Abstract: A cart-ball system is a challenging system from the
control engineering point of view. This is due to the nonlinearities,
multivariable, and non-minimum phase behavior present in this
system. This paper is concerned with the problem of modeling and
control of such system. The objective of control strategy is to place
the cart at a desired position while balancing the ball on the top of the
arc-shaped track fixed on the cart. A State-Feedback Controller
(SFC) with a pole-placement method will be designed in order to
control the system. At first, the mathematical model of a cart-ball
system in the state-space form is developed. Then, the linearization of
a model will be established in order to design a SFC. The integral
control strategy will be performed as to control the cart position of a
system. Simulation work is then performed using
MATLAB/SIMULINK software in order to study the performance of
SFC when applied to the system.
Abstract: The cables in a nuclear power plant are designed to be
used for about 40 years in safe operation environment. However, the
heat and radiation in the nuclear power plant causes the rapid
performance deterioration of cables in nuclear vessels and heat
exchangers, which requires cable lifetime estimation. The most
accurate method of estimating the cable lifetime is to evaluate the
cables in a laboratory. However, removing cables while the plant is
operating is not allowed because of its safety and cost. In this paper, a
robot system to estimate the cable lifetime in nuclear power plants is
developed and tested. The developed robot system can calculate a
modulus value to estimate the cable lifetime even when the nuclear
power plant is in operation.
Abstract: Network security attacks are the violation of
information security policy that received much attention to the
computational intelligence society in the last decades. Data mining
has become a very useful technique for detecting network intrusions
by extracting useful knowledge from large number of network data
or logs. Naïve Bayesian classifier is one of the most popular data
mining algorithm for classification, which provides an optimal way
to predict the class of an unknown example. It has been tested that
one set of probability derived from data is not good enough to have
good classification rate. In this paper, we proposed a new learning
algorithm for mining network logs to detect network intrusions
through naïve Bayesian classifier, which first clusters the network
logs into several groups based on similarity of logs, and then
calculates the prior and conditional probabilities for each group of
logs. For classifying a new log, the algorithm checks in which cluster
the log belongs and then use that cluster-s probability set to classify
the new log. We tested the performance of our proposed algorithm by
employing KDD99 benchmark network intrusion detection dataset,
and the experimental results proved that it improves detection rates
as well as reduces false positives for different types of network
intrusions.
Abstract: This paper describes about the process of recognition and classification of brain images such as normal and abnormal based on PSO-SVM. Image Classification is becoming more important for medical diagnosis process. In medical area especially for diagnosis the abnormality of the patient is classified, which plays a great role for the doctors to diagnosis the patient according to the severeness of the diseases. In case of DICOM images it is very tough for optimal recognition and early detection of diseases. Our work focuses on recognition and classification of DICOM image based on collective approach of digital image processing. For optimal recognition and classification Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Support Vector Machine (SVM) are used. The collective approach by using PSO-SVM gives high approximation capability and much faster convergence.
Abstract: In an era of knowledge explosion, the growth of data
increases rapidly day by day. Since data storage is a limited resource,
how to reduce the data space in the process becomes a challenge issue.
Data compression provides a good solution which can lower the
required space. Data mining has many useful applications in recent
years because it can help users discover interesting knowledge in large
databases. However, existing compression algorithms are not
appropriate for data mining. In [1, 2], two different approaches were
proposed to compress databases and then perform the data mining
process. However, they all lack the ability to decompress the data to
their original state and improve the data mining performance. In this
research a new approach called Mining Merged Transactions with the
Quantification Table (M2TQT) was proposed to solve these problems.
M2TQT uses the relationship of transactions to merge related
transactions and builds a quantification table to prune the candidate
itemsets which are impossible to become frequent in order to improve
the performance of mining association rules. The experiments show
that M2TQT performs better than existing approaches.
