Abstract: To overcome the product overload of Internet
shoppers, we introduce a semantic recommendation procedure which
is more efficient when applied to Internet shopping malls. The
suggested procedure recommends the semantic products to the
customers and is originally based on Web usage mining, product
classification, association rule mining, and frequently purchasing.
We applied the procedure to the data set of MovieLens Company for
performance evaluation, and some experimental results are provided.
The experimental results have shown superior performance in
terms of coverage and precision.
Abstract: This paper describes a practical approach to design
and develop a hybrid learning with acceleration feedback control
(HLC) scheme for input tracking and end-point vibration suppression
of flexible manipulator systems. Initially, a collocated proportionalderivative
(PD) control scheme using hub-angle and hub-velocity
feedback is developed for control of rigid-body motion of the system.
This is then extended to incorporate a further hybrid control scheme
of the collocated PD control and iterative learning control with
acceleration feedback using genetic algorithms (GAs) to optimize the
learning parameters. Experimental results of the response of the
manipulator with the control schemes are presented in the time and
frequency domains. The performance of the HLC is assessed in terms
of input tracking, level of vibration reduction at resonance modes and
robustness with various payloads.
Abstract: Cloud computing is becoming more and more matured over the last few years and consequently the demands for better cloud services is increasing rapidly. One of the research topics to improve cloud services is the desktop computing in virtualized environment. This paper aims at the development of an adaptive virtual desktop service in cloud computing platform based on our previous research on the virtualization technology. We implement cloud virtual desktop and application software streaming technology that make it possible for providing Virtual Desktop as a Service (VDaaS). Given the development of remote desktop virtualization, it allows shifting the user’s desktop from the traditional PC environment to the cloud-enabled environment, which is stored on a remote virtual machine rather than locally. This proposed effort has the potential to positively provide an efficient, resilience and elastic environment for online cloud service. Users no longer need to burden the platform maintenances and drastically reduces the overall cost of hardware and software licenses. Moreover, this flexible remote desktop service represents the next significant step to the mobile workplace, and it lets users access their desktop environments from virtually anywhere.
Abstract: A low bit rate still image compression scheme by
compressing the indices of Vector Quantization (VQ) and generating
residual codebook is proposed. The indices of VQ are compressed by
exploiting correlation among image blocks, which reduces the bit per
index. A residual codebook similar to VQ codebook is generated that
represents the distortion produced in VQ. Using this residual
codebook the distortion in the reconstructed image is removed,
thereby increasing the image quality. Our scheme combines these two
methods. Experimental results on standard image Lena show that our
scheme can give a reconstructed image with a PSNR value of 31.6 db
at 0.396 bits per pixel. Our scheme is also faster than the existing VQ
variants.
Abstract: In this study, a Loop Back Algorithm for component
connected labeling for detecting objects in a digital image is
presented. The approach is using loop back connected component
labeling algorithm that helps the system to distinguish the object
detected according to their label. Deferent than whole window
scanning technique, this technique reduces the searching time for
locating the object by focusing on the suspected object based on
certain features defined. In this study, the approach was also
implemented for a face detection system. Face detection system is
becoming interesting research since there are many devices or
systems that require detecting the face for certain purposes. The input
can be from still image or videos, therefore the sub process of this
system has to be simple, efficient and accurate to give a good result.
Abstract: Motion capturing technology has been used for quite a
while and several research has been done within this area. Nevertheless,
we discovered open issues within current motion capturing
environments. In this paper we provide a state-of-the-art overview of
the addressed research areas and show issues with current motion
capturing environments. Observations, interviews and questionnaires
have been used to reveal the challenges actors are currently facing in
a motion capturing environment. Furthermore, the idea to create a
more immersive motion capturing environment to improve the acting
performances and motion capturing outcomes as a potential solution
is introduced. It is hereby the goal to explain the found open issues
and the developed ideas which shall serve for further research as a
basis. Moreover, a methodology to address the interaction and
systems design issues is proposed. A future outcome could be that
motion capture actors are able to perform more naturally, especially
if using a non-body-worn solution.
Abstract: In this paper a novel approach for generalized image
retrieval based on semantic contents is presented. A combination of
three feature extraction methods namely color, texture, and edge
histogram descriptor. There is a provision to add new features in
future for better retrieval efficiency. Any combination of these
methods, which is more appropriate for the application, can be used
for retrieval. This is provided through User Interface (UI) in the
form of relevance feedback. The image properties analyzed in this
work are by using computer vision and image processing algorithms.
For color the histogram of images are computed, for texture cooccurrence
matrix based entropy, energy, etc, are calculated and for
edge density it is Edge Histogram Descriptor (EHD) that is found.
For retrieval of images, a novel idea is developed based on greedy
strategy to reduce the computational complexity. The entire system
was developed using AForge.Imaging (an open source product),
MATLAB .NET Builder, C#, and Oracle 10g. The system was tested
with Coral Image database containing 1000 natural images and
achieved better results.
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: 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: 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: 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: Interaction Model plays an important role in Modelbased
Intelligent Interface Agent Architecture for developing
Intelligent User Interface. In this paper we are presenting some
improvements in the algorithms for development interaction model of
interface agent including: the action segmentation algorithm, the
action pair selection algorithm, the final action pair selection
algorithm, the interaction graph construction algorithm and the
probability calculation algorithm. The analysis of the algorithms also
presented. At the end of this paper, we introduce an experimental
program called “Personal Transfer System".
