Abstract: With a rapid growth in 3D graphics technology over the last few years, people are desired to see more flexible reacting motions of a biped in animations. In particular, it is impossible to anticipate all reacting motions of a biped while facing a perturbation. In this paper, we propose a three-level tracking method for animating a 3D humanoid character. First, we take the laws of physics into account to attach physical attributes, such as mass, gravity, friction, collision, contact, and torque, to bones and joints of a character. The next step is to employ PD controller to follow a reference motion as closely as possible. Once the character cannot tolerate a strong perturbation to prevent itself from falling down, we are capable of tracking a desirable falling-down action to avoid any falling condition inaccuracy. From the experimental results, we demonstrate the effectiveness and flexibility of the proposed method in comparison with conventional data-driven approaches.
Abstract: This paper develops a pedometer with a three-axis acceleration sensor that can be placed with any angle. The proposed pedometer measures the number of steps while users walk, jog or run. It can be worn on users’ waistband or placed within pocket or backpack. The work address to improve on the general pedometers, which can only be used in a single direction or can only count of steps without the continuous exercise judgment mechanism. Finally, experimental results confirm the superior performance of the proposed pedometer.
Abstract: Nowadays the devices of night vision are widely used both for military and civil applications. The variety of night vision applications require a variety of the night vision devices designs. A web-based architecture of a software system for design assessment before producing of night vision devices is developed. The proposed architecture of the web-based system is based on the application of a mathematical model for designing of night vision devices. An algorithm with two components – for iterative design and for intelligent design is developed and integrated into system architecture. The iterative component suggests compatible modules combinations to choose from. The intelligent component provides compatible combinations of modules satisfying given user requirements to device parameters. The proposed web-based architecture of a system for design assessment of night vision devices is tested via a prototype of the system. The testing showed the applicability of both iterative and intelligent components of algorithm.
Abstract: In recent years, new product development became more and more competitive and globalized, and the designing phase is critical for the product success. The concept of modularity can provide the necessary foundation for organizations to design products that can respond rapidly to market needs. The paper describes data structures and algorithms of intelligent Web-based system for modular design taking into account modules compatibility relationship and given design requirements. The system intelligence is realized by developed algorithms for choice of modules reflecting all system restrictions and requirements. The proposed data structure and algorithms are illustrated by case study of personal computer configuration. The applicability of the proposed approach is tested through a prototype of Web-based system.
Abstract: This Paper presents an on-going research in the area of Model-Driven Engineering (MDE). The premise is that UML is too unwieldy to serve as the basis for model-driven engineering. We need a smaller, simpler notation with a cleaner semantics. We propose some ideas for a simpler notation with a clean semantics. The result is known as μML, or the Micro-Modelling Language.
Abstract: Blind Signature were introduced by Chaum. In this
scheme, a signer can “sign” a document without knowing the
document contain. This is particularly important in electronic voting.
CryptO-0N2 is an electronic voting protocol which is development of
CryptO-0N. During its development this protocol has not been
furnished with the requirement of blind signature, so the choice of
voters can be determined by counting center. In this paper will be
presented of implementation of blind signature using RSA algorithm.
Abstract: Monitored 3-Dimensional (3D) video experience can be utilized as “feedback information” to fine tune the service parameters for providing a better service to the demanding 3D service customers. The 3D video experience which includes both video quality and depth perception is influenced by several contextual and content related factors (e.g., ambient illumination condition, content characteristics, etc) due to the complex nature of the 3D video. Therefore, effective factors on this experience should be utilized while assessing it. In this paper, structural information of the depth map sequences of the 3D video is considered as content related factor effective on the depth perception assessment. Cartoon-like filter is utilized to abstract the significant depth levels in the depth map sequences to determine the structural information. Moreover, subjective experiments are conducted using 3D videos associated with cartoon-like depth map sequences to investigate the effectiveness of ambient illumination condition, which is a contextual factor, on depth perception. Using the knowledge gained through this study, 3D video experience metrics can be developed to deliver better service to the 3D video service users.
