Abstract: Clustering is the process of subdividing an input data set into a desired number of subgroups so that members of the same subgroup are similar and members of different subgroups have diverse properties. Many heuristic algorithms have been applied to the clustering problem, which is known to be NP Hard. Genetic algorithms have been used in a wide variety of fields to perform clustering, however, the technique normally has a long running time in terms of input set size. This paper proposes an efficient genetic algorithm for clustering on very large data sets, especially on image data sets. The genetic algorithm uses the most time efficient techniques along with preprocessing of the input data set. We test our algorithm on both artificial and real image data sets, both of which are of large size. The experimental results show that our algorithm outperforms the k-means algorithm in terms of running time as well as the quality of the clustering.
Abstract: This article is dedicated to development of
mathematical models for determining the dynamics of
concentration of hazardous substances in urban turbulent
atmosphere. Development of the mathematical models implied
taking into account the time-space variability of the fields of
meteorological items and such turbulent atmosphere data as vortex
nature, nonlinear nature, dissipativity and diffusivity. Knowing the
turbulent airflow velocity is not assumed when developing the
model. However, a simplified model implies that the turbulent and
molecular diffusion ratio is a piecewise constant function that
changes depending on vertical distance from the earth surface.
Thereby an important assumption of vertical stratification of urban
air due to atmospheric accumulation of hazardous substances
emitted by motor vehicles is introduced into the mathematical
model. The suggested simplified non-linear mathematical model of
determining the sought exhaust concentration at a priori unknown
turbulent flow velocity through non-degenerate transformation is
reduced to the model which is subsequently solved analytically.
Abstract: University websites are considered as one of the brand primary touch points for multiple stakeholders, but most of them did not have great designs to create favorable impressions. Some of the elements that web designers should carefully consider are the appearance, the content, the functionality, usability and search engine optimization. However, priority should be placed on website simplicity and negative space. In terms of content, previous research suggests that universities should include reputation, learning environment, graduate career prospects, image destination, cultural integration, and virtual tour on their websites. The study examines how top 200 world ranking science and technology-based universities present their brands online and whether the websites capture the content dimensions. Content analysis of the websites revealed that the top ranking universities captured these dimensions at varying degree. Besides, the UK-based university had better priority on website simplicity and negative space compared to the Malaysian-based university.
Abstract: An approach to develop the FPGA of a flexible key
RSA encryption engine that can be used as a standard device in the
secured communication system is presented. The VHDL modeling of
this RSA encryption engine has the unique characteristics of
supporting multiple key sizes, thus can easily be fit into the systems
that require different levels of security. A simple nested loop addition
and subtraction have been used in order to implement the RSA
operation. This has made the processing time faster and used
comparatively smaller amount of space in the FPGA. The hardware
design is targeted on Altera STRATIX II device and determined that
the flexible key RSA encryption engine can be best suited in the
device named EP2S30F484C3. The RSA encryption implementation
has made use of 13,779 units of logic elements and achieved a clock
frequency of 17.77MHz. It has been verified that this RSA
encryption engine can perform 32-bit, 256-bit and 1024-bit
encryption operation in less than 41.585us, 531.515us and 790.61us
respectively.
Abstract: Intrusion Detection System is significant in network
security. It detects and identifies intrusion behavior or intrusion
attempts in a computer system by monitoring and analyzing the
network packets in real time. In the recent year, intelligent algorithms
applied in the intrusion detection system (IDS) have been an
increasing concern with the rapid growth of the network security.
IDS data deals with a huge amount of data which contains irrelevant
and redundant features causing slow training and testing process,
higher resource consumption as well as poor detection rate. Since the
amount of audit data that an IDS needs to examine is very large even
for a small network, classification by hand is impossible. Hence, the
primary objective of this review is to review the techniques prior to
classification process suit to IDS data.