Abstract: In this paper, a model of self-organizing spiking neural networks is introduced and applied to mobile robot environment representation and path planning problem. A network of spike-response-model neurons with a recurrent architecture is used to create robot-s internal representation from surrounding environment. The overall activity of network simulates a self-organizing system with unsupervised learning. A modified A* algorithm is used to find the best path using this internal representation between starting and goal points. This method can be used with good performance for both known and unknown environments.
Abstract: In this paper, we propose a dual version of the first
threshold ring signature scheme based on error-correcting code proposed
by Aguilar et. al in [1]. Our scheme uses an improvement of
Véron zero-knowledge identification scheme, which provide smaller
public and private key sizes and better computation complexity than
the Stern one. This scheme is secure in the random oracle model.
Abstract: Censored Production Rule is an extension of standard
production rule, which is concerned with problems of reasoning with
incomplete information, subject to resource constraints and problem
of reasoning efficiently with exceptions. A CPR has a form: IF A
(Condition) THEN B (Action) UNLESS C (Censor), Where C is the
exception condition. Fuzzy CPR are obtained by augmenting
ordinary fuzzy production rule “If X is A then Y is B with an
exception condition and are written in the form “If X is A then Y is B
Unless Z is C. Such rules are employed in situation in which the
fuzzy conditional statement “If X is A then Y is B" holds frequently
and the exception condition “Z is C" holds rarely. Thus “If X is A
then Y is B" part of the fuzzy CPR express important information
while the unless part acts only as a switch that changes the polarity of
“Y is B" to “Y is not B" when the assertion “Z is C" holds. The
proposed approach is an attempt to discover fuzzy censored
production rules from set of discovered fuzzy if then rules in the
form:
A(X)  B(Y) || C(Z).
Abstract: Cloud Computing is an approach that provides computation and storage services on-demand to clients over the network, independent of device and location. In the last few years, cloud computing became a trend in information technology with many companies that transfer their business processes and applications in the cloud. Cloud computing with service oriented architecture has contributed to rapid development of Geographic Information Systems. Open Geospatial Consortium with its standards provides the interfaces for hosted spatial data and GIS functionality to integrated GIS applications. Furthermore, with the enormous processing power, clouds provide efficient environment for data intensive applications that can be performed efficiently, with higher precision, and greater reliability. This paper presents our work on the geospatial data services within the cloud computing environment and its technology. A cloud computing environment with the strengths and weaknesses of the geographic information system will be introduced. The OGC standards that solve our application interoperability are highlighted. Finally, we outline our system architecture with utilities for requesting and invoking our developed data intensive applications as a web service.
Abstract: This paper deals with the application of Principal Component Analysis (PCA) and the Hotelling-s T2 Chart, using data collected from a drinking water treatment process. PCA is applied primarily for the dimensional reduction of the collected data. The Hotelling-s T2 control chart was used for the fault detection of the process. The data was taken from a United Utilities Multistage Water Treatment Works downloaded from an Integrated Program Management (IPM) dashboard system. The analysis of the results show that Multivariate Statistical Process Control (MSPC) techniques such as PCA, and control charts such as Hotelling-s T2, can be effectively applied for the early fault detection of continuous multivariable processes such as Drinking Water Treatment. The software package SIMCA-P was used to develop the MSPC models and Hotelling-s T2 Chart from the collected data.
Abstract: In this paper, we propose the robust water level detection method based on the accumulated histogram under small changed image which is acquired from water level surveillance camera. In general surveillance system, this is detecting and recognizing invasion from searching area which is in big change on the sequential images. However, in case of a water level detection system, these general surveillance techniques are not suitable due to small change on the water surface. Therefore the algorithm introduces the accumulated histogram which is emphasizing change of water surface in sequential images. Accumulated histogram is based on the current image frame. The histogram is cumulating differences between previous images and current image. But, these differences are also appeared in the land region. The band pass filter is able to remove noises in the accumulated histogram Finally, this algorithm clearly separates water and land regions. After these works, the algorithm converts from the water level value on the image space to the real water level on the real space using calibration table. The detected water level is sent to the host computer with current image. To evaluate the proposed algorithm, we use test images from various situations.
Abstract: Information sharing and gathering are important in the rapid advancement era of technology. The existence of WWW has caused rapid growth of information explosion. Readers are overloaded with too many lengthy text documents in which they are more interested in shorter versions. Oil and gas industry could not escape from this predicament. In this paper, we develop an Automated Text Summarization System known as AutoTextSumm to extract the salient points of oil and gas drilling articles by incorporating statistical approach, keywords identification, synonym words and sentence-s position. In this study, we have conducted interviews with Petroleum Engineering experts and English Language experts to identify the list of most commonly used keywords in the oil and gas drilling domain. The system performance of AutoTextSumm is evaluated using the formulae of precision, recall and F-score. Based on the experimental results, AutoTextSumm has produced satisfactory performance with F-score of 0.81.
Abstract: This paper takes the actual scene of Aletheia
University campus – the Class 2 national monument, the first
educational institute in northern Taiwan as an example, to present a
3D virtual navigation system which supports user positioning and
pre-download mechanism. The proposed system was designed based
on the principle of Voronoi Diagra) to divide the virtual scenes and
its multimedia information, which combining outdoor GPS
positioning and the indoor RFID location detecting function. When
users carry mobile equipments such as notebook computer, UMPC,
EeePC...etc., walking around the actual scenes of indoor and outdoor
areas of campus, this system can automatically detect the moving
path of users and pre-download the needed data so that users will
have a smooth and seamless navigation without waiting.