts that use gradient only to weight
the diffusivity function. SDWNAD is shown to greatly reduce
speckle noise while preserving image features as edges, orientation
coherence, and scatterer density. SDWNAD superior performances
over nonlinear coherent diffusion (NCD), speckle reducing
anisotropic diffusion (SRAD), adaptive weighted median filter
(AWMF), wavelet shrinkage (WS), and wavelet shrinkage with
contrast enhancement (WSCE), make these methods ideal
preprocessing steps for automatic segmentation in ultrasound
imaging.
Abstract: A new approach for protection of power transformer is
presented using a time-frequency transform known as Wavelet transform.
Different operating conditions such as inrush, Normal, load,
External fault and internal fault current are sampled and processed
to obtain wavelet coefficients. Different Operating conditions provide
variation in wavelet coefficients. Features like energy and Standard
deviation are calculated using Parsevals theorem. These features
are used as inputs to PNN (Probabilistic neural network) for fault
classification. The proposed algorithm provides more accurate results
even in the presence of noise inputs and accurately identifies inrush
and fault currents. Overall classification accuracy of the proposed
method is found to be 96.45%. Simulation of the fault (with and
without noise) was done using MATLAB AND SIMULINK software
taking 2 cycles of data window (40 m sec) containing 800 samples.
The algorithm was evaluated by using 10 % Gaussian white noise.
Abstract: To meet the demands of wireless sensor networks
(WSNs) where data are usually aggregated at a single source prior to
transmitting to any distant user, there is a need to establish a tree
structure inside any given event region. In this paper , a novel
technique to create one such tree is proposed .This tree preserves the
energy and maximizes the lifetime of event sources while they are
constantly transmitting for data aggregation. The term Decentralized
Lifetime Maximizing Tree (DLMT) is used to denote this tree.
DLMT features in nodes with higher energy tend to be chosen as data
aggregating parents so that the time to detect the first broken tree link
can be extended and less energy is involved in tree maintenance. By
constructing the tree in such a way, the protocol is able to reduce the
frequency of tree reconstruction, minimize the amount of data loss
,minimize the delay during data collection and preserves the energy.
Abstract: Telemedicine is brought to life by contemporary changes of our world and summarizes the entire range of services that are at the crossroad of traditional healthcare and information technology. It is believed that eHealth can help in solving critical issues of rising costs, care for ageing and housebound population, staff shortage. It is a feasible tool to provide routine as well as specialized health service as it has the potential to improve both the access to and the standard of care. eHealth is no more an optional choice. It has already made quite a way but it still remains a fantastic challenge for the future requiring cooperation and coordination at all possible levels. The strategic objectives of this paper are: 1. To start with an attempt to clarify the mass of terms used nowadays; 2. To answer the question “Who needs eHealth"; 3. To focus on the necessity of bridging telemedicine and medical (health) informatics as well as on the dual relationship between them; as well as 4. To underline the need of networking in understanding, developing and implementing eHealth.
Abstract: Automatic segmentation of skin lesions is the first step
towards the automated analysis of malignant melanoma. Although
numerous segmentation methods have been developed, few studies
have focused on determining the most effective color space for
melanoma application. This paper proposes an automatic segmentation
algorithm based on color space analysis and clustering-based histogram
thresholding, a process which is able to determine the optimal
color channel for detecting the borders in dermoscopy images. The
algorithm is tested on a set of 30 high resolution dermoscopy images.
A comprehensive evaluation of the results is provided, where borders
manually drawn by four dermatologists, are compared to automated
borders detected by the proposed algorithm, applying three previously
used metrics of accuracy, sensitivity, and specificity and a new metric
of similarity. By performing ROC analysis and ranking the metrics,
it is demonstrated that the best results are obtained with the X and
XoYoR color channels, resulting in an accuracy of approximately
97%. The proposed method is also compared with two state-of-theart
skin lesion segmentation methods.
Abstract: Under the limitation of investment budget, a utility
company is required to maximize the utilization of their existing
assets during their life cycle satisfying both engineering and financial
requirements. However, utility does not have knowledge about the
status of each asset in the portfolio neither in terms of technical nor
financial values. This paper presents a knowledge based model for
the utility companies in order to make an optimal decision on power
transformer with their utilization. CommonKADS methodology, a
structured development for knowledge and expertise representation,
is utilized for designing and developing knowledge based model. A
case study of One MVA power transformer of Nepal Electricity
Authority is presented. The results show that the reusable knowledge
can be categorized, modeled and utilized within the utility company
using the proposed methodologies. Moreover, the results depict that
utility company can achieve both engineering and financial benefits
from its utilization.