Abstract: In this paper we present a novel approach for face image coding. The proposed method makes a use of the features of video encoders like motion prediction. At first encoder selects appropriate prototype from the database and warps it according to features of encoding face. Warped prototype is placed as first I frame. Encoding face is placed as second frame as P frame type. Information about features positions, color change, selected prototype and data flow of P frame will be sent to decoder. The condition is both encoder and decoder own the same database of prototypes. We have run experiment with H.264 video encoder and obtained results were compared to results achieved by JPEG and JPEG2000. Obtained results show that our approach is able to achieve 3 times lower bitrate and two times higher PSNR in comparison with JPEG. According to comparison with JPEG2000 the bitrate was very similar, but subjective quality achieved by proposed method is better.
Abstract: Performance of a limited Round-Robin (RR) rule is
studied in order to clarify the characteristics of a realistic sharing
model of a processor. Under the limited RR rule, the processor
allocates to each request a fixed amount of time, called a quantum, in a
fixed order. The sum of the requests being allocated these quanta is
kept below a fixed value. Arriving requests that cannot be allocated
quanta because of such a restriction are queued or rejected. Practical
performance measures, such as the relationship between the mean
sojourn time, the mean number of requests, or the loss probability and
the quantum size are evaluated via simulation. In the evaluation, the
requested service time of an arriving request is converted into a
quantum number. One of these quanta is included in an RR cycle,
which means a series of quanta allocated to each request in a fixed
order. The service time of the arriving request can be evaluated using
the number of RR cycles required to complete the service, the number
of requests receiving service, and the quantum size. Then an increase
or decrease in the number of quanta that are necessary before service is
completed is reevaluated at the arrival or departure of other requests.
Tracking these events and calculations enables us to analyze the
performance of our limited RR rule. In particular, we obtain the most
suitable quantum size, which minimizes the mean sojourn time, for the
case in which the switching time for each quantum is considered.
Abstract: Robot manipulators are highly coupled nonlinear
systems, therefore real system and mathematical model of dynamics
used for control system design are not same. Hence, fine-tuning of
controller is always needed. For better tuning fast simulation speed
is desired. Since, Matlab incorporates LAPACK to increase the speed
and complexity of matrix computation, dynamics, forward and
inverse kinematics of PUMA 560 is modeled on Matlab/Simulink in
such a way that all operations are matrix based which give very less
simulation time. This paper compares PID parameter tuning using
Genetic Algorithm, Simulated Annealing, Generalized Pattern Search
(GPS) and Hybrid Search techniques. Controller performances for all
these methods are compared in terms of joint space ITSE and
cartesian space ISE for tracking circular and butterfly trajectories.
Disturbance signal is added to check robustness of controller. GAGPS
hybrid search technique is showing best results for tuning PID
controller parameters in terms of ITSE and robustness.
Abstract: The stereophotogrammetry modality is gaining more widespread use in the clinical setting. Registration and visualization of this data, in conjunction with conventional 3D volumetric image modalities, provides virtual human data with textured soft tissue and internal anatomical and structural information. In this investigation computed tomography (CT) and stereophotogrammetry data is acquired from 4 anatomical phantoms and registered using the trimmed iterative closest point (TrICP) algorithm. This paper fully addresses the issue of imaging artifacts around the stereophotogrammetry surface edge using the registered CT data as a reference. Several iterative algorithms are implemented to automatically identify and remove stereophotogrammetry surface edge outliers, improving the overall visualization of the combined stereophotogrammetry and CT data. This paper shows that outliers at the surface edge of stereophotogrammetry data can be successfully removed automatically.
Abstract: Theexperiment was carried out with 2x5 male Merino
lambs raised under intensive conditions to investigate the effect of
dietary calcium soap of linseed oil on the color and fatty acid
composition of longissimusdorsi muscle. Control lambs fed a basal
diet and the experimental lambs consumed a diet supplemented with
3% calcium soap of linseed oil. The color values (L*, a*, b* a*/b*
and chroma) were not influenced by dietary treatment. The MUFA
proportion reduced, SFA and PUFA content did not alter. As
expected, the linolenic (C18:3 n3) and thusthe n-3 content
significantly improved by linseed supplement (0.47 and 0.81; 0.78
and 1.16 in control and in experimental samples, respectively). Other
n-3 and n-6 fatty acids had similar valuestocontrol samples. The n-
6/n-3 ratio was significantly narrower in the experimental group (6.31
vs. 9.38) but the P/S ratio did not differ betweenthe two groups.In
conclusion calcium soap of linseed oil seems to be a suitable
supplement form of n-3 fatty acids to improve the nutritive value of
lamb meat.