Abstract: We introduce, a new interactive 3D simulation system of ocular motion and expressions suitable for: (1) character animation applications to game design, film production, HCI (Human Computer Interface), conversational animated agents, and virtual reality; (2) medical applications (ophthalmic neurological and muscular pathologies: research and education); and (3) real time simulation of unconscious cognitive and emotional responses (for use, e.g., in psychological research). The system is comprised of: (1) a physiologically accurate parameterized 3D model of the eyes, eyelids, and eyebrow regions; and (2) a prototype device for realtime control of eye motions and expressions, including unconsciously produced expressions, for application as in (1), (2), and (3) above. The 3D eye simulation system, created using state-of-the-art computer animation technology and 'optimized' for use with an interactive and web deliverable platform, is, to our knowledge, the most advanced/realistic available so far for applications to character animation and medical pedagogy.
Abstract: In this paper we present a system for classifying videos
by frequency spectra. Many videos contain activities with repeating
movements. Sports videos, home improvement videos, or videos
showing mechanical motion are some example areas. Motion of these
areas usually repeats with a certain main frequency and several side
frequencies. Transforming repeating motion to its frequency domain
via FFT reveals these frequencies. Average amplitudes of frequency
intervals can be seen as features of cyclic motion. Hence determining
these features can help to classify videos with repeating movements.
In this paper we explain how to compute frequency spectra for video
clips and how to use them for classifying. Our approach utilizes series
of image moments as a function. This function again is transformed
into its frequency domain.
Abstract: One major difficulty that faces developers of
concurrent and distributed software is analysis for concurrency based
faults like deadlocks. Petri nets are used extensively in the
verification of correctness of concurrent programs. ECATNets [2] are
a category of algebraic Petri nets based on a sound combination of
algebraic abstract types and high-level Petri nets. ECATNets have
'sound' and 'complete' semantics because of their integration in
rewriting logic [12] and its programming language Maude [13].
Rewriting logic is considered as one of very powerful logics in terms
of description, verification and programming of concurrent systems.
We proposed in [4] a method for translating Ada-95 tasking
programs to ECATNets formalism (Ada-ECATNet). In this paper,
we show that ECATNets formalism provides a more compact
translation for Ada programs compared to the other approaches based
on simple Petri nets or Colored Petri nets (CPNs). Such translation
doesn-t reduce only the size of program, but reduces also the number
of program states. We show also, how this compact Ada-ECATNet
may be reduced again by applying reduction rules on it. This double
reduction of Ada-ECATNet permits a considerable minimization of
the memory space and run time of corresponding Maude program.
Abstract: This paper presents a remote on-line diagnostic system
for vehicles via the use of On-Board Diagnostic (OBD), GPS, and 3G
techniques. The main parts of the proposed system are on-board
computer, vehicle monitor server, and vehicle status browser. First,
the on-board computer can obtain the location of deriver and vehicle
status from GPS receiver and OBD interface, respectively. Then
on-board computer will connect with the vehicle monitor server
through 3G network to transmit the real time vehicle system status.
Finally, vehicle status browser could show the remote vehicle status
including vehicle speed, engine rpm, battery voltage, engine coolant
temperature, and diagnostic trouble codes. According to the
experimental results, the proposed system can help fleet managers and
car knockers to understand the remote vehicle status. Therefore this
system can decrease the time of fleet management and vehicle repair
due to the fleet managers and car knockers who find the diagnostic
trouble messages in time.
Abstract: In this report, an OTA which is used in fully
differential pipelined ADC was described. Using gain-boost
architecture with difference-ended amplifier, this OTA achieve
high-gain and high-speed. Besides, the CMFB circuit is also used, and
some methods are concerned to improve the performance. Then, by
optimization the layout design, OTA-s mismatch was reduced. This
design was using TSMC 0.18um CMOS process and simulation both
schematic and layout in Cadence. The result of the simulation shows
that the OTA has a gain up to 80dB,a unity gain bandwidth of about
1.437GHz for a 2pF load, a slew rate is about 428V/μs, a output swing
is 0.2V~1.35V, with the power supply of 1.8V, the power
consumption is 88mW. This amplifier was used in a 10bit 150MHz
pipelined ADC.
Abstract: This paper analyzed the perception of e-commerce
application services by construction material traders in Malaysia.
Five attributes were tested: usability, reputation, trust, privacy and
familiarity. Study methodology consists of survey questionnaire and
statistical analysis that includes reliability analysis, factor analysis,
ANOVA and regression analysis. The respondents were construction
material traders, including hardware stores in Klang Valley, Kuala
Lumpur.
