Abstract: In this paper, we introduce an mobile agent framework
with proactive load balancing for ambient intelligence (AmI) environments.
One of the main obstacles of AmI is the scalability in
which the openness of AmI environment introduces dynamic resource
requirements on agencies. To mediate this scalability problem, our
framework proposes a load balancing module to proactively analyze
the resource consumption of network bandwidth and preferred agencies
to suggest the optimal communication method to its user. The
framework generally formulates an AmI environment that consists
of three main components: (1) mobile devices, (2) hosts or agencies,
and (3) directory service center (DSC). A preliminary implementation
was conducted with NetLogo and the experimental results show that
the proposed approach provides enhanced system performance by
minimizing the network utilization to provide users with responsive
services.
Abstract: Reducing energy consumption of embedded systems requires careful memory management. It has been shown that Scratch- Pad Memories (SPMs) are low size, low cost, efficient (i.e. energy saving) data structures directly managed at the software level. In this paper, the focus is on heuristic methods for SPMs management. A method is efficient if the number of accesses to SPM is as large as possible and if all available space (i.e. bits) is used. A Tabu Search (TS) approach for memory management is proposed which is, to the best of our knowledge, a new original alternative to the best known existing heuristic (BEH). In fact, experimentations performed on benchmarks show that the Tabu Search method is as efficient as BEH (in terms of energy consumption) but BEH requires a sorting which can be computationally expensive for a large amount of data. TS is easy to implement and since no sorting is necessary, unlike BEH, the corresponding sorting time is saved. In addition to that, in a dynamic perspective where the maximum capacity of the SPM is not known in advance, the TS heuristic will perform better than BEH.
Abstract: In this paper the Huang-s method for solving a m×n fuzzy linear system when, m≤ n, is considered. The method in detail is discussed and illustrated by solving some numerical examples.
Abstract: This article demonstrated development of
controlled release system of an NSAID drug, Diclofenac
sodium employing different ratios of Ethyl cellulose.
Diclofenac sodium and ethyl cellulose in different proportions
were processed by microencapsulation based on phase
separation technique to formulate microcapsules. The
prepared microcapsules were then compressed into tablets to
obtain controlled release oral formulations. In-vitro evaluation
was performed by dissolution test of each preparation was
conducted in 900 ml of phosphate buffer solution of pH 7.2
maintained at 37 ± 0.5 °C and stirred at 50 rpm. At predetermined
time intervals (0, 0.5, 1.0, 1.5, 2, 3, 4, 6, 8, 10, 12,
16, 20 and 24 hrs). The drug concentration in the collected
samples was determined by UV spectrophotometer at 276 nm.
The physical characteristics of diclofenac sodium
microcapsules were according to accepted range. These were
off-white, free flowing and spherical in shape. The release
profile of diclofenac sodium from microcapsules was found to
be directly proportional to the proportion of ethylcellulose and
coat thickness. The in-vitro release pattern showed that with
ratio of 1:1 and 1:2 (drug: polymer), the percentage release of
drug at first hour was 16.91 and 11.52 %, respectively as
compared to 1:3 which is only 6.87 % with in this time. The
release mechanism followed higuchi model for its release
pattern. Tablet Formulation (F2) of present study was found
comparable in release profile the marketed brand Phlogin-SR,
microcapsules showed an extended release beyond 24 h.
Further, a good correlation was found between drug release
and proportion of ethylcellulose in the microcapsules.
Microencapsulation based on coacervation found as good
technique to control release of diclofenac sodium for making
the controlled release formulations.
Abstract: This paper considers the robust exponential stability issues for a class of uncertain switched neutral system which delays switched according to the switching rule. The system under consideration includes both stable and unstable subsystems. The uncertainties considered in this paper are norm bounded, and possibly time varying. Based on multiple Lyapunov functional approach and dwell-time technique, the time-dependent switching rule is designed depend on the so-called average dwell time of stable subsystems as well as the ratio of the total activation time of stable subsystems and unstable subsystems. It is shown that by suitably controlling the switching between the stable and unstable modes, the robust stabilization of the switched uncertain neutral systems can be achieved. Two simulation examples are given to demonstrate the effectiveness of the proposed method.
