Abstract: In this paper, we first give the representation of the general solution of the following least-squares problem (LSP): Given matrices X ∈ Rn×p, B ∈ Rp×p and A0 ∈ Rr×r, find a matrix A ∈ Rn×n such that XT AX − B = min, s. t. A([1, r]) = A0, where A([1, r]) is the r×r leading principal submatrix of the matrix A. We then consider a best approximation problem: given an n × n matrix A˜ with A˜([1, r]) = A0, find Aˆ ∈ SE such that A˜ − Aˆ = minA∈SE A˜ − A, where SE is the solution set of LSP. We show that the best approximation solution Aˆ is unique and derive an explicit formula for it. Keyw
Abstract: The aged are faced with increasing risk for falls. The
aged have the easily fragile bones than others. When falls have
occurred, it is important to detect this emergency state because such
events often lead to more serious illness or even death. A
implementation of PDA system, for detection of emergency situation,
was developed using 3-axis accelerometer in this paper as follows.
The signals were acquired from the 3-axis accelerometer, and then
transmitted to the PDA through Bluetooth module. This system can
classify the human activity, and also detect the emergency state like
falls. When the fall occurs, the system generates the alarm on the
PDA. If a subject does not respond to the alarm, the system determines
whether the current situation is an emergency state or not, and then
sends some information to the emergency center in the case of urgent
situation. Three different studies were conducted on 12 experimental
subjects, with results indicating a good accuracy. The first study was
performed to detect the posture change of human daily activity. The
second study was performed to detect the correct direction of fall. The
third study was conducted to check the classification of the daily
physical activity. Each test was lasted at least 1 min. in third study.
The output of acceleration signal was compared and evaluated by
changing a various posture after attaching a 3-axis accelerometer
module on the chest. The newly developed system has some important
features such as portability, convenience and low cost. One of the
main advantages of this system is that it is available at home
healthcare environment. Another important feature lies in low cost to
manufacture device. The implemented system can detect the fall
accurately, so will be widely used in emergency situation.
Abstract: The uses of road map in daily activities are numerous
but it is a hassle to construct and update a road map whenever there
are changes. In Universiti Malaysia Sarawak, research on Automatic
Road Extraction (ARE) was explored to solve the difficulties in
updating road map. The research started with using Satellite Image
(SI), or in short, the ARE-SI project. A Hybrid Simple Colour Space
Segmentation & Edge Detection (Hybrid SCSS-EDGE) algorithm
was developed to extract roads automatically from satellite-taken
images. In order to extract the road network accurately, the satellite
image must be analyzed prior to the extraction process. The
characteristics of these elements are analyzed and consequently the
relationships among them are determined. In this study, the road
regions are extracted based on colour space elements and edge details
of roads. Besides, edge detection method is applied to further filter
out the non-road regions. The extracted road regions are validated by
using a segmentation method. These results are valuable for building
road map and detecting the changes of the existing road database.
The proposed Hybrid Simple Colour Space Segmentation and Edge
Detection (Hybrid SCSS-EDGE) algorithm can perform the tasks
fully automatic, where the user only needs to input a high-resolution
satellite image and wait for the result. Moreover, this system can
work on complex road network and generate the extraction result in
seconds.
Abstract: Recent developments in storage technology and
networking architectures have made it possible for broad areas of applications to rely on data streams for quick response and accurate
decision making. Data streams are generated from events of real world so existence of associations, which are among the occurrence of these events in real world, among concepts of data streams is
logical. Extraction of these hidden associations can be useful for prediction of subsequent concepts in concept shifting data streams. In this paper we present a new method for learning association among
concepts of data stream and prediction of what the next concept will be. Knowing the next concept, an informed update of data model will be possible. The results of conducted experiments show that the proposed method is proper for classification of concept shifting data
streams.
Abstract: The purpose of this paper is to introduce an interactive online case-study library website developed in a national project. The design goal of the website is to provide interactive, enhanced, case-based and online educational resource for educators through the purpose and within the scope of a national project. The ADDIE instructional design model was used in the development of the website for interactive case-based library. This library is developed on a web-based platform, which is important in terms of manageability, accessibility, and updateability of data. Users are able to sort the displayed case-studies by their titles, dates, ratings, view counts, etc. The usability test is used and the expert opinion is taken for the evaluation of the website. This website is a tool to integrate technology into education. It is believed that this website will be beneficial for pre-service and in-service teachers in terms of their professional developments.
Abstract: It is not a secret that, IT management has become
more and more and integrated part of almost all organizations. IT
managers posses an enormous amount of knowledge within both
organizational knowledge and general IT knowledge. This article
investigates how IT managers keep themselves updated on IT
knowledge in general and looks into how much time IT managers
spend on weekly basis searching the net for new or problem solving
IT knowledge. The theory used in this paper is used to investigate the
current role of IT managers and what issues they are facing.