Abstract: Computer network courses are essential parts of college computer science curriculum and hands-on networking experience is well recognized as an effective approach to help students understand better about the network concepts, the layered architecture of network protocols, and the dynamics of the networks. However, existing networking labs are usually server-based and relatively cumbersome, which require a certain level of specialty and resource to set up and maintain the lab environment. Many universities/colleges lack the resources and build-ups in this field and have difficulty to provide students with hands-on practice labs. A new affordable and easily-adoptable approach to networking labs is desirable to enhance network teaching and learning. In addition, current network labs are short on providing hands-on practice for modern wireless and mobile network learning. With the prevalence of smart mobile devices, wireless and mobile network are permeating into various aspects of our information society. The emerging and modern mobile technology provides computer science students with more authentic learning experience opportunities especially in network learning. A mobile device based hands-on labware can provide an excellent ‘real world’ authentic learning environment for computer network especially for wireless network study. In this paper, we present our mobile device-based hands-on labware (series of lab module) for computer network learning which is guided by authentic learning principles to immerse students in a real world relevant learning environment. We have been using this labware in teaching computer network, mobile security, and wireless network classes. The student feedback shows that students can learn more when they have hands-on authentic learning experience.
Abstract: In this paper we propose a method which improves the efficiency of video coding. Our method combines an adaptive GOP (group of pictures) structure and the shot cut detection. We have analyzed different approaches for shot cut detection with aim to choose the most appropriate one. The next step is to situate N frames to the positions of detected cuts during the process of video encoding. Finally the efficiency of the proposed method is confirmed by simulations and the obtained results are compared with fixed GOP structures of sizes 4, 8, 12, 16, 32, 64, 128 and GOP structure with length of entire video. Proposed method achieved the gain in bit rate from 0.37% to 50.59%, while providing PSNR (Peak Signal-to-Noise Ratio) gain from 1.33% to 0.26% in comparison to simulated fixed GOP structures.
Abstract: This paper presents an ESN-based Arabic phoneme
recognition system trained with supervised, forced and combined
supervised/forced supervised learning algorithms. Mel-Frequency
Cepstrum Coefficients (MFCCs) and Linear Predictive Code (LPC)
techniques are used and compared as the input feature extraction
technique. The system is evaluated using 6 speakers from the King
Abdulaziz Arabic Phonetics Database (KAPD) for Saudi Arabia
dialectic and 34 speakers from the Center for Spoken Language
Understanding (CSLU2002) database of speakers with different
dialectics from 12 Arabic countries. Results for the KAPD and
CSLU2002 Arabic databases show phoneme recognition
performances of 72.31% and 38.20% respectively.
Abstract: Ethnicity identification of face images is of interest in
many areas of application, but existing methods are few and limited.
This paper presents a fusion scheme that uses block-based uniform
local binary patterns and Haar wavelet transform to combine local
and global features. In particular, the LL subband coefficients of the
whole face are fused with the histograms of uniform local binary
patterns from block partitions of the face. We applied the principal
component analysis on the fused features and managed to reduce the
dimensionality of the feature space from 536 down to around 15
without sacrificing too much accuracy. We have conducted a number
of preliminary experiments using a collection of 746 subject face
images. The test results show good accuracy and demonstrate the
potential of fusing global and local features. The fusion approach is
robust, making it easy to further improve the identification at both
feature and score levels.
Abstract: In process control applications, above 90% of the
controllers are of PID type. This paper proposed a robust PI
controller with fractional-order integrator. The PI parameters were
obtained using classical Ziegler-Nichols rules but enhanced with the
application of error filter cascaded to the fractional-order PI. The
controller was applied on steam temperature process that was
described by FOPDT transfer function. The process can be classified
as lag dominating process with very small relative dead-time. The
proposed control scheme was compared with other PI controller
tuned using Ziegler-Nichols and AMIGO rules. Other PI controller
with fractional-order integrator known as F-MIGO was also
considered. All the controllers were subjected to set point change and
load disturbance tests. The performance was measured using Integral
of Squared Error (ISE) and Integral of Control Signal (ICO). The
proposed controller produced best performance for all the tests with
the least ISE index.
Abstract: The wireless mesh networks (WMNs) are emerging technology in wireless networking as they can serve large scale high speed internet access. Due to its wireless multi-hop feature, wireless mesh network is prone to suffer from many attacks, such as denial of service attack (DoS). We consider a special case of DoS attack which is selective forwarding attack (a.k.a. gray hole attack). In such attack, a misbehaving mesh router selectively drops the packets it receives rom its predecessor mesh router. It is very hard to detect that packet loss is due to medium access collision, bad channel quality or because of selective forwarding attack. In this paper, we present a review of detection algorithms of selective forwarding attack and discuss their advantage & disadvantage. Finally we conclude this paper with open research issues and challenges.
Abstract: In this study, a classification-based video
super-resolution method using artificial neural network (ANN) is
proposed to enhance low-resolution (LR) to high-resolution (HR)
frames. The proposed method consists of four main steps:
classification, motion-trace volume collection, temporal adjustment,
and ANN prediction. A classifier is designed based on the edge
properties of a pixel in the LR frame to identify the spatial information.