Abstract: Trace element speciation of an integrated soil
amendment matrix was studied with a modified BCR sequential
extraction procedure. The analysis included pseudo-total
concentration determinations according to USEPA 3051A and
relevant physicochemical properties by standardized methods. Based
on the results, the soil amendment matrix possessed neutralization
capacity comparable to commercial fertilizers. Additionally, the
pseudo-total concentrations of all trace elements included in the
Finnish regulation for agricultural fertilizers were lower than the
respective statutory limit values. According to chemical speciation,
the lability of trace elements increased in the following order: Hg <
Cr < Co < Cu < As < Zn < Ni < Pb < Cd < V < Mo < Ba. The
validity of the BCR approach as a tool for chemical speciation was
confirmed by the additional acid digestion phase. Recovery of trace
elements during the procedure assured the validity of the approach
and indicated good quality of the analytical work.
Abstract: This paper proposes a solution to the motion planning
and control problem of a point-mass robot which is required to move
safely to a designated target in a priori known workspace cluttered
with fixed elliptical obstacles of arbitrary position and sizes. A
tailored and unique algorithm for target convergence and obstacle
avoidance is proposed that will work for any number of fixed
obstacles. The control laws proposed in this paper also ensures that
the equilibrium point of the given system is asymptotically stable.
Computer simulations with the proposed technique and applications
to a planar (RP) manipulator will be presented.
Abstract: Application-Specific Instruction (ASI ) set Processors
(ASIP) have become an important design choice for embedded
systems due to runtime flexibility, which cannot be provided by
custom ASIC solutions. One major bottleneck in maximizing ASIP
performance is the limitation on the data bandwidth between the
General Purpose Register File (GPRF) and ASIs. This paper presents
the Implicit Registers (IRs) to provide the desirable data bandwidth.
An ASI Input/Output model is proposed to formulate the overheads of
the additional data transfer between the GPRF and IRs, therefore,
an IRs allocation algorithm is used to achieve the better performance
by minimizing the number of extra data transfer instructions. The
experiment results show an up to 3.33x speedup compared to the
results without using IRs.
Abstract: Hyperglycemia-mediated accumulation of advanced glycation end-products (AGEs) play a pivotal role in the development of diabetic complications by inducing inflammation. In the present study, we evaluated the possible effects of water/ethanol (1/1, v/v) extracts (WEE) and its fractions from Canarium album Raeusch. (Chinese olive) which is a fruit used on AGEs-stimulated oxidative stress and inflammation in monocytes and vascular endothelial cells. Co-incubation of EA.hy926 endothelial cells with WEE and its fractions for 24h resulted in a significant decrease of monocyte–endothelial cell adhesion, the expression of ICAM-1, generation of intracellular ROS and depletion of GSH induced by AGEs. Chinese olive fruit extracts also reduced the expression of pro-inflammatory mediates, such as TNF-α, IL-1β and IL-6 in THP-1 cells. These findings suggested that Chinese olive fruit was able to protect vascular endothelium from dysfunction induced by AGEs.
Abstract: Reducing river sediments through path correction and
preservation of river walls leads to considerable reduction of
sedimentation at the pumping stations. Path correction and
preservation of walls is not limited to one particular method but,
depending on various conditions, a combination of several methods
can be employed. In this article, we try to review and evaluate
methods for preservation of river banks in order to reduce sediments.
