Abstract: In the age of global communications, heterogeneous
networks are seen to be the best choice of strategy to ensure continuous and uninterruptible services. This will allow mobile
terminal to stay in connection even they are migrating into different segment coverage through the handoff process. With the increase of
teletraffic demands in mobile cellular system, hierarchical cellular systems have been adopted extensively for more efficient channel
utilization and better QoS (Quality of Service). This paper presents a
bidirectional call overflow scheme between two layers of microcells and macrocells, where handoffs are decided by the velocity of mobile
making the call. To ensure that handoff calls are given higher priorities, it is assumed that guard channels are assigned in both
macrocells and microcells. A hysteresis value introduced in mobile velocity is used to allow mobile roam in the same cell if its velocity
changes back within the set threshold values. By doing this the number of handoffs is reduced thereby reducing the processing overhead and enhancing the quality of service to the end user.
Abstract: Modeling and simulation of biochemical reactions is of great interest in the context of system biology. The central dogma of this re-emerging area states that it is system dynamics and organizing principles of complex biological phenomena that give rise to functioning and function of cells. Cell functions, such as growth, division, differentiation and apoptosis are temporal processes, that can be understood if they are treated as dynamic systems. System biology focuses on an understanding of functional activity from a system-wide perspective and, consequently, it is defined by two hey questions: (i) how do the components within a cell interact, so as to bring about its structure and functioning? (ii) How do cells interact, so as to develop and maintain higher levels of organization and functions? In recent years, wet-lab biologists embraced mathematical modeling and simulation as two essential means toward answering the above questions. The credo of dynamics system theory is that the behavior of a biological system is given by the temporal evolution of its state. Our understanding of the time behavior of a biological system can be measured by the extent to which a simulation mimics the real behavior of that system. Deviations of a simulation indicate either limitations or errors in our knowledge. The aim of this paper is to summarize and review the main conceptual frameworks in which models of biochemical networks can be developed. In particular, we review the stochastic molecular modelling approaches, by reporting the principal conceptualizations suggested by A. A. Markov, P. Langevin, A. Fokker, M. Planck, D. T. Gillespie, N. G. van Kampfen, and recently by D. Wilkinson, O. Wolkenhauer, P. S. Jöberg and by the author.
Abstract: The article presents test results on the changes
occurring in sewage sludge during the process of its storage. Tests
were conducted on mechanically dehydrated sewage sludge derived
from large municipal sewage treatment plants equipped with
biological sewage treatment systems. In testing presented in the paper
the focus was on the basic fuel properties of sewage sludge: moisture
content, heat of combustion, carbon share. In the first part of the
article the overview of the issues concerning the sewage sludge
management is presented and the genesis of tests is explained.
Further in the paper, selected results of conducted tests are discussed.
Changes in tested parameters were determined in the period of a 10-
month sewage storage.
Abstract: Today, building automation is advancing from simple
monitoring and control tasks of lightning and heating towards more
and more complex applications that require a dynamic perception
and interpretation of different scenes occurring in a building. Current
approaches cannot handle these newly upcoming demands. In this
article, a bionically inspired approach for multimodal, dynamic scene
perception and interpretation is presented, which is based on neuroscientific
and neuro-psychological research findings about the perceptual
system of the human brain. This approach bases on data from diverse
sensory modalities being processed in a so-called neuro-symbolic
network. With its parallel structure and with its basic elements being
information processing and storing units at the same time, a very
efficient method for scene perception is provided overcoming the
problems and bottlenecks of classical dynamic scene interpretation
systems.
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: Wavelength multiplexing (WDM) technology along
with optical amplifiers is used for optical communication systems in
S-band, C-band and L-band. To improve the overall system
performance Hybrid amplifiers consisting of cascaded TDFA and
EDFA with different gain bandwidths are preferred for long haul
wavelength multiplexed optical communication systems. This paper
deals with statistical analysis of different configuration of hybrid
amplifier i.e. analysis of TDFA-EDFA configuration and EDFA –
TDFA configuration. In this paper One-Way ANOVA method is used
for statistical analysis.
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: Road traffic accidents are a major cause of death worldwide. In an attempt to reduce accidents, some research efforts have focused on creating Advanced Driver Assistance Systems (ADAS) able to detect vehicle, driver and environmental conditions and to use this information to identify cues for potential accidents. This paper presents continued work on a novel Non-intrusive Intelligent Driver Assistance and Safety System (Ni-DASS) for assessing driver point of regard within vehicles. It uses an on-board CCD camera to observe the driver-s face. A template matching approach is used to compare the driver-s eye-gaze pattern with a set of eye-gesture templates of the driver looking at different focal points within the vehicle. The windscreen is divided into cells and comparison of the driver-s eye-gaze pattern with templates of a driver-s eyes looking at each cell is used to determine the driver-s point of regard on the windscreen. Results indicate that the proposed technique could be useful in situations where low resolution estimates of driver point of regard are adequate. For instance, To allow ADAS systems to alert the driver if he/she has positively failed to observe a hazard.
