Abstract: Functional imaging procedures for the non-invasive assessment of tissue microcirculation are highly requested, but require a mathematical approach describing the trans- and intercapillary passage of tracer particles. Up to now, two theoretical, for the moment different concepts have been established for tracer kinetic modeling of contrast agent transport in tissues: pharmacokinetic compartment models, which are usually written as coupled differential equations, and the indicator dilution theory, which can be generalized in accordance with the theory of lineartime- invariant (LTI) systems by using a convolution approach. Based on mathematical considerations, it can be shown that also in the case of an open two-compartment model well-known from functional imaging, the concentration-time course in tissue is given by a convolution, which allows a separation of the arterial input function from a system function being the impulse response function, summarizing the available information on tissue microcirculation. Due to this reason, it is possible to integrate the open two-compartment model into the system-theoretic concept of indicator dilution theory (IDT) and thus results known from IDT remain valid for the compartment approach. According to the long number of applications of compartmental analysis, even for a more general context similar solutions of the so-called forward problem can already be found in the extensively available appropriate literature of the seventies and early eighties. Nevertheless, to this day, within the field of biomedical imaging – not from the mathematical point of view – there seems to be a trench between both approaches, which the author would like to get over by exemplary analysis of the well-known model.
Abstract: This study focuses on bureau management
technologies and information systems in developing countries.
Developing countries use such systems which facilitate executive and
organizational functions through the utilization of bureau
management technologies and provide the executive staff with
necessary information.
The concepts of data and information differ from each other in
developing countries, and thus the concepts of data processing and
information processing are different. Symbols represent ideas,
objects, figures, letters and numbers. Data processing system is an
integrated system which deals with the processing of the data related
to the internal and external environment of the organization in order
to make decisions, create plans and develop strategies; it goes
without saying that this system is composed of both human beings
and machines. Information is obtained through the acquisition and
the processing of data. On the other hand, data are raw
communicative messages. Within this framework, data processing
equals to producing plausible information out of raw data.
Organizations in developing countries need to obtain information
relevant to them because rapid changes in the organizational arena
require rapid access to accurate information. The most significant
role of the directors and managers who work in the organizational
arena is to make decisions. Making a correct decision is possible only
when the directors and managers are equipped with sound ideas and
appropriate information. Therefore, acquisition, organization and
distribution of information gain significance. Today-s organizations
make use of computer-assisted “Management Information Systems"
in order to obtain and distribute information.
Decision Support System which is closely related to practice is an
information system that facilitates the director-s task of making
decisions. Decision Support System integrates human intelligence,
information technology and software in order to solve the complex
problems. With the support of the computer technology and software
systems, Decision Support System produces information relevant to
the decision to be made by the director and provides the executive
staff with supportive ideas about the decision.
Artificial Intelligence programs which transfer the studies and
experiences of the people to the computer are called expert systems.
An expert system stores expert information in a limited area and can
solve problems by deriving rational consequences.
Bureau management technologies and information systems in
developing countries create a kind of information society and
information economy which make those countries have their places
in the global socio-economic structure and which enable them to play
a reasonable and fruitful role; therefore it is of crucial importance to
make use of information and management technologies in order to
work together with innovative and enterprising individuals and it is
also significant to create “scientific policies" based on information
and technology in the fields of economy, politics, law and culture.
Abstract: This paper indicate the importance of
telecommunications supervision systems (TSS), integrating
heterogeneous TSS into single system thru umbrella systems,
introduces the structure, features, requirements of TSS and TSS
related intelligent solutions.
Abstract: This paper maps the structure of the social network of
the 2011 class ofsixty graduate students of the Masters of Science
(Knowledge Management) programme at the Nanyang Technological
University, based on their friending relationships on Facebook. To
ensure anonymity, actual names were not used. Instead, they were
replaced with codes constructed from their gender, nationality, mode
of study, year of enrollment and a unique number. The relationships
between friends within the class, and among the seniors and alumni
of the programme wereplotted. UCINet and Pajek were used to plot
the sociogram, to compute the density, inclusivity, and degree,
global, betweenness, and Bonacich centralities, to partition the
students into two groups, namely, active and peripheral, and to
identify the cut-points. Homophily was investigated, and it was
observed for nationality and study mode. The groups students formed
on Facebook were also studied, and of fifteen groups, eight were
classified as dead, which we defined as those that have been inactive
for over two months.
