Abstract: The next stage of the home networking environment is
supposed to be ubiquitous, where each piece of material is equipped
with an RFID (Radio Frequency Identification) tag. To fully support
the ubiquitous environment, home networking middleware should be
able to recommend home services based on a user-s interests and
efficiently manage information on service usage profiles for the users.
Therefore, USN (Ubiquitous Sensor Network) technology, which
recognizes and manages a appliance-s state-information (location,
capabilities, and so on) by connecting RFID tags is considered. The
Intelligent Multi-Agent Middleware (IMAM) architecture was
proposed to intelligently manage the mobile RFID-based home
networking and to automatically supply information about home
services that match a user-s interests. Evaluation results for
personalization services for IMAM using Bayesian-Net and Decision
Trees are presented.
Abstract: Problem solving has traditionally been one of the principal research areas for artificial intelligence. Yet, although artificial intelligence reasoning techniques have been employed in several product support systems, the benefit of integrating product support, knowledge engineering, and problem solving, is still unclear. This paper studies the synergy of these areas and proposes a knowledge engineering framework that integrates product support systems and artificial intelligence techniques. The framework includes four spaces; the data, problem, hypothesis, and solution ones. The data space incorporates the knowledge needed for structured reasoning to take place, the problem space contains representations of problems, and the hypothesis space utilizes a multimodal reasoning approach to produce appropriate solutions in the form of virtual documents. The solution space is used as the gateway between the system and the user. The proposed framework enables the development of product support systems in terms of smaller, more manageable steps while the combination of different reasoning techniques provides a way to overcome the lack of documentation resources.
Abstract: Business Process Modeling (BPM) is the first and
most important step in business process management lifecycle. Graph
based formalism and rule based formalism are the two most
predominant formalisms on which process modeling languages are
developed. BPM technology continues to face challenges in coping
with dynamic business environments where requirements and goals
are constantly changing at the execution time. Graph based
formalisms incur problems to react to dynamic changes in Business
Process (BP) at the runtime instances. In this research, an adaptive
and flexible framework based on the integration between Object
Oriented diagramming technique and Petri Net modeling language is
proposed in order to support change management techniques for
BPM and increase the representation capability for Object Oriented
modeling for the dynamic changes in the runtime instances. The
proposed framework is applied in a higher education environment to
achieve flexible, updatable and dynamic BP.
Abstract: Wavelet neural networks (WNNs) have emerged as a vital alternative to the vastly studied multilayer perceptrons (MLPs) since its first implementation. In this paper, we applied various clustering algorithms, namely, K-means (KM), Fuzzy C-means (FCM), symmetry-based K-means (SBKM), symmetry-based Fuzzy C-means (SBFCM) and modified point symmetry-based K-means (MPKM) clustering algorithms in choosing the translation parameter of a WNN. These modified WNNs are further applied to the heterogeneous cancer classification using benchmark microarray data and were compared against the conventional WNN with random initialization method. Experimental results showed that a WNN classifier with the MPKM algorithm is more precise than the conventional WNN as well as the WNNs with other clustering algorithms.
Abstract: In the present work, we introduce the particle swarm optimization called (PSO in short) to avoid the Runge-s phenomenon occurring in many numerical problems. This new approach is tested with some numerical examples including the generalized integral quadrature method in order to solve the Volterra-s integral equations
Abstract: Peer review is an activity where students review their
classmates- writing and then evaluate the content, development, unity
and organization. Studies have shown that peer review activities
benefit both the reviewer and the writer in developing their reading
and writing skills. Furthermore, peer review activities may also
enhance students- soft skills. This study was conducted to find out the
benefits of peer review activity in a technical writing class based on
engineering students- perceptions. The study also highlights how
these benefits could improve the students- soft skills. A set of
questionnaire was given to 200 undergraduate students of a technical
writing course. The results of the study indicate that the activity could
help improve their critical thinking skills, written and oral
communication skills, as well as team work. This paper further
discusses how the implications of these benefits could help enhance
students- soft skills.
Abstract: Smart Grids employ wireless sensor networks for
their control and monitoring. Sensors are characterized by limitations
in the processing power, energy supply and memory spaces, which
require a particular attention on the design of routing and data
management algorithms.