Abstract: This paper deals with modeling and parameter
identification of nonlinear systems described by Hammerstein model
having Piecewise nonlinear characteristics such as Dead-zone
nonlinearity characteristic. The simultaneous use of both an easy
decomposition technique and the triangular basis functions leads to a
particular form of Hammerstein model. The approximation by using
Triangular basis functions for the description of the static nonlinear
block conducts to a linear regressor model, so that least squares
techniques can be used for the parameter estimation. Singular Values
Decomposition (SVD) technique has been applied to separate the
coupled parameters. The proposed approach has been efficiently
tested on academic examples of simulation.
Abstract: In any trust model, the two information sources that a peer relies on to predict trustworthiness of another peer are direct experience as well as reputation. These two vital components evolve over time. Trust evolution is an important issue, where the objective is to observe a sequence of past values of a trust parameter and determine the future estimates. Unfortunately, trust evolution algorithms received little attention and the proposed algorithms in the literature do not comply with the conditions and the nature of trust. This paper contributes to this important problem in the following ways: (a) presents an algorithm that manages and models trust evolution in a P2P environment, (b) devises new mechanisms for effectively maintaining trust values based on the conditions that influence trust evolution , and (c) introduces a new methodology for incorporating trust-nurture incentives into the trust evolution algorithm. Simulation experiments are carried out to evaluate our trust evolution algorithm.
Abstract: In the highly competitive and rapidly changing global
marketplace, independent organizations and enterprises often come
together and form a temporary alignment of virtual enterprise in a
supply chain to better provide products or service. As firms adopt the
systems approach implicit in supply chain management, they must
manage the quality from both internal process control and external
control of supplier quality and customer requirements. How to
incorporate quality management of upstream and downstream supply
chain partners into their own quality management system has recently
received a great deal of attention from both academic and practice.
This paper investigate the collaborative feature and the entities-
relationship in a supply chain, and presents an ontology of
collaborative supply chain from an approach of aligning
service-oriented framework with service-dominant logic. This
perspective facilitates the segregation of material flow management
from manufacturing capability management, which provides a
foundation for the coordination and integration of the business process
to measure, analyze, and continually improve the quality of products,
services, and process. Further, this approach characterizes the different
interests of supply chain partners, providing an innovative approach to
analyze the collaborative features of supply chain. Furthermore, this
ontology is the foundation to develop quality management system
which internalizes the quality management in upstream and
downstream supply chain partners and manages the quality in supply
chain systematically.
Abstract: Over the years, there is a growing trend towards
quality-based specifications in highway construction. In many
Quality Control/Quality Assurance (QC/QA) specifications, the
contractor is primarily responsible for quality control of the process,
whereas the highway agency is responsible for testing the acceptance
of the product. A cooperative investigation was conducted in Illinois
over several years to develop a prototype End-Result Specification
(ERS) for asphalt pavement construction. The final characteristics of
the product are stipulated in the ERS and the contractor is given
considerable freedom in achieving those characteristics. The risk for
the contractor or agency depends on how the acceptance limits and
processes are specified. Stochastic simulation models are very useful
in estimating and analyzing payment risk in ERS systems and these
form an integral part of the Illinois-s prototype ERS system. This
paper describes the development of an innovative methodology to
estimate the variability components in in-situ density, air voids and
asphalt content data from ERS projects. The information gained from
this would be crucial in simulating these ERS projects for estimation
and analysis of payment risks associated with asphalt pavement
construction. However, these methods require at least two parties to
conduct tests on all the split samples obtained according to the
sampling scheme prescribed in present ERS implemented in Illinois.
Abstract: A key element of many distribution systems is the
routing and scheduling of vehicles servicing a set of customers. A
wide variety of exact and approximate algorithms have been
proposed for solving the vehicle routing problems (VRP). Exact
algorithms can only solve relatively small problems of VRP, which is
classified as NP-Hard. Several approximate algorithms have proven
successful in finding a feasible solution not necessarily optimum.
