Abstract: In the last years numerous applications of Human-
Computer Interaction have exploited the capabilities of Time-of-
Flight cameras for achieving more and more comfortable and precise
interactions. In particular, gesture recognition is one of the most active
fields. This work presents a new method for interacting with a virtual
object in a 3D space. Our approach is based on the fusion of depth
data, supplied by a ToF camera, with color information, supplied
by a HD webcam. The hand detection procedure does not require
any learning phase and is able to concurrently manage gestures of
two hands. The system is robust to the presence in the scene of
other objects or people, thanks to the use of the Kalman filter for
maintaining the tracking of the hands.
Abstract: Electricity market activities and a growing demand for electricity have led to heavily stressed power systems. This requires operation of the networks closer to their stability limits. Power system operation is affected by stability related problems, leading to unpredictable system behavior. Voltage stability refers to the ability of a power system to sustain appropriate voltage levels through large and small disturbances. Steady-state voltage stability is concerned with limits on the existence of steady-state operating points for the network. FACTS devices can be utilized to increase the transmission capacity, the stability margin and dynamic behavior or serve to ensure improved power quality. Their main capabilities are reactive power compensation, voltage control and power flow control. Among the FACTS controllers, Static Var Compensator (SVC) provides fast acting dynamic reactive compensation for voltage support during contingency events. In this paper, voltage stability assessment with appropriate representations of tap-changer transformers and SVC is investigated. Integrating both of these devices is the main topic of this paper. Effect of the presence of tap-changing transformers on static VAR compensator controller parameters and ratings necessary to stabilize load voltages at certain values are highlighted. The interrelation between transformer off nominal tap ratios and the SVC controller gains and droop slopes and the SVC rating are found. P-V curves are constructed to calculate loadability margins.
Abstract: In today-s competitive global business environment,
the concept of supply chain management (SCM) continues to become
increasingly market-oriented, shifting the primary driver of the value
chain from supply to demand. Recent recommendations encourage
researchers to focus investigations on the supply chain process
integration (SCPI) capabilities that integrate a focal firm with its
network of suppliers and business customers to create value for it.
However, theoretical and empirical researches pertaining to the
antecedents and consequences of a focal firm-s SCPI capabilities have
been limited and piecemeal. The purpose of this study is to investigate
the critical determinants and consequences of a focal firm-s SCPI
capabilities. We test our proposed research framework using a sample
of 139 sales managers of manufacturing industries in Taiwan, our
research findings show that (1) both perceived business customer-s
power and focal firm-s market-oriented culture positively influences a
focal firm-s SCPI capabilities, and (2) SCPI capabilities positively
influence a focal firm-s SCM performance, both operational and
strategic benefits. Implications for practitioners and researchers and
suggestions for future research are also addressed in this study.
Abstract: In order to meet the limits imposed on automotive
emissions, engine control systems are required to constrain air/fuel
ratio (AFR) in a narrow band around the stoichiometric value, due to
the strong decay of catalyst efficiency in case of rich or lean mixture.
This paper presents a model of a sample spark ignition engine and
demonstrates Simulink-s capabilities to model an internal combustion
engine from the throttle to the crankshaft output. We used welldefined
physical principles supplemented, where appropriate, with
empirical relationships that describe the system-s dynamic behavior
without introducing unnecessary complexity. We also presents a PID
tuning method that uses an adaptive fuzzy system to model the
relationship between the controller gains and the target output
response, with the response specification set by desired percent
overshoot and settling time. The adaptive fuzzy based input-output
model is then used to tune on-line the PID gains for different
response specifications. Experimental results demonstrate that better
performance can be achieved with adaptive fuzzy tuning relative to
similar alternative control strategies. The actual response
specifications with adaptive fuzzy matched the desired response
specifications.
Abstract: Wikis are promoted as collaborative writing tools that
allow students to transform a text into a collective document by
information sharing and group reflection. However, despite the
promising collaborative capabilities of wikis, their pedagogical value
regarding collaborative writing is still questionable. Wiki alone
cannot make collaborative writing happen, and students do not
automatically become more active, participate, and collaborate with
others when they use wikis. To foster collaborative writing and active
involvement in wiki development there is a need for a systematic
approach to wikis. Themain goal of this paper is to propose and
evaluate a co-writing approach to the development of wikis, along
with the study of three wiki applications to report on pedagogical
implications of collaborative writing in higher education.
Abstract: IEEE has designed 802.11i protocol to address the
security issues in wireless local area networks. Formal analysis is
important to ensure that the protocols work properly without having
to resort to tedious testing and debugging which can only show the
presence of errors, never their absence. In this paper, we present
the formal verification of an abstract protocol model of 802.11i.
We translate the 802.11i protocol into the Strand Space Model and
then prove the authentication property of the resulting model using
the Strand Space formalism. The intruder in our model is imbued
with powerful capabilities and repercussions to possible attacks are
evaluated. Our analysis proves that the authentication of 802.11i is
not compromised in the presented model. We further demonstrate
how changes in our model will yield a successful man-in-the-middle
attack.