Since most routing algorithms for sensor networks, focus on
finding energy efficient paths to prolong the lifetime of sensor
networks, the power of sensors on efficient paths depletes quickly,
and consequently sensor networks become incapable of monitoring
events from some parts of their target areas. In consequence, the
design of routing protocols should consider not only energy
efficiency paths, but also energy efficient algorithms in general.
In this paper we propose an energy efficient routing protocol for
wireless sensor networks without the support of any location
information system. The reliability and the efficiency of this protocol
have been demonstrated by simulation studies where we compare
them to the legacy protocols. Our simulation results show that these
algorithms scale well with network size and density.
Abstract: Understanding the cell's large-scale organization is an interesting task in computational biology. Thus, protein-protein interactions can reveal important organization and function of the cell. Here, we investigated the correspondence between protein interactions and function for the yeast. We obtained the correlations among the set of proteins. Then these correlations are clustered using both the hierarchical and biclustering methods. The detailed analyses of proteins in each cluster were carried out by making use of their functional annotations. As a result, we found that some functional classes appear together in almost all biclusters. On the other hand, in hierarchical clustering, the dominancy of one functional class is observed. In the light of the clustering data, we have verified some interactions which were not identified as core interactions in DIP and also, we have characterized some functionally unknown proteins according to the interaction data and functional correlation. In brief, from interaction data to function, some correlated results are noticed about the relationship between interaction and function which might give clues about the organization of the proteins, also to predict new interactions and to characterize functions of unknown proteins.
Abstract: Here are many methods for designing and
implementation of virtual laboratories, because of their special
features. The most famous architectural designs are based on
the events. This model of architecting is so efficient for virtual
laboratories implemented on a local network. Later, serviceoriented
architecture, gave the remote access ability to them
and Peer-To-Peer architecture, hired to exchanging data with
higher quality and more speed. Other methods, such as Agent-
Based architecting, are trying to solve the problems of
distributed processing in a complicated laboratory system.
This study, at first, reviews the general principles of
designing a virtual laboratory, and then compares the different
methods based on EDA, SOA and Agent-Based architecting
to present weaknesses and strengths of each method. At the
end, we make the best choice for design, based on existing
conditions and requirements.
Abstract: Knowledge of an organization does not merely reside
in structured form of information and data; it is also embedded in
unstructured form. The discovery of such knowledge is particularly
difficult as the characteristic is dynamic, scattered, massive and
multiplying at high speed. Conventional methods of managing
unstructured information are considered too resource demanding and
time consuming to cope with the rapid information growth.
In this paper, a Multi-faceted and Automatic Knowledge
Elicitation System (MAKES) is introduced for the purpose of
discovery and capture of organizational knowledge. A trial
implementation has been conducted in a public organization to
achieve the objective of decision capture and navigation from a
number of meeting minutes which are autonomously organized,
classified and presented in a multi-faceted taxonomy map in both
document and content level. Key concepts such as critical decision
made, key knowledge workers, knowledge flow and the relationship
among them are elicited and displayed in predefined knowledge
model and maps. Hence, the structured knowledge can be retained,
shared and reused.
Conducting Knowledge Management with MAKES reduces work
in searching and retrieving the target decision, saves a great deal of
time and manpower, and also enables an organization to keep pace
with the knowledge life cycle. This is particularly important when
the amount of unstructured information and data grows extremely
quickly. This system approach of knowledge management can
accelerate value extraction and creation cycles of organizations.
Abstract: Symbolic Circuit Analysis (SCA) is a technique used
to generate the symbolic expression of a network. It has become a
well-established technique in circuit analysis and design. The
symbolic expression of networks offers excellent way to perform
frequency response analysis, sensitivity computation, stability
measurements, performance optimization, and fault diagnosis. Many
approaches have been proposed in the area of SCA offering different
features and capabilities. Numerical Interpolation methods are very
common in this context, especially by using the Fast Fourier
Transform (FFT). The aim of this paper is to present a method for
SCA that depends on the use of Wavelet Transform (WT) as a
mathematical tool to generate the symbolic expression for large
circuits with minimizing the analysis time by reducing the number of
computations.