Although different parts of the problem are stochastic in nature; yet,
limited work relevant to the application of discrete event system
simulation has addressed the problem. Presented here is optimization
using simulation of VRP; where, a simplified problem has been
developed in the ExtendSimTM simulation environment; where,
ExtendSimTM evolutionary optimizer is used to minimize the total
transportation cost of the problem. Results obtained from the model
are very satisfactory. Further complexities of the problem are
proposed for consideration in the future.
Abstract: This paper presents a simple method for estimation of
additional load as a factor of the existing load that may be drawn
before reaching the point of line maximum loadability of radial
distribution system (RDS) with different realistic load models at
different substation voltages. The proposed method involves a simple
line loadability index (LLI) that gives a measure of the proximity of
the present state of a line in the distribution system. The LLI can use
to assess voltage instability and the line loading margin. The
proposed method also compares with the existing method of
maximum loadability index [10]. The simulation results show that the
LLI can identify not only the weakest line/branch causing system
instability but also the system voltage collapse point when it is near
one. This feature enables us to set an index threshold to monitor and
predict system stability on-line so that a proper action can be taken to
prevent the system from collapse. To demonstrate the validity of the
proposed algorithm, computer simulations are carried out on two bus
and 69 bus RDS.
Abstract: Speech enhancement is the process of eliminating
noise and increasing the quality of a speech signal, which is
contaminated with other kinds of distortions. This paper is on
developing an optimum cascaded system for speech enhancement.
This aim is attained without diminishing any relevant speech
information and without much computational and time complexity.
LMS algorithm, Spectral Subtraction and Kalman filter have been
deployed as the main de-noising algorithms in this work. Since these
algorithms suffer from respective shortcomings, this work has been
undertaken to design cascaded systems in different combinations and
the evaluation of such cascades by qualitative (listening) and
quantitative (SNR) tests.
Abstract: Most of the Question Answering systems
composed of three main modules: question processing,
document processing and answer processing. Question
processing module plays an important role in QA systems. If
this module doesn't work properly, it will make problems for
other sections. Moreover answer processing module is an
emerging topic in Question Answering, where these systems
are often required to rank and validate candidate answers.
These techniques aiming at finding short and precise answers
are often based on the semantic classification.
This paper discussed about a new model for question
answering which improved two main modules, question
processing and answer processing.
There are two important components which are the bases
of the question processing. First component is question
classification that specifies types of question and answer.
Second one is reformulation which converts the user's
question into an understandable question by QA system in a
specific domain. Answer processing module, consists of
candidate answer filtering, candidate answer ordering
components and also it has a validation section for interacting
with user. This module makes it more suitable to find exact
answer. In this paper we have described question and answer
processing modules with modeling, implementing and
evaluating the system. System implemented in two versions.
Results show that 'Version No.1' gave correct answer to 70%
of questions (30 correct answers to 50 asked questions) and
'version No.2' gave correct answers to 94% of questions (47
correct answers to 50 asked questions).
Abstract: In this paper, we propose a new method to describe fractal shapes using parametric l-systems. First we introduce scaling factors in the production rules of the parametric l-systems grammars. Then we decorticate these grammars with scaling factors using turtle algebra to show the mathematical relation between l-systems and iterated function systems (IFS). We demonstrate that with specific values of the scaling factors, we find the exact relationship established by Prusinkiewicz and Hammel between l-systems and IFS.
Abstract: International trade involves both large and small firms
engaged in business overseas. Possible drivers that force companies
to enter international markets include increasing competition at the
domestic market, maturing domestic markets, and limited domestic
market opportunities. Technology is an important driving factor in
shaping international marketing strategy as well as in driving force
towards a more global marketplace, especially technology in
communication. It includes telephones, the internet, computer
systems and e-mail. There are three main marketing strategy choices,
namely standardization approach, adaptation approach and middleof-
the-road approach that companies implement to overseas markets.
The decision depends on situations and factors facing the companies
in the international markets. In this paper, the contingency concept is
considered that no single strategy can be effective in all contexts.
The effect of strategy on performance depends on specific situational
variables. Strategic fit is employed to investigate export marketing
strategy adaptation under certain environmental conditions, which in
turn can lead to superior performance.