Abstract: Lately, an interest has grown greatly in the usages of
RFID in an un-presidential applications. It is shown in the adaptation
of major software companies such as Microsoft, IBM, and Oracle
the RFID capabilities in their major software products. For example
Microsoft SharePoints 2010 workflow is now fully compatible with
RFID platform. In addition, Microsoft BizTalk server is also capable
of all RFID sensors data acquisition. This will lead to applications
that required high bit rate, long range and a multimedia content in
nature. Higher frequencies of operation have been designated for
RFID tags, among them are the 2.45 and 5.8 GHz. The higher the
frequency means higher range, and higher bit rate, but the drawback
is the greater cost. In this paper we present a single layer, low
profile patch antenna operates at 5.8 GHz with pure resistive input
impedance of 50 and close to directive radiation. Also, we propose
a modification to the design in order to improve the operation band
width from 8.7 to 13.8
Abstract: In this paper we propose an intelligent agent approach
to control the electric power grid at a smaller granularity in order to
give it self-healing capabilities. We develop a method using the
influence model to transform transmission substations into
information processing, analyzing and decision making (intelligent
behavior) units. We also develop a wireless communication method
to deliver real-time uncorrupted information to an intelligent
controller in a power system environment. A combined networking
and information theoretic approach is adopted in meeting both the
delay and error probability requirements. We use a mobile agent
approach in optimizing the achievable information rate vector and in
the distribution of rates to users (sensors). We developed the concept
and the quantitative tools require in the creation of cooperating semiautonomous
subsystems which puts the electric grid on the path
towards intelligent and self-healing system.
Abstract: In this work a dynamic model of a new quadrotor aerial
vehicle that is equipped with a tilt-wing mechanism is presented.
The vehicle has the capabilities of vertical take-off/landing (VTOL)
like a helicopter and flying horizontal like an airplane. Dynamic
model of the vehicle is derived both for vertical and horizontal flight
modes using Newton-Euler formulation. An LQR controller for the
vertical flight mode has also been developed and its performance
has been tested with several simulations.
Abstract: Recognizing the increasing importance of using the
Internet to conduct business, this paper looks at some related matters
associated with small businesses making a decision of whether or not
to have a Website and go online. Small businesses in Saudi Arabia
struggle to have this decision. For organizations, to fully go online,
conduct business and provide online information services, they need
to connect their database to the Web. Some issues related to doing
that might be beyond the capabilities of most small businesses in
Saudi Arabia, such as Website management, technical issues and
security concerns. Here we focus on a small business firm in Saudi
Arabia (Case Study), discussing the issues related to going online
decision and the firm's options of what to do and how to do it. The
paper suggested some valuable solutions of connecting databases to
the Web. It also discusses some of the important issues related to
online information services and e-commerce, mainly Web hosting
options and security issues.
Abstract: A computational platform is presented in this
contribution. It has been designed as a virtual laboratory to be used
for exploring optimization algorithms in biological problems. This
platform is built on a blackboard-based agent architecture. As a test
case, the version of the platform presented here is devoted to the
study of protein folding, initially with a bead-like description of the
chain and with the widely used model of hydrophobic and polar
residues (HP model). Some details of the platform design are
presented along with its capabilities and also are revised some
explorations of the protein folding problems with different types of
discrete space. It is also shown the capability of the platform to
incorporate specific tools for the structural analysis of the runs in
order to understand and improve the optimization process.
Accordingly, the results obtained demonstrate that the ensemble of
computational tools into a single platform is worthwhile by itself,
since experiments developed on it can be designed to fulfill different
levels of information in a self-consistent fashion. By now, it is being
explored how an experiment design can be useful to create a
computational agent to be included within the platform. These
inclusions of designed agents –or software pieces– are useful for the
better accomplishment of the tasks to be developed by the platform.
Clearly, while the number of agents increases the new version of the
virtual laboratory thus enhances in robustness and functionality.
Abstract: Exploring an autistic child in Elementary school is a
difficult task that must be fully thought out and the teachers should
be aware of the many challenges they face raising their child
especially the behavioral problems of autistic children. Hence there
arises a need for developing Artificial intelligence (AI)
Contemporary Techniques to help diagnosis to discover autistic
people.
In this research, we suggest designing architecture of expert
system that combine Cognitive Maps (CM) with Case Based
Reasoning technique (CBR) in order to reduce time and costs of
traditional diagnosis process for the early detection to discover
autistic children. The teacher is supposed to enter child's information
for analyzing by CM module. Then, the reasoning processor would
translate the output into a case to be solved a current problem by
CBR module. We will implement a prototype for the model as a
proof of concept using java and MYSQL.
This will be provided a new hybrid approach that will achieve new
synergies and improve problem solving capabilities in AI. And we
will predict that will reduce time, costs, the number of human errors
and make expertise available to more people who want who want to
serve autistic children and their families.
