Abstract: The standard approach to image reconstruction is to stabilize the problem by including an edge-preserving roughness penalty in addition to faithfulness to the data. However, this methodology produces noisy object boundaries and creates a staircase effect. The existing attempts to favor the formation of smooth contour lines take the edge field explicitly into account; they either are computationally expensive or produce disappointing results. In this paper, we propose to incorporate the smoothness of the edge field in an implicit way by means of an additional penalty term defined in the wavelet domain. We also derive an efficient half-quadratic algorithm to solve the resulting optimization problem, including the case when the data fidelity term is non-quadratic and the cost function is nonconvex. Numerical experiments show that our technique preserves edge sharpness while smoothing contour lines; it produces visually pleasing reconstructions which are quantitatively better than those obtained without wavelet-domain constraints.
Abstract: Software crisis refers to the situation in which the developers are not able to complete the projects within time and budget constraints and moreover these overscheduled and over budget projects are of low quality as well. Several methodologies have been adopted form time to time to overcome this situation and now in the focus is component based software engineering. In this approach, emphasis is on reuse of already existing software artifacts. But the results can not be achieved just by preaching the principles; they need to be practiced as well. This paper highlights some of the very basic elements of this approach, which has to be in place to get the desired goals of high quality, low cost with shorter time-to-market software products.
Abstract: Transmission network expansion planning (TNEP) is a basic part of power system planning that determines where, when and how many new transmission lines should be added to the network. Up till now, various methods have been presented to solve the static transmission network expansion planning (STNEP) problem. But in all of these methods, lines adequacy rate has not been considered at the end of planning horizon, i.e., expanded network misses adequacy after some times and needs to be expanded again. In this paper, expansion planning has been implemented by merging lines loading parameter in the STNEP and inserting investment cost into the fitness function constraints using genetic algorithm. Expanded network will possess a maximum adequacy to provide load demand and also the transmission lines overloaded later. Finally, adequacy index could be defined and used to compare some designs that have different investment costs and adequacy rates. In this paper, the proposed idea has been tested on the Garvers network. The results show that the network will possess maximum efficiency economically.
Abstract: This study discusses the effect of uncertainty on
production levels of a petrochemical complex. Uncertainly or
variations in some model parameters, such as prices, supply and
demand of materials, can affect the optimality or the efficiency of any
chemical process. For any petrochemical complex with many plants,
there are many sources of uncertainty and frequent variations which
require more attention. Many optimization approaches are proposed
in the literature to incorporate uncertainty within the model in order
to obtain a robust solution. In this work, a stability analysis approach
is applied to a deterministic LP model of a petrochemical complex
consists of ten plants to investigate the effect of such variations on
the obtained optimal production levels. The proposed approach can
determinate the allowable variation ranges of some parameters,
mainly objective or RHS coefficients, before the system lose its
optimality. Parameters with relatively narrow range of variations, i.e.
stability limits, are classified as sensitive parameters or constraints
that need accurate estimate or intensive monitoring. These stability
limits offer easy-to-use information to the decision maker and help in
understanding the interaction between some model parameters and
deciding when the system need to be re-optimize. The study shows
that maximum production of ethylene and the prices of intermediate
products are the most sensitive factors that affect the stability of the
optimum solution
Abstract: Databases have become ubiquitous. Almost all IT applications are storing into and retrieving information from databases. Retrieving information from the database requires knowledge of technical languages such as Structured Query Language (SQL). However majority of the users who interact with the databases do not have a technical background and are intimidated by the idea of using languages such as SQL. This has led to the development of a few Natural Language Database Interfaces (NLDBIs). A NLDBI allows the user to query the database in a natural language. This paper highlights on architecture of new NLDBI system, its implementation and discusses on results obtained. In most of the typical NLDBI systems the natural language statement is converted into an internal representation based on the syntactic and semantic knowledge of the natural language. This representation is then converted into queries using a representation converter. A natural language query is translated to an equivalent SQL query after processing through various stages. The work has been experimented on primitive database queries with certain constraints.
Abstract: In present communication, we have developed the
suitable constraints for the given the mean codeword length and the
measures of entropy. This development has proved that Renyi-s
entropy gives the minimum value of the log of the harmonic mean
and the log of power mean. We have also developed an important
relation between best 1:1 code and the uniquely decipherable code by
using different measures of entropy.
Abstract: Due to the deregulation of the Electric Supply
Industry and the resulting emergence of electricity market, the
volumes of power purchases are on the rise all over the world. In a
bid to meet the customer-s demand in a reliable and yet economic
manner, utilities purchase power from the energy market over and
above its own production. This paper aims at developing an optimal
power purchase model with two objectives viz economy and
environment ,taking various functional operating constraints such as
branch flow limits, load bus voltage magnitudes limits, unit capacity
constraints and security constraints into consideration.The price of
purchased power being an uncertain variable is modeled using fuzzy
logic. DEMO (Differential Evolution For Multi-objective
Optimization) is used to obtain the pareto-optimal solution set of the
multi-objective problem formulated. Fuzzy set theory has been
employed to extract the best compromise non-dominated solution.