Abstract: This paper presents the results of an experimental
investigation carried out to evaluate the shrinkage of High Strength
Concrete. High Strength Concrete is made by partially replacement of
cement by flyash and silica fume. The shrinkage of High Strength
Concrete has been studied using the different types of coarse and fine
aggregates i.e. Sandstone and Granite of 12.5 mm size and Yamuna
and Badarpur Sand. The Mix proportion of concrete is 1:0.8:2.2 with
water cement ratio as 0.30. Superplasticizer dose @ of 2% by weight
of cement is added to achieve the required degree of workability in
terms of compaction factor.
From the test results of the above investigation it can be concluded
that the shrinkage strain of High Strength Concrete increases with
age. The shrinkage strain of concrete with replacement of cement by
10% of Flyash and Silica fume respectively at various ages are more
(6 to 10%) than the shrinkage strain of concrete without Flyash and
Silica fume. The shrinkage strain of concrete with Badarpur sand as
Fine aggregate at 90 days is slightly less (10%) than that of concrete
with Yamuna Sand. Further, the shrinkage strain of concrete with
Granite as Coarse aggregate at 90 days is slightly less (6 to 7%) than
that of concrete with Sand stone as aggregate of same size. The
shrinkage strain of High Strength Concrete is also compared with that
of normal strength concrete. Test results show that the shrinkage
strain of high strength concrete is less than that of normal strength
concrete.
Abstract: We consider a typical problem in the assembly of
printed circuit boards (PCBs) in a two-machine flow shop system to
simultaneously minimize the weighted sum of weighted tardiness and
weighted flow time. The investigated problem is a group scheduling
problem in which PCBs are assembled in groups and the interest is to
find the best sequence of groups as well as the boards within each
group to minimize the objective function value. The type of setup
operation between any two board groups is characterized as carryover
sequence-dependent setup time, which exactly matches with the real
application of this problem. As a technical constraint, all of the
boards must be kitted before the assembly operation starts (kitting
operation) and by kitting staff. The main idea developed in this paper
is to completely eliminate the role of kitting staff by assigning the
task of kitting to the machine operator during the time he is idle
which is referred to as integration of internal (machine) and external
(kitting) setup times. Performing the kitting operation, which is a
preparation process of the next set of boards while the other boards
are currently being assembled, results in the boards to continuously
enter the system or have dynamic arrival times. Consequently, a
dynamic PCB assembly system is introduced for the first time in the
assembly of PCBs, which also has characteristics similar to that of
just-in-time manufacturing. The problem investigated is
computationally very complex, meaning that finding the optimal
solutions especially when the problem size gets larger is impossible.
Thus, a heuristic based on Genetic Algorithm (GA) is employed. An
example problem on the application of the GA developed is
demonstrated and also numerical results of applying the GA on
solving several instances are provided.
Abstract: The main aim of this study is to identify the most
influential variables that cause defects on the items produced by a
casting company located in Turkey. To this end, one of the items
produced by the company with high defective percentage rates is
selected. Two approaches-the regression analysis and decision treesare
used to model the relationship between process parameters and
defect types. Although logistic regression models failed, decision tree
model gives meaningful results. Based on these results, it can be
claimed that the decision tree approach is a promising technique for
determining the most important process variables.
Abstract: Many corporations are seriously concerned about
security of networks and therefore, their network supervisors are still
reluctant to install WLANs. In this regards, the IEEE802.11i standard
was developed to address the security problems, even though the
mistrust of the wireless LAN technology is still existing. The thought
was that the best security solutions could be found in open standards
based technologies that can be delivered by Virtual Private
Networking (VPN) being used for long time without addressing any
security holes for the past few years. This work, addresses this issue
and presents a simulated wireless LAN of IEEE802.11g protocol, and
analyzes impact of integrating Virtual Private Network technology to
secure the flow of traffic between the client and the server within the
LAN, using OPNET WLAN utility. Two Wireless LAN scenarios
have been introduced and simulated. These are based on normal
extension to a wired network and VPN over extension to a wired
network. The results of the two scenarios are compared and indicate
the impact of improving performance, measured by response time
and load, of Virtual Private Network over wireless LAN.