Findings support that usability and familiarity with e-commerce
services in Malaysia have insignificant influence on the acceptance of
e-commerce application. However, reputation, trust and privacy
attributes have significant influence on the choice of e-commerce
acceptance by construction material traders. E-commerce
applications studied included customer database, e-selling, emarketing,
e-payment, e-buying and online advertising. Assumptions
are made that traders have basic knowledge and exposure to ICT
services. i.e. internet service and computers. Study concludes that
reputation, privacy and trust are the three website attributes that
influence the acceptance of e-commerce by construction material
traders.
Abstract: Prediction of fault-prone modules provides one way to
support software quality engineering. Clustering is used to determine
the intrinsic grouping in a set of unlabeled data. Among various
clustering techniques available in literature K-Means clustering
approach is most widely being used. This paper introduces K-Means
based Clustering approach for software finding the fault proneness of
the Object-Oriented systems. The contribution of this paper is that it
has used Metric values of JEdit open source software for generation
of the rules for the categorization of software modules in the
categories of Faulty and non faulty modules and thereafter
empirically validation is performed. The results are measured in
terms of accuracy of prediction, probability of Detection and
Probability of False Alarms.
Abstract: This paper aims at to develop a robust optimization methodology for the mechatronic modules of machine tools by considering all important characteristics from all structural and control domains in one single process. The relationship between these two domains is strongly coupled. In order to reduce the disturbance caused by parameters in either one, the mechanical and controller design domains need to be integrated. Therefore, the concurrent integrated design method Design For Control (DFC), will be employed in this paper. In this connect, it is not only applied to achieve minimal power consumption but also enhance structural performance and system response at same time. To investigate the method for integrated optimization, a mechatronic feed drive system of the machine tools is used as a design platform. Pro/Engineer and AnSys are first used to build the 3D model to analyze and design structure parameters such as elastic deformation, nature frequency and component size, based on their effects and sensitivities to the structure. In addition, the robust controller,based on Quantitative Feedback Theory (QFT), will be applied to determine proper control parameters for the controller. Therefore, overall physical properties of the machine tool will be obtained in the initial stage. Finally, the technology of design for control will be carried out to modify the structural and control parameters to achieve overall system performance. Hence, the corresponding productivity is expected to be greatly improved.
Abstract: In order to study the effect of plant density and
competition of wheat with field bindweed (Convolvulus arvensis) on
yield and agronomical properties of wheat(Triticum Sativum) in
irrigated conditions, a factorial experiment as the base of complete
randomize block design in three replication was conducted at the
field of Kamalvand in khoramabad (Lorestan) region of Iran during
2008-2009. Three plant density (Factor A=200, 230 and 260kg/ha)
three cultivar (Factor B=Bahar,Pishtaz and Alvand) and weed control
(Factor C= control and no control of weeds)were assigned in
experiment. Results show that: Plant density had significant effect
(statistically) on seed yield, 1000 seed weight, weed density and dry
weight of weeds, seed yield and harvest index had been meaningful
effect for cultivars. The interaction between plant density and
cultivars for weed density, seed yield, thousand seed weight and
harvest index were significant. 260 kg/ha (plant density) of wheat had
more effect on increasing of seed yield in Bahar cultivar wheat in
khoramabad region of Iran.
Abstract: Safety, river environment, and sediment utilization are the elements of the target of sediment management. As a change in an element by sediment management, may affect the other two elements, and the priority among three elements depends on stakeholders. It is necessary to develop a method to evaluate the effect of sediment management on each element and an integrated evaluation method for socio-economic effect. In this study, taking Mount Merapi basin as an investigation field, the method for an active volcanic basin was developed. An integrated evaluation method for sediment management was discussed from a socio-economic point on safety, environment, and sediment utilization and a case study of sediment management was evaluated by means of this method. To evaluate the effect of sediment management, some parameters on safety, utilization, and environment have been introduced. From a utilization point of view, job opportunity, additional income of local people, and tax income to local government were used to evaluate the effectiveness of sediment management. The risk degree of river infrastructure was used to describe the effect of sediment management on a safety aspect. To evaluate the effects of sediment management on environment, the mean diameter of grain size distribution of riverbed surface was used. On the coordinate system designating these elements, the direction of change in basin condition by sediment management can be predicted, so that the most preferable sediment management can be decided. The results indicate that the cases of sediment management tend to give the negative impacts on sediment utilization. However, these sediment managements will give positive impacts on safety and environment condition. Evaluation result from a social-economic point of view shows that the case study of sediment management reduces job opportunity and additional income for inhabitants as well as tax income for government. Therefore, it is necessary to make another policy for creating job opportunity for inhabitants to support these sediment managements.