Abstract: The purpose of this study is two-fold. First, it attempts to explore potential opportunities for utilizing visual interactive simulations along with Business Intelligence (BI) as a decision support tool for strategic decision making. Second, it tries to figure out the essential top-level managerial requirements that would transform strategic decision simulation into an integral component of BI systems. The domain of particular interest was the application of visual interactive simulation capabilities in the field of supply chains. A qualitative exploratory method was applied, through the use of interviews with two leading companies. The collected data was then analysed to demonstrate the difference between the literature perspective and the practical managerial perspective on the issue. The results of the study suggest that although the use of simulation particularly in managing supply chains is very evident in literature, yet, in practice such utilization is still in its infancy, particularly regarding strategic decisions. Based on the insights a prototype of a simulation based BI-solution-extension was developed and evaluated.
Abstract: In this paper, we propose a supervised method for
color image classification based on a multilevel sigmoidal neural
network (MSNN) model. In this method, images are classified into
five categories, i.e., “Car", “Building", “Mountain", “Farm" and
“Coast". This classification is performed without any segmentation
processes. To verify the learning capabilities of the proposed method,
we compare our MSNN model with the traditional Sigmoidal Neural
Network (SNN) model. Results of comparison have shown that the
MSNN model performs better than the traditional SNN model in the
context of training run time and classification rate. Both color
moments and multi-level wavelets decomposition technique are used
to extract features from images. The proposed method has been
tested on a variety of real and synthetic images.
Abstract: Recent scientific investigations indicate that
multimodal biometrics overcome the technical limitations of
unimodal biometrics, making them ideally suited for everyday life
applications that require a reliable authentication system. However,
for a successful adoption of multimodal biometrics, such systems
would require large heterogeneous datasets with complex multimodal
fusion and privacy schemes spanning various distributed
environments. From experimental investigations of current
multimodal systems, this paper reports the various issues related to
speed, error-recovery and privacy that impede the diffusion of such
systems in real-life. This calls for a robust mechanism that caters to
the desired real-time performance, robust fusion schemes,
interoperability and adaptable privacy policies.
The main objective of this paper is to present a framework that
addresses the abovementioned issues by leveraging on the
heterogeneous resource sharing capacities of Grid services and the
efficient machine learning capabilities of artificial neural networks
(ANN). Hence, this paper proposes a Grid-based neural network
framework for adopting multimodal biometrics with the view of
overcoming the barriers of performance, privacy and risk issues that
are associated with shared heterogeneous multimodal data centres.
The framework combines the concept of Grid services for reliable
brokering and privacy policy management of shared biometric
resources along with a momentum back propagation ANN (MBPANN)
model of machine learning for efficient multimodal fusion and
authentication schemes. Real-life applications would be able to adopt
the proposed framework to cater to the varying business requirements
and user privacies for a successful diffusion of multimodal
biometrics in various day-to-day transactions.
Abstract: This research intends to introduce a new usage of Artificial Intelligent (AI) approaches in Stepping Stone Detection (SSD) fields of research. By using Self-Organizing Map (SOM) approaches as the engine, through the experiment, it is shown that SOM has the capability to detect the number of connection chains that involved in a stepping stones. Realizing that by counting the number of connection chain is one of the important steps of stepping stone detection and it become the research focus currently, this research has chosen SOM as the AI techniques because of its capabilities. Through the experiment, it is shown that SOM can detect the number of involved connection chains in Network-based Stepping Stone Detection (NSSD).
Abstract: An information procuring and processing emerging technology wireless sensor network (WSN) Consists of autonomous nodes with versatile devices underpinned by applications. Nodes are equipped with different capabilities such as sensing, computing, actuation and wireless communications etc. based on application requirements. A WSN application ranges from military implementation in the battlefield, environmental monitoring, health sector as well as emergency response of surveillance. The nodes are deployed independently to cooperatively monitor the physical and environmental conditions. The architecture of WSN differs based on the application requirements and focus on low cost, flexibility, fault tolerance capability, deployment process as well as conserve energy. In this paper we have present the characteristics, architecture design objective and architecture of WSN
Abstract: Nowadays social media are important tools for web
resource discovery. The performance and capabilities of web searches
are vital, especially search results from social research paper
bookmarking. This paper proposes a new algorithm for ranking
method that is a combination of similarity ranking with paper posted
time or CSTRank. The paper posted time is static ranking for
improving search results. For this particular study, the paper posted
time is combined with similarity ranking to produce a better ranking
than other methods such as similarity ranking or SimRank. The
retrieval performance of combination rankings is evaluated using
mean values of NDCG. The evaluation in the experiments implies
that the chosen CSTRank ranking by using weight score at ratio 90:10
can improve the efficiency of research paper searching on social
bookmarking websites.
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: In power systems, protective relays must filter their
inputs to remove undesirable quantities and retain signal quantities of
interest. This job must be performed accurate and fast. A new
method for filtering the undesirable components such as DC and
harmonic components associated with the fundamental system
signals. The method is s based on a dynamic filtering algorithm. The
filtering algorithm has many advantages over some other classical
methods. It can be used as dynamic on-line filter without the need of
parameters readjusting as in the case of classic filters. The proposed
filter is tested using different signals. Effects of number of samples
and sampling window size are discussed. Results obtained are
presented and discussed to show the algorithm capabilities.