The results obtained on IEEE 30 bus system are presented and
compared with that of NSGAII.
Abstract: This paper presents a heuristic to solve large size 0-1 Multi constrained Knapsack problem (01MKP) which is NP-hard. Many researchers are used heuristic operator to identify the redundant constraints of Linear Programming Problem before applying the regular procedure to solve it. We use the intercept matrix to identify the zero valued variables of 01MKP which is known as redundant variables. In this heuristic, first the dominance property of the intercept matrix of constraints is exploited to reduce the search space to find the optimal or near optimal solutions of 01MKP, second, we improve the solution by using the pseudo-utility ratio based on surrogate constraint of 01MKP. This heuristic is tested for benchmark problems of sizes upto 2500, taken from literature and the results are compared with optimum solutions. Space and computational complexity of solving 01MKP using this approach are also presented. The encouraging results especially for relatively large size test problems indicate that this heuristic can successfully be used for finding good solutions for highly constrained NP-hard problems.
Abstract: Seismic design may require non-conventional
concept, due to the fact that the stiffness and layout of the structure
have a great effect on the overall structural behaviour, on the seismic
load intensity as well as on the internal force distribution. To find an
economical and optimal structural configuration the key issue is the
optimal design of the lateral load resisting system. This paper focuses
on the optimal design of regular, concentric braced frame (CBF)
multi-storey steel building structures. The optimal configurations are
determined by a numerical method using genetic algorithm approach,
developed by the authors. Aim is to find structural configurations
with minimum structural cost. The design constraints of objective
function are assigned in accordance with Eurocode 3 and Eurocode 8
guidelines. In this paper the results are presented for various building
geometries, different seismic intensities, and levels of energy
dissipation.
Abstract: Recently, a great amount of interest has been shown
in the field of modeling and controlling hybrid systems. One of the
efficient and common methods in this area utilizes the mixed logicaldynamical
(MLD) systems in the modeling. In this method, the
system constraints are transformed into mixed-integer inequalities by
defining some logic statements. In this paper, a system containing
three tanks is modeled as a nonlinear switched system by using the
MLD framework. Comparing the model size of the three-tank system
with that of a two-tank system, it is deduced that the number of
binary variables, the size of the system and its complexity
tremendously increases with the number of tanks, which makes the
control of the system more difficult. Therefore, methods should be
found which result in fewer mixed-integer inequalities.
Abstract: In this study, we propose a network architecture for
providing secure access to information resources of enterprise
network from remote locations in a wireless fashion. Our proposed
architecture offers a very promising solution for organizations which
are in need of a secure, flexible and cost-effective remote access
methodology. Security of the proposed architecture is based on
Virtual Private Network technology and a special role based access
control mechanism with location and time constraints. The flexibility
mainly comes from the use of Internet as the communication medium
and cost-effectiveness is due to the possibility of in-house
implementation of the proposed architecture.
Abstract: The ability of UML to handle the modeling process of complex industrial software applications has increased its popularity to the extent of becoming the de-facto language in serving the design purpose. Although, its rich graphical notation naturally oriented towards the object-oriented concept, facilitates the understandability, it hardly successes to report all domainspecific aspects in a satisfactory way. OCL, as the standard language for expressing additional constraints on UML models, has great potential to help improve expressiveness. Unfortunately, it suffers from a weak formalism due to its poor semantic resulting in many obstacles towards the build of tools support and thus its application in the industry field. For this reason, many researches were established to formalize OCL expressions using a more rigorous approach. Our contribution join this work in a complementary way since it focuses specifically on OCL predefined properties which constitute an important part in the construction of OCL expressions. Using formal methods, we mainly succeed in expressing rigorously OCL predefined functions.
Abstract: As the gradual increase of the enterprise scale, the
firms may possess many manufacturing plants located in different
places geographically. This change will result in the multi-site
production planning problems under the environment of multiple
plants or production resources. Our research proposes the structural
framework to analyze the multi-site planning problems. The analytical
framework is composed of six elements: multi-site conceptual model,
product structure (bill of manufacturing), production strategy,
manufacturing capability and characteristics, production planning
constraints, and key performance indicators. As well as the discussion
of these six ingredients, we also review related literatures in this paper
to match our analytical framework. Finally we take a real-world
practical example of a TFT-LCD manufacturer in Taiwan to explain
our proposed analytical framework for the multi-site production
planning problems.