Abstract: Assembly line balancing is a very important issue in
mass production systems due to production cost. Although many
studies have been done on this topic, but because assembly line
balancing problems are so complex they are categorized as NP-hard
problems and researchers strongly recommend using heuristic
methods. This paper presents a new heuristic approach called the
critical task method (CTM) for solving U-shape assembly line
balancing problems. The performance of the proposed heuristic
method is tested by solving a number of test problems and comparing
them with 12 other heuristics available in the literature to confirm the
superior performance of the proposed heuristic. Furthermore, to
prove the efficiency of the proposed CTM, the objectives are
increased to minimize the number of workstation (or equivalently
maximize line efficiency), and minimizing the smoothness index.
Finally, it is proven that the proposed heuristic is more efficient than
the others to solve the U-shape assembly line balancing problem.
Abstract: Nowadays companies strive to survive in a
competitive global environment. To speed up product
development/modifications, it is suggested to adopt a collaborative
product development approach. However, despite the advantages of
new IT improvements still many CAx systems work separately and
locally. Collaborative design and manufacture requires a product
information model that supports related CAx product data models. To
solve this problem many solutions are proposed, which the most
successful one is adopting the STEP standard as a product data model
to develop a collaborative CAx platform. However, the improvement
of the STEP-s Application Protocols (APs) over the time, huge
number of STEP AP-s and cc-s, the high costs of implementation,
costly process for conversion of older CAx software files to the STEP
neutral file format; and lack of STEP knowledge, that usually slows
down the implementation of the STEP standard in collaborative data
exchange, management and integration should be considered. In this
paper the requirements for a successful collaborative CAx system is
discussed. The STEP standard capability for product data integration
and its shortcomings as well as the dominant platforms for supporting
CAx collaboration management and product data integration are
reviewed. Finally a platform named LAYMOD to fulfil the
requirements of CAx collaborative environment and integrating the
product data is proposed. The platform is a layered platform to enable
global collaboration among different CAx software
packages/developers. It also adopts the STEP modular architecture
and the XML data structures to enable collaboration between CAx
software packages as well as overcoming the STEP standard
limitations. The architecture and procedures of LAYMOD platform
to manage collaboration and avoid contradicts in product data
integration are introduced.
Abstract: Visual inputs are one of the key sources from which
humans perceive the environment and 'understand' what is
happening. Artificial systems perceive the visual inputs as digital
images. The images need to be processed and analysed. Within the
human brain, processing of visual inputs and subsequent
development of perception is one of its major functionalities. In this
paper we present part of our research project, which aims at the
development of an artificial model for visual perception (or
'understanding') based on the human perceptive and cognitive
systems. We propose a new model for perception from visual inputs
and a way of understaning or interpreting images using the model.
We demonstrate the implementation and use of the model with a real
image data set.
Abstract: In Orthogonal Frequency Division Multiplexing (OFDM) systems, the peak to average power ratio (PAR) is much high. The clipping signal scheme is a useful method to reduce PAR. Clipping the OFDM signal, however, increases the overall noise level by introducing clipping noise. It is necessary to recover the figure of the original signal at receiver in order to reduce the clipping noise. Considering the continuity of the signal and the figure of the peak, we obtain a certain conic function curve to replace the clipped signal module within the clipping time. The results of simulation show that the proposed scheme can reduce the systems? BER (bit-error rate) 10 times when signal-to-interference-and noise-ratio (SINR) equals to 12dB. And the BER performance of the proposed scheme is superior to that of kim's scheme, too.
Abstract: Dynamic shear test on simulated phantom can be used
to validate magnetic resonance elastography (MRE) measurements.
Phantom gel has been usually utilized for the cell culture of cartilage
and soft tissue and also been used for mechanical property
characterization using imaging systems. The viscoelastic property of
the phantom would be important for dynamic experiments and
analyses. In this study, An axisymmetric FE model is presented for
determining the dynamic shear behaviour of brain simulated phantom
using ABAQUS. The main objective of this study was to investigate
the effect of excitation frequencies and boundary conditions on shear
modulus and shear viscosity in viscoelastic media.
Abstract: One of the most important aspects expected from an
ERP system is to mange user\administrator manual documents
dynamically. Since an ERP package is frequently changed during its
implementation in customer sites, it is often needed to add new
documents and/or apply required changes to existing documents in
order to cover new or changed capabilities. The worse is that since
these changes occur continuously, the corresponding documents
should be updated dynamically; otherwise, implementing the ERP
package in the organization encounters serious risks. In this paper, we
propose a new architecture which is based on the agent oriented
vision and supplies the dynamic document generation expected from
ERP systems using several independent but cooperative agents.
Beside the dynamic document generation which is the main issue of
this paper, the presented architecture will address some aspects of
intelligence and learning capabilities existing in ERP.