Abstract: The paper describes a knowledge based system for
analysis of microscopic wear particles. Wear particles contained in
lubricating oil carry important information concerning machine
condition, in particular the state of wear. Experts (Tribologists) in the
field extract this information to monitor the operation of the machine
and ensure safety, efficiency, quality, productivity, and economy of
operation. This procedure is not always objective and it can also be
expensive. The aim is to classify these particles according to their
morphological attributes of size, shape, edge detail, thickness ratio,
color, and texture, and by using this classification thereby predict
wear failure modes in engines and other machinery. The attribute
knowledge links human expertise to the devised Knowledge Based
Wear Particle Analysis System (KBWPAS). The system provides an
automated and systematic approach to wear particle identification
which is linked directly to wear processes and modes that occur in
machinery. This brings consistency in wear judgment prediction
which leads to standardization and also less dependence on
Tribologists.
Abstract: In neural networks, when new patterns are learned by a network, the new information radically interferes with previously stored patterns. This drawback is called catastrophic forgetting or catastrophic interference. In this paper, we propose a biologically inspired neural network model which overcomes this problem. The proposed model consists of two distinct networks: one is a Hopfield type of chaotic associative memory and the other is a multilayer neural network. We consider that these networks correspond to the hippocampus and the neocortex of the brain, respectively. Information given is firstly stored in the hippocampal network with fast learning algorithm. Then the stored information is recalled by chaotic behavior of each neuron in the hippocampal network. Finally, it is consolidated in the neocortical network by using pseudopatterns. Computer simulation results show that the proposed model has much better ability to avoid catastrophic forgetting in comparison with conventional models.
Abstract: A SCADA (Supervisory Control And Data
Acquisition) system is an industrial control and monitoring system for
national infrastructures. The SCADA systems were used in a closed
environment without considering about security functionality in the
past. As communication technology develops, they try to connect the
SCADA systems to an open network. Therefore, the security of the
SCADA systems has been an issue. The study of key management for
SCADA system also has been performed. However, existing key
management schemes for SCADA system such as SKE(Key
establishment for SCADA systems) and SKMA(Key management
scheme for SCADA systems) cannot support broadcasting
communication. To solve this problem, an Advanced Key
Management Architecture for Secure SCADA Communication has
been proposed by Choi et al.. Choi et al.-s scheme also has a problem
that it requires lots of computational cost for multicasting
communication. In this paper, we propose an enhanced scheme which
improving computational cost for multicasting communication with
considering the number of keys to be stored in a low power
communication device (RTU).
Abstract: We proposed a new class of asymmetric turbo encoder for 3G systems that performs well in both “water fall" and “error floor" regions in [7]. In this paper, a modified (optimal) power allocation scheme for the different bits of new class of asymmetric turbo encoder has been investigated to enhance the performance. The simulation results and performance bound for proposed asymmetric turbo code with modified Unequal Power Allocation (UPA) scheme for the frame length, N=400, code rate, r=1/3 with Log-MAP decoder over Additive White Gaussian Noise (AWGN) channel are obtained and compared with the system with typical UPA and without UPA. The performance tests are extended over AWGN channel for different frame size to verify the possibility of implementation of the modified UPA scheme for the proposed asymmetric turbo code. From the performance results, it is observed that the proposed asymmetric turbo code with modified UPA performs better than the system without UPA and with typical UPA and it provides a coding gain of 0.4 to 0.52dB.
Abstract: In analyzing large scale nonlinear dynamical systems,
it is often desirable to treat the overall system as a collection of
interconnected subsystems. Solutions properties of the large scale
system are then deduced from the solution properties of the
individual subsystems and the nature of the interconnections. In this
paper a new approach is proposed for the stability analysis of large
scale systems, which is based upon the concept of vector Lyapunov
functions and the decomposition methods. The present results make
use of graph theoretic decomposition techniques in which the overall
system is partitioned into a hierarchy of strongly connected
components. We show then, that under very reasonable assumptions,
the overall system is stable once the strongly connected subsystems
are stables. Finally an example is given to illustrate the constructive
methodology proposed.