Abstract: Language Reforms and potential use of ICTs has been a focal area of Higher Education Commission of Pakistan. Efforts are being accelerated to incorporate fast expanding ICTs to bring qualitative improvement in language instruction in higher education. This paper explores how university teachers are benefitting from ICTs to make their English class effective and what type of problems they face in practicing ICTs during their lectures. An in-depth qualitative study was employed to understand why language teachers tend to use ICTs in their instruction and how they are practicing it. A sample of twenty teachers from five universities located in Islamabad, three from public sector and two from private sector, was selected on non-random (Snowball) sampling basis. An interview with 15 semi-structured items was used as research instruments to collect data. The findings reveal that business English teaching is facilitated and improved through the use of ICTs. The language teachers need special training regarding the practices and implementation of ICTs. It is recommended that initiatives might be taken to equip university language teachers with modern methodology incorporating ICTs as focal area and efforts might be made to remove barriers regarding the training of language teachers and proper usage of ICTs.
Abstract: Intrusion detection systems (IDS)are crucial components
of the security mechanisms of today-s computer systems.
Existing research on intrusion detection has focused on sequential
intrusions. However, intrusions can also be formed by concurrent
interactions of multiple processes. Some of the intrusions caused
by these interactions cannot be detected using sequential intrusion
detection methods. Therefore, there is a need for a mechanism that
views the distributed system as a whole. L-BIDS (Lattice-Based
Intrusion Detection System) is proposed to address this problem. In
the L-BIDS framework, a library of intrusions and distributed traces
are represented as lattices. Then these lattices are compared in order
to detect intrusions in the distributed traces.
Abstract: The fast growth in complexity coupled with requests for shorter development periods for embedded systems are bringing demands towards a more effective, i.e. higher-abstract, design process for hardaware/software integrated design. In Software Engineering area, Model Driven Architecture (MDA) and Executable UML (xUML) has been accepted to bring further improvement in software design. This paper constructs MDA and xUML stepwise transformations from an abstract specification model to a more concrete implementation model using the refactoring technique for hardaware/software integrated design. This approach provides clear and structured models which enables quick exploration and synthesis, and early stage verification.
Abstract: In this paper we apply one of approaches in category of heuristic methods as Genetic Algorithms for obtaining approximate solution of optimal control problems. The firs we convert optimal control problem to a quasi Assignment Problem by defining some usual characters as defined in Genetic algorithm applications. Then we obtain approximate optimal control function as an piecewise constant function. Finally the numerical examples are given.
Abstract: this paper presents an auto-regressive network called the Auto-Regressive Multi-Context Recurrent Neural Network (ARMCRN), which forecasts the daily peak load for two large power plant systems. The auto-regressive network is a combination of both recurrent and non-recurrent networks. Weather component variables are the key elements in forecasting because any change in these variables affects the demand of energy load. So the AR-MCRN is used to learn the relationship between past, previous, and future exogenous and endogenous variables. Experimental results show that using the change in weather components and the change that occurred in past load as inputs to the AR-MCRN, rather than the basic weather parameters and past load itself as inputs to the same network, produce higher accuracy of predicted load. Experimental results also show that using exogenous and endogenous variables as inputs is better than using only the exogenous variables as inputs to the network.
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: The various types of frequent pattern discovery
problem, namely, the frequent itemset, sequence and graph mining
problems are solved in different ways which are, however, in certain
aspects similar. The main approach of discovering such patterns can
be classified into two main classes, namely, in the class of the levelwise
methods and in that of the database projection-based methods.
The level-wise algorithms use in general clever indexing structures
for discovering the patterns. In this paper a new approach is proposed
for discovering frequent sequences and tree-like patterns efficiently
that is based on the level-wise issue. Because the level-wise
algorithms spend a lot of time for the subpattern testing problem, the
new approach introduces the idea of using automaton theory to solve
this problem.
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 paper presents an algorithm of particle swarm
optimization with reduction for global optimization problems. Particle
swarm optimization is an algorithm which refers to the collective
motion such as birds or fishes, and a multi-point search algorithm
which finds a best solution using multiple particles. Particle
swarm optimization is so flexible that it can adapt to a number
of optimization problems. When an objective function has a lot of
local minimums complicatedly, the particle may fall into a local
minimum. For avoiding the local minimum, a number of particles are
initially prepared and their positions are updated by particle swarm
optimization. Particles sequentially reduce to reach a predetermined
number of them grounded in evaluation value and particle swarm
optimization continues until the termination condition is met. In order
to show the effectiveness of the proposed algorithm, we examine the
minimum by using test functions compared to existing algorithms.
Furthermore the influence of best value on the initial number of
particles for our algorithm is discussed.
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: Problem-based learning (PBL) is one of the student
centered approaches and has been considered by a number of higher
educational institutions in many parts of the world as a method of
delivery. This paper presents a creative thinking approach for
implementing Problem-based Learning in Mechanics of Structure
within a Malaysian Polytechnics environment. In the learning
process, students learn how to analyze the problem given among the
students and sharing classroom knowledge into practice. Further,
through this course-s emphasis on problem-based learning, students
acquire creative thinking skills and professional skills as they tackle
complex, interdisciplinary and real-situation problems. Once the
creative ideas are generated, there are useful additional techniques
for tender ideas that will grow into a productive concept or solution.
The combination of creative skills and technical abilities will enable
the students to be ready to “hit-the-ground-running" and produce in
industry when they graduate.
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: The Internet and the ever growing applications enable
communities to share and collaborate through common platforms.
However, this growing pattern is not witnessed yet even for elearning.
This paper is based on a doctoral research which aimed at
researching the ways students interact in an online campus and the
supports that they look for and require. Content analysis, based on the
Panchoo/Jaillet methodology, was done on four synchronous
meetings between a tutor and his ten students. The UNIV-Rct ecampus,
analogical to a physical campus, was found to be user
friendly and the students enrolled in a master-s course faced no
difficulties in using it. In addition to the environmental aspects, the
pedagogical implementation of the course has driven the students to
interact and collaborate significantly and this has contributed to
overcome the problems faced by the distance learners. This
completely online model was found to be fruitful in helping distant
learners fight their loneliness and brave their difficulties in a socioconstructivism
approach.
Abstract: This paper presents a new Hybrid Fuzzy (HF) PID type controller based on Genetic Algorithms (GA-s) for solution of the Automatic generation Control (AGC) problem in a deregulated electricity environment. In order for a fuzzy rule based control system to perform well, the fuzzy sets must be carefully designed. A major problem plaguing the effective use of this method is the difficulty of accurately constructing the membership functions, because it is a computationally expensive combinatorial optimization problem. On the other hand, GAs is a technique that emulates biological evolutionary theories to solve complex optimization problems by using directed random searches to derive a set of optimal solutions. For this reason, the membership functions are tuned automatically using a modified GA-s based on the hill climbing method. The motivation for using the modified GA-s is to reduce fuzzy system effort and take large parametric uncertainties into account. The global optimum value is guaranteed using the proposed method and the speed of the algorithm-s convergence is extremely improved, too. This newly developed control strategy combines the advantage of GA-s and fuzzy system control techniques and leads to a flexible controller with simple stricture that is easy to implement. The proposed GA based HF (GAHF) controller is tested on a threearea deregulated power system under different operating conditions and contract variations. The results of the proposed GAHF controller are compared with those of Multi Stage Fuzzy (MSF) controller, robust mixed H2/H∞ and classical PID controllers through some performance indices to illustrate its robust performance for a wide range of system parameters and load changes.