Abstract: The cycles of the steam-injection gas-turbine systems are studied. The analyses of the parametric effects and the optimal operating conditions for the steam-injection gas-turbine (STIG) system and the regenerative steam-injection gas-turbine (RSTIG) system are investigated to ensure the maximum performance. Using the analytic model, the performance parameters of the system such as thermal efficiency, fuel consumption and specific power, and also the optimal operating conditions are evaluated in terms of pressure ratio, steam injection ratio, ambient temperature and turbine inlet temperature (TIT). It is shown that the computational results are presented to have a notable enhancement of thermal efficiency and specific power.
Abstract: Ultra-wide band (UWB) communication is one of
the most promising technologies for high data rate wireless networks
for short range applications. This paper proposes a blind channel
estimation method namely IMM (Interactive Multiple Model) Based
Kalman algorithm for UWB OFDM systems. IMM based Kalman
filter is proposed to estimate frequency selective time varying
channel. In the proposed method, two Kalman filters are concurrently
estimate the channel parameters. The first Kalman filter namely
Static Model Filter (SMF) gives accurate result when the user is static
while the second Kalman filter namely the Dynamic Model Filter
(DMF) gives accurate result when the receiver is in moving state. The
static transition matrix in SMF is assumed as an Identity matrix
where as in DMF, it is computed using Yule-Walker equations. The
resultant filter estimate is computed as a weighted sum of individual
filter estimates. The proposed method is compared with other existing
channel estimation methods.
Abstract: The evaluation of the question answering system is a major research area that needs much attention. Before the rise of domain-oriented question answering systems based on natural language understanding and reasoning, evaluation is never a problem as information retrieval-based metrics are readily available for use. However, when question answering systems began to be more domains specific, evaluation becomes a real issue. This is especially true when understanding and reasoning is required to cater for a wider variety of questions and at the same time achieve higher quality responses The research in this paper discusses the inappropriateness of the existing measure for response quality evaluation and in a later part, the call for new standard measures and the related considerations are brought forward. As a short-term solution for evaluating response quality of heterogeneous systems, and to demonstrate the challenges in evaluating systems of different nature, this research presents a black-box approach using observation, classification scheme and a scoring mechanism to assess and rank three example systems (i.e. AnswerBus, START and NaLURI).
Abstract: This paper proposes a novel spectrum sensing technique
for the digital video broadcasting-terrestrial (DVB-T) systems, which
utilizes the periodicity of pilot signals in the orthogonal frequency
division multiplexing (OFDM) symbols. The proposed scheme can
overcome the effect of the timing synchronization error by recorrelating
the correlation values in the same sample distances. The
numerical results demonstrate that the detection probability performance
of the proposed scheme outperforms that of the conventional
scheme when there exists a timing synchronization error.
Abstract: Image compression is one of the most important
applications Digital Image Processing. Advanced medical imaging
requires storage of large quantities of digitized clinical data. Due to
the constrained bandwidth and storage capacity, however, a medical
image must be compressed before transmission and storage. There
are two types of compression methods, lossless and lossy. In Lossless
compression method the original image is retrieved without any
distortion. In lossy compression method, the reconstructed images
contain some distortion. Direct Cosine Transform (DCT) and Fractal
Image Compression (FIC) are types of lossy compression methods.
This work shows that lossy compression methods can be chosen for
medical image compression without significant degradation of the
image quality. In this work DCT and Fractal Compression using
Partitioned Iterated Function Systems (PIFS) are applied on different
modalities of images like CT Scan, Ultrasound, Angiogram, X-ray
and mammogram. Approximately 20 images are considered in each
modality and the average values of compression ratio and Peak
Signal to Noise Ratio (PSNR) are computed and studied. The quality
of the reconstructed image is arrived by the PSNR values. Based on
the results it can be concluded that the DCT has higher PSNR values
and FIC has higher compression ratio. Hence in medical image
compression, DCT can be used wherever picture quality is preferred
and FIC is used wherever compression of images for storage and
transmission is the priority, without loosing picture quality
diagnostically.
Abstract: In this era of technology, fueled by the pervasive usage of the internet, security is a prime concern. The number of new attacks by the so-called “bots", which are automated programs, is increasing at an alarming rate. They are most likely to attack online registration systems. Technology, called “CAPTCHA" (Completely Automated Public Turing test to tell Computers and Humans Apart) do exist, which can differentiate between automated programs and humans and prevent replay attacks. Traditionally CAPTCHA-s have been implemented with the challenge involved in recognizing textual images and reproducing the same. We propose an approach where the visual challenge has to be read out from which randomly selected keywords are used to verify the correctness of spoken text and in turn detect the presence of human. This is supplemented with a speaker recognition system which can identify the speaker also. Thus, this framework fulfills both the objectives – it can determine whether the user is a human or not and if it is a human, it can verify its identity.