Abstract: Employing a recently introduced unified adaptive filter
theory, we show how the performance of a large number of important
adaptive filter algorithms can be predicted within a general framework
in nonstationary environment. This approach is based on energy conservation
arguments and does not need to assume a Gaussian or white
distribution for the regressors. This general performance analysis can
be used to evaluate the mean square performance of the Least Mean
Square (LMS) algorithm, its normalized version (NLMS), the family
of Affine Projection Algorithms (APA), the Recursive Least Squares
(RLS), the Data-Reusing LMS (DR-LMS), its normalized version
(NDR-LMS), the Block Least Mean Squares (BLMS), the Block
Normalized LMS (BNLMS), the Transform Domain Adaptive Filters
(TDAF) and the Subband Adaptive Filters (SAF) in nonstationary
environment. Also, we establish the general expressions for the
steady-state excess mean square in this environment for all these
adaptive algorithms. Finally, we demonstrate through simulations that
these results are useful in predicting the adaptive filter performance.
Abstract: Integrated fiber-wireless (FiWi) access networks are a viable solution that can deliver the high profile quadruple play services. Passive optical networks (PON) networks integrated with wireless access networks provide ubiquitous characteristics for high bandwidth applications. Operation of PON improves by employing a variety of multiplexing techniques. One of it is time division/wavelength division multiplexed (TDM/WDM) architecture that improves the performance of optical-wireless access networks. This paper proposes a novel feedback-based TDM/WDM-PON architecture and introduces a model of integrated PON-FiWi networks. Feedback-based link architecture is an efficient solution to improves the performance of optical-line-terminal (OLT) and interlink optical-network-units (ONUs) communication. Furthermore, the feedback-based WDM/TDM-PON architecture is compared with existing architectures in terms of capacity of network throughput.
Abstract: Sleep stage scoring is the process of classifying the
stage of the sleep in which the subject is in. Sleep is classified into
two states based on the constellation of physiological parameters.
The two states are the non-rapid eye movement (NREM) and the
rapid eye movement (REM). The NREM sleep is also classified into
four stages (1-4). These states and the state wakefulness are
distinguished from each other based on the brain activity. In this
work, a classification method for automated sleep stage scoring
based on a single EEG recording using wavelet packet decomposition
was implemented. Thirty two ploysomnographic recording from the
MIT-BIH database were used for training and validation of the
proposed method. A single EEG recording was extracted and
smoothed using Savitzky-Golay filter. Wavelet packets
decomposition up to the fourth level based on 20th order Daubechies
filter was used to extract features from the EEG signal. A features
vector of 54 features was formed. It was reduced to a size of 25 using
the gain ratio method and fed into a classifier of regression trees. The
regression trees were trained using 67% of the records available. The
records for training were selected based on cross validation of the
records. The remaining of the records was used for testing the
classifier. The overall correct rate of the proposed method was found
to be around 75%, which is acceptable compared to the techniques in
the literature.
Abstract: The purpose of this research is to develop and apply the
RSCMAC to enhance the dynamic accuracy of Global Positioning
System (GPS). GPS devices provide services of accurate positioning,
speed detection and highly precise time standard for over 98% area on
the earth. The overall operation of Global Positioning System includes
24 GPS satellites in space; signal transmission that includes 2
frequency carrier waves (Link 1 and Link 2) and 2 sets random
telegraphic codes (C/A code and P code), on-earth monitoring stations
or client GPS receivers. Only 4 satellites utilization, the client position
and its elevation can be detected rapidly. The more receivable
satellites, the more accurate position can be decoded. Currently, the
standard positioning accuracy of the simplified GPS receiver is greatly
increased, but due to affected by the error of satellite clock, the
troposphere delay and the ionosphere delay, current measurement
accuracy is in the level of 5~15m. In increasing the dynamic GPS
positioning accuracy, most researchers mainly use inertial navigation
system (INS) and installation of other sensors or maps for the
assistance. This research utilizes the RSCMAC advantages of fast
learning, learning convergence assurance, solving capability of
time-related dynamic system problems with the static positioning
calibration structure to improve and increase the GPS dynamic
accuracy. The increasing of GPS dynamic positioning accuracy can be
achieved by using RSCMAC system with GPS receivers collecting
dynamic error data for the error prediction and follows by using the
predicted error to correct the GPS dynamic positioning data. The
ultimate purpose of this research is to improve the dynamic positioning
error of cheap GPS receivers and the economic benefits will be
enhanced while the accuracy is increased.