Abstract: The protection of parallel transmission lines has been a challenging task due to mutual coupling between the adjacent circuits of the line. This paper presents a novel scheme for detection and classification of faults on parallel transmission lines. The proposed approach uses combination of wavelet transform and neural network, to solve the problem. While wavelet transform is a powerful mathematical tool which can be employed as a fast and very effective means of analyzing power system transient signals, artificial neural network has a ability to classify non-linear relationship between measured signals by identifying different patterns of the associated signals. The proposed algorithm consists of time-frequency analysis of fault generated transients using wavelet transform, followed by pattern recognition using artificial neural network to identify the type of the fault. MATLAB/Simulink is used to generate fault signals and verify the correctness of the algorithm. The adaptive discrimination scheme is tested by simulating different types of fault and varying fault resistance, fault location and fault inception time, on a given power system model. The simulation results show that the proposed scheme for fault diagnosis is able to classify all the faults on the parallel transmission line rapidly and correctly.
Abstract: Current technological advances pale in comparison to the changes in social behaviors and 'sense of place' that is being empowered since the Internet made it on the scene. Today-s students view the Internet as both a source of entertainment and an educational tool. The development of virtual environments is a conceptual framework that needs to be addressed by educators and it is important that they become familiar with who these virtual learners are and how they are motivated to learn. Massively multiplayer online role playing games (MMORPGs), if well designed, could become the vehicle of choice to deliver learning content. We suggest that these games, in order to accomplish these goals, must begin with well-established instructional design principles that are co-aligned with established principles of video game design. And have the opportunity to provide an instructional model of significant prescriptive power. The authors believe that game designers need to take advantage of the natural motivation player-learners have for playing games by developing them in such a way so as to promote, intrinsic motivation, content learning, transfer of knowledge, and naturalization.
Abstract: This paper presents a new version of the SVM mixture algorithm initially proposed by Kwok for classification and regression problems. For both cases, a slight modification of the mixture model leads to a standard SVM training problem, to the existence of an exact solution and allows the direct use of well known decomposition and working set selection algorithms. Only the regression case is considered in this paper but classification has been addressed in a very similar way. This method has been successfully applied to engine pollutants emission modeling.
Abstract: This paper presents the development of a Bayesian
belief network classifier for prediction of graft status and survival
period in renal transplantation using the patient profile information
prior to the transplantation. The objective was to explore feasibility
of developing a decision making tool for identifying the most suitable
recipient among the candidate pool members. The dataset was
compiled from the University of Toledo Medical Center Hospital
patients as reported to the United Network Organ Sharing, and had
1228 patient records for the period covering 1987 through 2009. The
Bayes net classifiers were developed using the Weka machine
learning software workbench. Two separate classifiers were induced
from the data set, one to predict the status of the graft as either failed
or living, and a second classifier to predict the graft survival period.
The classifier for graft status prediction performed very well with a
prediction accuracy of 97.8% and true positive values of 0.967 and
0.988 for the living and failed classes, respectively. The second
classifier to predict the graft survival period yielded a prediction
accuracy of 68.2% and a true positive rate of 0.85 for the class
representing those instances with kidneys failing during the first year
following transplantation. Simulation results indicated that it is
feasible to develop a successful Bayesian belief network classifier for
prediction of graft status, but not the graft survival period, using the
information in UNOS database.
Abstract: The goal of the study reported in the paper was to
determine whether Ambient Occlusion Shading (AOS) has a significant effect on users' perception of American Sign Language (ASL) finger spelling animations. Seventy-one (71) subjects
participated in the study; all subjects were fluent in ASL. The participants were asked to watch forty (40) sign language animation
clips representing twenty (20) finger spelled words. Twenty (20) clips did not show ambient occlusion, whereas the other twenty (20) were
rendered using ambient occlusion shading. After viewing each animation, subjects were asked to type the word being finger-spelled and rate its legibility. Findings show that the presence of AOS had a significant effect on the subjects perception of the signed words.
Subjects were able to recognize the animated words rendered with AOS with higher level of accuracy, and the legibility ratings of the animations showing AOS were consistently higher across subjects.