Furthermore a research is conducted where 7 IT managers in medium
sized and large Danish companies are interviewed to add further
focus on the role of the IT manager and to focus on how they keep
themselves updated. Beside finding substantial need for more
research, IT managers – generalists or specialists – only have limited
knowledge resources at hand in updating their own knowledge –
leaving much initiative to vendors.
Abstract: This paper presents a new stable robust adaptive controller and observer design for a class of nonlinear systems that contain i. Coupling of unmeasured states and unknown parameters ii. Unknown dead zone at the system actuator. The system is firstly cast into a modified form in which the observer and parameter estimation become feasible. Then a stable robust adaptive controller, state observer, parameter update laws are derived that would provide global adaptive system stability and desirable performance. To validate the approach, simulation was performed to a single-link mechanical system with a dynamic friction model and unknown dead zone exists at the system actuation. Then a comparison is presented with the results when there is no dead zone at the system actuation.
Abstract: Over the past few years, XML (eXtensible Mark-up
Language) has emerged as the standard for information
representation and data exchange over the Internet. This paper
provides a kick-start for new researches venturing in XML databases
field. We survey the storage representation for XML document,
review the XML query processing and optimization techniques with
respect to the particular storage instance. Various optimization
technologies have been developed to solve the query retrieval and
updating problems. Towards the later year, most researchers
proposed hybrid optimization techniques. Hybrid system opens the
possibility of covering each technology-s weakness by its strengths.
This paper reviews the advantages and limitations of optimization
techniques.
Abstract: The first generation of Mobile Agents based Intrusion
Detection System just had two components namely data collection
and single centralized analyzer. The disadvantage of this type of
intrusion detection is if connection to the analyzer fails, the entire
system will become useless. In this work, we propose novel hybrid
model for Mobile Agent based Distributed Intrusion Detection
System to overcome the current problem. The proposed model has
new features such as robustness, capability of detecting intrusion
against the IDS itself and capability of updating itself to detect new
pattern of intrusions. In addition, our proposed model is also capable
of tackling some of the weaknesses of centralized Intrusion Detection
System models.
Abstract: In this research, we propose to use the discrete cosine
transform to approximate the cumulative distributions of data cube
cells- values. The cosine transform is known to have a good energy
compaction property and thus can approximate data distribution
functions easily with small number of coefficients. The derived
estimator is accurate and easy to update. We perform experiments to
compare its performance with a well-known technique - the (Haar)
wavelet. The experimental results show that the cosine transform
performs much better than the wavelet in estimation accuracy, speed,
space efficiency, and update easiness.
Abstract: In this paper, novel techniques in increasing the accuracy
and speed of convergence of a Feed forward Back propagation
Artificial Neural Network (FFBPNN) with polynomial activation
function reported in literature is presented. These technique was
subsequently used to determine the coefficients of Autoregressive
Moving Average (ARMA) and Autoregressive (AR) system. The
results obtained by introducing sequential and batch method of weight
initialization, batch method of weight and coefficient update, adaptive
momentum and learning rate technique gives more accurate result
and significant reduction in convergence time when compared t the
traditional method of back propagation algorithm, thereby making
FFBPNN an appropriate technique for online ARMA coefficient
determination.
Abstract: With the proliferation of mobile computing technology, mobile learning (m-learning) will play a vital role in the rapidly growing electronic learning market. However, the acceptance of m-learning by individuals is critical to the successful implementation of m-learning systems. Thus, there is a need to research the factors that affect users- intention to use m-learning. Based on an updated information system (IS) success model, data collected from 350 respondents in Taiwan were tested against the research model using the structural equation modeling approach. The data collected by questionnaire were analyzed to check the validity of constructs. Then hypotheses describing the relationships between the identified constructs and users- satisfaction were formulated and tested.
Abstract: It is a challenge to provide a wide range of queries to
database query systems for small mobile devices, such as the PDAs
and cell phones. Currently, due to the physical and resource
limitations of these devices, most reported database querying systems
developed for them are only offering a small set of pre-determined
queries for users to possibly pose. The above can be resolved by
allowing free-form queries to be entered on the devices. Hence, a
query language that does not restrict the combination of query terms
entered by users is proposed. This paper presents the free-form query
language and the method used in translating free-form queries to
their equivalent SQL statements.
Abstract: The recent developments in computing and
communication technology permit to users to access multimedia
documents with variety of devices (PCs, PDAs, mobile phones...)
having heterogeneous capabilities. This diversification of supports
has trained the need to adapt multimedia documents according to
their execution contexts. A semantic framework for multimedia
document adaptation based on the conceptual neighborhood graphs
was proposed. In this framework, adapting consists on finding
another specification that satisfies the target constraints and which is
as close as possible from the initial document. In this paper, we
propose a new way of building the conceptual neighborhood graphs
to best preserve the proximity between the adapted and the original
documents and to deal with more elaborated relations models by
integrating the relations relaxation graphs that permit to handle the
delays and the distances defined within the relations.