Abstract: Radio wave propagation on the road surface is a major
problem on wireless sensor network for traffic monitoring. In this
paper, we compare receiving signal strength on two scenarios 1) an
empty road and 2) a road with a vehicle. We investigate the effect of
antenna polarization and antenna height to the receiving signal
strength. The transmitting antenna is installed on the road surface.
The receiving signal is measured 360 degrees around the transmitting
antenna with the radius of 2.5 meters. Measurement results show the
receiving signal fluctuation around the transmitting antenna in both
scenarios. Receiving signal with vertical polarization antenna results
in higher signal strength than horizontal polarization antenna. The
optimum antenna elevation is 1 meter for both horizon and vertical
polarizations with the vehicle on the road. In the empty road, the
receiving signal level is unvarying with the elevation when the
elevation is greater than 1.5 meters.
Abstract: Nowadays, Multimedia Communication has been developed and improved rapidly in order to enable users to communicate between each other over the Internet. In general, the multimedia communication consists of audio and video communication. However, this paper focuses on audio streams. The audio translation between protocols is a very critical issue due to solving the communication problems between any two protocols, as well as it enables people around the world to talk with each other at anywhere and anytime even they use different protocols. In this paper, a proposed method for an audio translation module between two protocols has been presented. These two protocols are InterAsterisk eXchange Protocol (IAX) and Real Time Switching Control Protocol (RSW), which they are widely used to provide two ways audio transfer feature. The result of this work is to introduce possibility of interworking together.
Abstract: As computer network technology becomes
increasingly complex, it becomes necessary to place greater
requirements on the validity of developing standards and the
resulting technology. Communication networks are based on large
amounts of protocols. The validity of these protocols have to be
proved either individually or in an integral fashion. One strategy for
achieving this is to apply the growing field of formal methods.
Formal methods research defines systems in high order logic so that
automated reasoning can be applied for verification. In this research
we represent and implement a formerly announced multicast protocol
in Prolog language so that certain properties of the protocol can be
verified. It is shown that by using this approach some minor faults in
the protocol were found and repaired. Describing the protocol as
facts and rules also have other benefits i.e. leads to a process-able
knowledge. This knowledge can be transferred as ontology between
systems in KQML format. Since the Prolog language can increase its
knowledge base every time, this method can also be used to learn an
intelligent network.
Abstract: In this work, we present an automatic vehicle detection
system for airborne videos using combined features. We propose a
pixel-wise classification method for vehicle detection using Dynamic
Bayesian Networks. In spite of performing pixel-wise classification,
relations among neighboring pixels in a region are preserved in the
feature extraction process. The main novelty of the detection scheme is
that the extracted combined features comprise not only pixel-level
information but also region-level information. Afterwards, tracking is
performed on the detected vehicles. Tracking is performed using
efficient Kalman filter with dynamic particle sampling. Experiments
were conducted on a wide variety of airborne videos. We do not
assume prior information of camera heights, orientation, and target
object sizes in the proposed framework. The results demonstrate
flexibility and good generalization abilities of the proposed method on
a challenging dataset.
Abstract: Water quality is a subject of ongoing concern.
Deterioration of water quality has initiated serious management
efforts in many countries. This study endeavors to automatically
classify water quality. The water quality classes are evaluated using 6
factor indices. These factors are pH value (pH), Dissolved Oxygen
(DO), Biochemical Oxygen Demand (BOD), Nitrate Nitrogen
(NO3N), Ammonia Nitrogen (NH3N) and Total Coliform (TColiform).
The methodology involves applying data mining
techniques using multilayer perceptron (MLP) neural network
models. The data consisted of 11 sites of canals in Dusit district in
Bangkok, Thailand. The data is obtained from the Department of
Drainage and Sewerage Bangkok Metropolitan Administration
during 2007-2011. The results of multilayer perceptron neural
network exhibit a high accuracy multilayer perception rate at 96.52%
in classifying the water quality of Dusit district canal in Bangkok
Subsequently, this encouraging result could be applied with plan and
management source of water quality.