To exploit the spatio-temporal information, a motion-trace volume is
collected using motion estimation, which can eliminate unfathomable
object motion in the LR frames. In addition, temporal lateral process is
employed for volume adjustment to reduce unnecessary temporal
features. Finally, ANN is applied to each class to learn the complicated
spatio-temporal relationship between LR and HR frames. Simulation
results show that the proposed method successfully improves both
peak signal-to-noise ratio and perceptual quality.
Abstract: Artificial Bee Colony (ABC) algorithm is a relatively new swarm intelligence technique for clustering. It produces higher
quality clusters compared to other population-based algorithms but with poor energy efficiency, cluster quality consistency and typically slower in convergence speed. Inspired by energy saving foraging behavior of natural honey bees this paper presents a Quality and Quantity Aware Artificial Bee Colony (Q2ABC) algorithm to improve quality of cluster identification, energy efficiency and convergence speed of the original ABC. To evaluate the performance of Q2ABC algorithm, experiments were conducted on a suite of ten benchmark UCI datasets. The results demonstrate Q2ABC outperformed ABC and K-means algorithm in the quality of clusters delivered.
Abstract: Due to heavy energy constraints in WSNs clustering is
an efficient way to manage the energy in sensors. There are many
methods already proposed in the area of clustering and research is
still going on to make clustering more energy efficient. In our paper
we are proposing a minimum spanning tree based clustering using
divide and conquer approach. The MST based clustering was first
proposed in 1970’s for large databases. Here we are taking divide and
conquer approach and implementing it for wireless sensor networks
with the constraints attached to the sensor networks. This Divide and
conquer approach is implemented in a way that we don’t have to
construct the whole MST before clustering but we just find the edge
which will be the part of the MST to a corresponding graph and
divide the graph in clusters there itself if that edge from the graph can
be removed judging on certain constraints and hence saving lot of
computation.
Abstract: This paper presents the result of three senior capstone
projects at the Department of Computer Engineering, Prince of
Songkla University, Thailand. These projects focus on developing an
examination management system for the Faculty of Engineering in
order to manage the examination both the examination room
assignments and the examination proctor assignments in each room.
The current version of the software is a web-based application. The
developed software allows the examination proctors to select their
scheduled time online while each subject is assigned to each available
examination room according to its type and the room capacity. The
developed system is evaluated using real data by prospective users of
the system. Several suggestions for further improvements are given
by the testers. Even though the features of the developed software are
not superior, the developing process can be a case study for a projectbased
teaching style. Furthermore, the process of developing this
software can show several issues in developing an educational
support application.
Abstract: According to investigating impact of complexity of
stereoscopic frame pairs on stereoscopic video coding and
transmission, a new rate control algorithm is presented. The proposed
rate control algorithm is performed on three levels: stereoscopic group
of pictures (SGOP) level, stereoscopic frame (SFrame) level and
frame level. A temporal-spatial frame complexity model is firstly
established, in the bits allocation stage, the frame complexity, position
significance and reference property between the left and right frames
are taken into account. Meanwhile, the target buffer is set according to
the frame complexity. Experimental results show that the proposed
method can efficiently control the bitrates, and it outperforms the fixed
quantization parameter method from the rate distortion perspective,
and average PSNR gain between rate-distortion curves (BDPSNR) is
0.21dB.
Abstract: Motion control of flexible arms is more difficult than
that of rigid arms, however utilizing its dynamics enables improved
performance such as a fast motion in short operation time. This paper
investigates a ball throwing robot with one rigid link and one flexible
link. This robot throws a ball at a set speed with a proper control torque.
A mathematical model of this ball throwing robot is derived through
Hamilton’s principle. Several patterns of torque input are designed and
tested through the proposed simulation models. The parameters of
each torque input pattern is optimized and determined by chaos
embedded vector evaluated particle swarm optimization (CEVEPSO).
Then, the residual vibration of the manipulator after throwing is
suppressed with input shaping technique. Finally, a real experiment is
set up for the model checking.
Abstract: Our objective in this paper is to propose an approach
capable of clustering web messages. The clustering is carried out by
assigning, with a certain probability, texts written by the same web
user to the same cluster based on Stylometric features and using
fuzzy clustering algorithms. Focus in the present work is on
comparing the most popular algorithms in fuzzy clustering theory
namely, Fuzzy C-means, Possibilistic C-means and Fuzzy
Possibilistic C-Means.