Abstract: Abrasive waterjet is a novel machining process capable of processing wide range of hard-to-machine materials. This research addresses modeling and optimization of the process parameters for this machining technique. To model the process a set of experimental data has been used to evaluate the effects of various parameter settings in cutting 6063-T6 aluminum alloy. The process variables considered here include nozzle diameter, jet traverse rate, jet pressure and abrasive flow rate. Depth of cut, as one of the most important output characteristics, has been evaluated based on different parameter settings. The Taguchi method and regression modeling are used in order to establish the relationships between input and output parameters. The adequacy of the model is evaluated using analysis of variance (ANOVA) technique. The pairwise effects of process parameters settings on process response outputs are also shown graphically. The proposed model is then embedded into a Simulated Annealing algorithm to optimize the process parameters. The optimization is carried out for any desired values of depth of cut. The objective is to determine proper levels of process parameters in order to obtain a certain level of depth of cut. Computational results demonstrate that the proposed solution procedure is quite effective in solving such multi-variable problems.
Abstract: We present a dual-band (Cellular & PCS) dual-path
zero-IF receiver for CDMA2000 diversity, monitoring and
simultaneous-GPS. The secondary path is a SAW-less diversity
CDMA receiver which can be also used for advanced features like
monitoring when supported with an additional external VCO. A GPS
receiver is integrated with its dedicated VCO allowing simultaneous
positioning during a cellular call. The circuit is implemented in a
0.25μm 40GHz-fT BiCMOS process and uses a HVQFN 56-pin
package. It consumes a maximum 300mW from a 2.8V supply in
dual-modes. The chip area is 12.8mm2.
Abstract: This paper considers a scheduling problem in flexible
flow shops environment with the aim of minimizing two important
criteria including makespan and cumulative tardiness of jobs. Since
the proposed problem is known as an Np-hard problem in literature,
we have to develop a meta-heuristic to solve it. We considered
general structure of Genetic Algorithm (GA) and developed a new
version of that based on Data Envelopment Analysis (DEA). Two
objective functions assumed as two different inputs for each Decision
Making Unit (DMU). In this paper we focused on efficiency score of
DMUs and efficient frontier concept in DEA technique. After
introducing the method we defined two different scenarios with
considering two types of mutation operator. Also we provided an
experimental design with some computational results to show the
performance of algorithm. The results show that the algorithm
implements in a reasonable time.
Abstract: In this article, the design of a Supply Chain Network
(SCN) consisting of several suppliers, production plants, distribution
centers and retailers, is considered. Demands of retailers are
considered stochastic parameters, so we generate amounts of data via
simulation to extract a few demand scenarios. Then a mixed integer
two-stage programming model is developed to optimize
simultaneously two objectives: (1) minimization the fixed and
variable cost, (2) maximization the service level. A weighting method
is utilized to solve this two objective problem and a numerical
example is made to show the performance of the model.
Abstract: This paper demonstrates a model of an e-Learning
system based on nowadays learning theory and distant education
practice. The relationships in the model are designed to be simple
and functional and do not necessarily represent any particular e-
Learning environments. It is meant to be a generic e-Learning
system model with implications for any distant education course
instructional design. It allows online instructors to move away from
the discrepancy between the courses and body of knowledge. The
interrelationships of four primary sectors that are at the e-Learning
system are presented in this paper. This integrated model includes
[1] pedagogy, [2] technology, [3] teaching, and [4] learning. There
are interactions within each of these sectors depicted by system loop
map.