Abstract: Campus sustainability is the goal of a university striving for sustainable development. This study found that of 17 popular approaches, two comprehensive campus sustainability assessment frameworks were developed in the context of Sustainability in Higher Education (SHE), and used by many university campuses around the world. Sustainability Tracking Assessment and Rating Systems (STARS) and the Campus Sustainability Assessment Framework (CSAF) approaches are more comprehensive than others. Therefore, the researchers examined aspects and elements used by CSAF and STARS in the approach to develop a campus sustainability assessment framework for Universiti Kebangsaan Malaysia (UKM). Documents analysis found that CSAF and STARS do not focus on physical development, especially the construction industry, as key elements of campus sustainability assessment. This finding is in accordance with the Sustainable UKM Programme which consists of three main components of sustainable community, ecosystem and physical development.
Abstract: Present wireless communication demands compact and intelligent devices with multitasking capabilities at affordable cost. The focus in the presented paper is on a dual band antenna for wireless communication with the capability of operating at two frequency bands with same structure. Two resonance frequencies are observed with the second operation band at 4.2GHz approximately three times the first resonance frequency at 1.5GHz. Structure is simple loop of microstrip line with characteristic impedance 50 ohms. The proposed antenna is designed using defective ground structure (DGS) and shows the nearly one third reductions in size as compared to without DGS. This antenna was simulated on electromagnetic (EM) simulation software and fabricated using microwave integrated circuit technique on RT-Duroid dielectric substrate (εr= 2.22) of thickness (H=15 mils). The designed antenna was tested on automatic network analyzer and shows the good agreement with simulated results. The proposed structure is modeled into an equivalent electrical circuit and simulated on circuit simulator. Subsequently, theoretical analysis was carried out and simulated. The simulated, measured, equivalent circuit response, and theoretical results shows good resemblance. The bands of operation draw many potential applications in today’s wireless communication.
Abstract: A gene network gives the knowledge of the regulatory
relationships among the genes. Each gene has its activators and
inhibitors that regulate its expression positively and negatively
respectively. Genes themselves are believed to act as activators and
inhibitors of other genes. They can even activate one set of genes and
inhibit another set. Identifying gene networks is one of the most
crucial and challenging problems in Bioinformatics. Most work done
so far either assumes that there is no time delay in gene regulation or
there is a constant time delay. We here propose a Dynamic Time-
Lagged Correlation Based Method (DTCBM) to learn the gene
networks, which uses time-lagged correlation to find the potential
gene interactions, and then uses a post-processing stage to remove
false gene interactions to common parents, and finally uses dynamic
correlation thresholds for each gene to construct the gene network.
DTCBM finds correlation between gene expression signals shifted in
time, and therefore takes into consideration the multi time delay
relationships among the genes. The implementation of our method is
done in MATLAB and experimental results on Saccharomyces
cerevisiae gene expression data and comparison with other methods
indicate that it has a better performance.
Abstract: In this research work, poly (acrylonitrile-butadienestyrene)/
polypropylene (ABS/PP) blends were processed by melt
compounding in a twin-screw extruder. Upgrading of the thermal
characteristics of the obtained materials was attempted by the
incorporation of organically modified montmorillonite (OMMT), as
well as, by the addition of two types of compatibilizers;
polypropylene grafted with maleic anhydride (PP-g-MAH) and ABS
grafted with maleic anhydride (ABS-g-MAH). The effect of the
above treatments was investigated separately and in combination.
Increasing the PP content in ABS matrix seems to increase the
thermal stability of their blend and the glass transition temperature
(Tg) of SAN phase of ABS. From the other part, the addition of ABS
to PP promotes the formation of its β-phase, which is maximum at 30
wt% ABS concentration, and increases the crystallization temperature
(Tc) of PP. In addition, it increases the crystallization rate of PP.The
β-phase of PP in ABS/PP blends is reduced by the addition of
compatibilizers or/and organoclay reinforcement. The incorporation
of compatibilizers increases the thermal stability of PP and reduces
its melting (ΔΗm) and crystallization (ΔΗc) enthalpies. Furthermore it
decreases slightly the Tgs of PP and SAN phases of ABS/PP blends.
Regarding the storage modulus of the ABS/PP blends, it presents a
change in their behavior at about 10°C and return to their initial
behavior at ~110°C. The incorporation of OMMT to no compatibilized
and compatibilized ABS/PP blends enhances their storage modulus.