Abstract: The study of a real function of two real variables can be supported by visualization using a Computer Algebra System (CAS). One type of constraints of the system is due to the algorithms implemented, yielding continuous approximations of the given function by interpolation. This often masks discontinuities of the function and can provide strange plots, not compatible with the mathematics. In recent years, point based geometry has gained increasing attention as an alternative surface representation, both for efficient rendering and for flexible geometry processing of complex surfaces. In this paper we present different artifacts created by mesh surfaces near discontinuities and propose a point based method that controls and reduces these artifacts. A least squares penalty method for an automatic generation of the mesh that controls the behavior of the chosen function is presented. The special feature of this method is the ability to improve the accuracy of the surface visualization near a set of interior points where the function may be discontinuous. The present method is formulated as a minimax problem and the non uniform mesh is generated using an iterative algorithm. Results show that for large poorly conditioned matrices, the new algorithm gives more accurate results than the classical preconditioned conjugate algorithm.
Abstract: All practical real-time scheduling algorithms in multiprocessor systems present a trade-off between their computational complexity and performance. In real-time systems, tasks have to be performed correctly and timely. Finding minimal schedule in multiprocessor systems with real-time constraints is shown to be NP-hard. Although some optimal algorithms have been employed in uni-processor systems, they fail when they are applied in multiprocessor systems. The practical scheduling algorithms in real-time systems have not deterministic response time. Deterministic timing behavior is an important parameter for system robustness analysis. The intrinsic uncertainty in dynamic real-time systems increases the difficulties of scheduling problem. To alleviate these difficulties, we have proposed a fuzzy scheduling approach to arrange real-time periodic and non-periodic tasks in multiprocessor systems. Static and dynamic optimal scheduling algorithms fail with non-critical overload. In contrast, our approach balances task loads of the processors successfully while consider starvation prevention and fairness which cause higher priority tasks have higher running probability. A simulation is conducted to evaluate the performance of the proposed approach. Experimental results have shown that the proposed fuzzy scheduler creates feasible schedules for homogeneous and heterogeneous tasks. It also and considers tasks priorities which cause higher system utilization and lowers deadline miss time. According to the results, it performs very close to optimal schedule of uni-processor systems.
Abstract: In this paper, a particle swarm optimization (PSO)
algorithm is proposed to solve machine loading problem in flexible
manufacturing system (FMS), with bicriterion objectives of
minimizing system unbalance and maximizing system throughput in
the occurrence of technological constraints such as available
machining time and tool slots. A mathematical model is used to
select machines, assign operations and the required tools. The
performance of the PSO is tested by using 10 sample dataset and the
results are compared with the heuristics reported in the literature. The
results support that the proposed PSO is comparable with the
algorithms reported in the literature.
Abstract: This paper is concerned with the application of small
rating Capacitive Energy Storage units for the improvement of
Automatic Generation Control of a multiunit multiarea power
system. Generation Rate Constraints are also considered in the
investigations. Integral Squared Error technique is used to obtain the
optimal integral gain settings by minimizing a quadratic performance
index. Simulation studies reveal that with CES units, the deviations
in area frequencies and inter-area tie-power are considerably
improved in terms of peak deviations and settling time as compared
to that obtained without CES units.
Abstract: E-Appointment Scheduling (EAS) has been developed
to handle appointment for UMP students, lecturers in Faculty of
Computer Systems & Software Engineering (FCSSE) and Student
Medical Center. The schedules are based on the timetable and
university activities. Constraints Logic Programming (CLP) has been
implemented to solve the scheduling problems by giving
recommendation to the users in part of determining any available
slots from the lecturers and doctors- timetable. By using this system,
we can avoid wasting time and cost because this application will set
an appointment by auto-generated. In addition, this system can be an
alternative to the lecturers and doctors to make decisions whether to
approve or reject the appointments.
Abstract: Nature conducts its action in a very private manner. To
reveal these actions classical science has done a great effort. But
classical science can experiment only with the things that can be seen
with eyes. Beyond the scope of classical science quantum science
works very well. It is based on some postulates like qubit,
superposition of two states, entanglement, measurement and
evolution of states that are briefly described in the present paper.
One of the applications of quantum computing i.e.
implementation of a novel quantum evolutionary algorithm(QEA) to
automate the time tabling problem of Dayalbagh Educational Institute
(Deemed University) is also presented in this paper. Making a good
timetable is a scheduling problem. It is NP-hard, multi-constrained,
complex and a combinatorial optimization problem. The solution of
this problem cannot be obtained in polynomial time. The QEA uses
genetic operators on the Q-bit as well as updating operator of
quantum gate which is introduced as a variation operator to converge
toward better solutions.
Abstract: Motion estimation is the most computationally
intensive part in video processing. Many fast motion estimation
algorithms have been proposed to decrease the computational
complexity by reducing the number of candidate motion vectors.
However, these studies are for fast search algorithms themselves while
almost image and video compressions are operated with software
based. Therefore, the timing constraints for running these motion
estimation algorithms not only challenge for the video codec but also
overwhelm for some of processors. In this paper, the performance of
motion estimation is enhanced by using Intel's Streaming SIMD
Extension 2 (SSE2) technology with Intel Pentium 4 processor.