Abstract: Problem solving has traditionally been one of the principal research areas for artificial intelligence. Yet, although artificial intelligence reasoning techniques have been employed in several product support systems, the benefit of integrating product support, knowledge engineering, and problem solving, is still unclear. This paper studies the synergy of these areas and proposes a knowledge engineering framework that integrates product support systems and artificial intelligence techniques. The framework includes four spaces; the data, problem, hypothesis, and solution ones. The data space incorporates the knowledge needed for structured reasoning to take place, the problem space contains representations of problems, and the hypothesis space utilizes a multimodal reasoning approach to produce appropriate solutions in the form of virtual documents. The solution space is used as the gateway between the system and the user. The proposed framework enables the development of product support systems in terms of smaller, more manageable steps while the combination of different reasoning techniques provides a way to overcome the lack of documentation resources.
Abstract: Tourism industry is an important sector in Malaysia economy and this motivates the examination of long-run relationships between tourist arrivals from three selected European countries in Malaysia and four possible determinants; relative prices, exchange rates, transportation cost and relative prices of substitute destination. The study utilizes data from January 1999 to September 2008 and employs standard econometric techniques that include unit root test and cointegration test. The estimated demand model indicates that depreciation of local currency and increases in prices at substitute destination have positive impact on tourist arrivals while increase in transportation cost has negative impact on tourist arrivals. In addition, the model suggests that higher rate of increase in local prices relative to prices at tourist country of origin may not deter tourists from coming to Malaysia
Abstract: Business Process Modeling (BPM) is the first and
most important step in business process management lifecycle. Graph
based formalism and rule based formalism are the two most
predominant formalisms on which process modeling languages are
developed. BPM technology continues to face challenges in coping
with dynamic business environments where requirements and goals
are constantly changing at the execution time. Graph based
formalisms incur problems to react to dynamic changes in Business
Process (BP) at the runtime instances. In this research, an adaptive
and flexible framework based on the integration between Object
Oriented diagramming technique and Petri Net modeling language is
proposed in order to support change management techniques for
BPM and increase the representation capability for Object Oriented
modeling for the dynamic changes in the runtime instances. The
proposed framework is applied in a higher education environment to
achieve flexible, updatable and dynamic BP.
Abstract: In the present work, we introduce the particle swarm optimization called (PSO in short) to avoid the Runge-s phenomenon occurring in many numerical problems. This new approach is tested with some numerical examples including the generalized integral quadrature method in order to solve the Volterra-s integral equations
Abstract: In this paper, the semi–ratio–dependent predator-prey system with nonmonotonic functional response on time scales is investigated. By using the coincidence degree theory, sufficient conditions for existence of periodic solutions are obtained.
Abstract: This paper establishes some closed formulas for
Riemann- Liouville impulsive fractional integral calculus and also
for Riemann- Liouville and Caputo impulsive fractional
derivatives.
Abstract: In order to derive important parameters concerning
mobile subscriber MS with ongoing calls in Low Earth Orbit Mobile
Satellite Systems LEO MSSs, a positioning system had to be
integrated into MSS in order to localize mobile subscribers MSs and
track them during the connection. Such integration is regarded as a
complex implementation.
We propose in this paper a novel method based on advantages of
mobility model of Low Earth Orbit Mobile Satellite System LEO
MSS called Evaluation Parameters Method EPM which allows for
such systems the evaluation of different information concerning a
MS with a call in progress even if its location is unknown.
Abstract: This paper reports a new approach on identifying the
individuality of persons by using parametric classification of multiple
mental thoughts. In the approach, electroencephalogram (EEG)
signals were recorded when the subjects were thinking of one or
more (up to five) mental thoughts. Autoregressive features were
computed from these EEG signals and classified by Linear
Discriminant classifier. The results here indicate that near perfect
identification of 400 test EEG patterns from four subjects was
possible, thereby opening up a new avenue in biometrics.