Abstract: A self tuning PID control strategy using reinforcement
learning is proposed in this paper to deal with the control of wind
energy conversion systems (WECS). Actor-Critic learning is used to
tune PID parameters in an adaptive way by taking advantage of the
model-free and on-line learning properties of reinforcement learning
effectively. In order to reduce the demand of storage space and to
improve the learning efficiency, a single RBF neural network is used
to approximate the policy function of Actor and the value function of
Critic simultaneously. The inputs of RBF network are the system
error, as well as the first and the second-order differences of error.
The Actor can realize the mapping from the system state to PID
parameters, while the Critic evaluates the outputs of the Actor and
produces TD error. Based on TD error performance index and
gradient descent method, the updating rules of RBF kernel function
and network weights were given. Simulation results show that the
proposed controller is efficient for WECS and it is perfectly
adaptable and strongly robust, which is better than that of a
conventional PID controller.
Abstract: A hybrid feature based adaptive particle filter algorithm is presented for object tracking in real scenarios with static camera.
The hybrid feature is combined by two effective features: the Grayscale Arranging Pairs (GAP) feature and the color histogram feature. The GAP feature has high discriminative ability even under conditions of severe illumination variation and dynamic background
elements, while the color histogram feature has high reliability to identify the detected objects. The combination of two features covers the shortage of single feature. Furthermore, we adopt an updating
target model so that some external problems such as visual angles can be overcame well. An automatic initialization algorithm is introduced which provides precise initial positions of objects. The experimental
results show the good performance of the proposed method.
Abstract: IETF defines mobility support in IPv6, i.e. MIPv6, to
allow nodes to remain reachable while moving around in the IPv6
internet. When a node moves and visits a foreign network, it is still
reachable through the indirect packet forwarding from its home
network. This triangular routing feature provides node mobility but
increases the communication latency between nodes. This deficiency
can be overcome by using a Binding Update (BU) scheme, which let
nodes keep up-to-date IP addresses and communicate with each other
through direct IP routing. To further protect the security of BU, a
Return Routability (RR) procedure was developed. However, it has
been found that RR procedure is vulnerable to many attacks. In this
paper, we will propose a lightweight RR procedure based on
geometric computing. In consideration of the inherent limitation of
computing resources in mobile node, the proposed scheme is
developed to minimize the cost of computations and to eliminate the
overhead of state maintenance during binding updates. Compared with
other CGA-based BU schemes, our scheme is more efficient and
doesn-t need nonce tables in nodes.
Abstract: The photonic component industry is a highly
innovative industry with a large value chain. In order to ensure the
growth of the industry much effort must be devoted to road mapping
activities. In such activities demand and price evolution forecasting
tools can prove quite useful in order to help in the roadmap
refinement and update process. This paper attempts to provide useful
guidelines in roadmapping of optical components and considers two
models based on diffusion theory and the extended learning curve for
demand and price evolution forecasting.
Abstract: An optimal solution for a large number of constraint
satisfaction problems can be found using the technique of
substitution and elimination of variables analogous to the technique
that is used to solve systems of equations. A decision function
f(A)=max(A2) is used to determine which variables to eliminate. The
algorithm can be expressed in six lines and is remarkable in both its
simplicity and its ability to find an optimal solution. However it is
inefficient in that it needs to square the updated A matrix after each
variable elimination. To overcome this inefficiency the algorithm is
analyzed and it is shown that the A matrix only needs to be squared
once at the first step of the algorithm and then incrementally updated
for subsequent steps, resulting in significant improvement and an
algorithm complexity of O(n3).
Abstract: Estimation time and cost of work completion in a
project and follow up them during execution are contributors to
success or fail of a project, and is very important for project
management team. Delivering on time and within budgeted cost
needs to well managing and controlling the projects. To dealing with
complex task of controlling and modifying the baseline project
schedule during execution, earned value management systems have
been set up and widely used to measure and communicate the real
physical progress of a project. But it often fails to predict the total
duration of the project. In this paper data mining techniques is used
predicting the total project duration in term of Time Estimate At
Completion-EAC (t). For this purpose, we have used a project with
90 activities, it has updated day by day. Then, it is used regular
indexes in literature and applied Earned Duration Method to
calculate time estimate at completion and set these as input data for
prediction and specifying the major parameters among them using
Clem software. By using data mining, the effective parameters on
EAC and the relationship between them could be extracted and it is
very useful to manage a project with minimum delay risks. As we
state, this could be a simple, safe and applicable method in prediction
the completion time of a project during execution.