Search results for: Non-linear integer programming models
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3977

Search results for: Non-linear integer programming models

3677 Multi-Objective Cellular Manufacturing System under Machines with Different Life-Cycle using Genetic Algorithm

Authors: N. Javadian, J. Rezaeian, Y. Maali

Abstract:

In this paper a multi-objective nonlinear programming model of cellular manufacturing system is presented which minimize the intercell movements and maximize the sum of reliability of cells. We present a genetic approach for finding efficient solutions to the problem of cell formation for products having multiple routings. These methods find the non-dominated solutions and according to decision makers prefer, the best solution will be chosen.

Keywords: Cellular Manufacturing, Genetic Algorithm, Multiobjective, Life-Cycle.

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3676 An Efficient Computational Algorithm for Solving the Nonlinear Lane-Emden Type Equations

Authors: Gholamreza Hojjati, Kourosh Parand

Abstract:

In this paper we propose a class of second derivative multistep methods for solving some well-known classes of Lane- Emden type equations which are nonlinear ordinary differential equations on the semi-infinite domain. These methods, which have good stability and accuracy properties, are useful in deal with stiff ODEs. We show superiority of these methods by applying them on the some famous Lane-Emden type equations.

Keywords: Lane-Emden type equations, nonlinear ODE, stiff problems, multistep methods, astrophysics.

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3675 Prioritization Method in the Fuzzy Analytic Network Process by Fuzzy Preferences Programming Method

Authors: Tarifa S. Almulhim, Ludmil Mikhailov, Dong-Ling Xu

Abstract:

In this paper, a method for deriving a group priority vector in the Fuzzy Analytic Network Process (FANP) is proposed. By introducing importance weights of multiple decision makers (DMs) based on their experiences, the Fuzzy Preferences Programming Method (FPP) is extended to a fuzzy group prioritization problem in the FANP. Additionally, fuzzy pair-wise comparison judgments are presented rather than exact numerical assessments in order to model the uncertainty and imprecision in the DMs- judgments and then transform the fuzzy group prioritization problem into a fuzzy non-linear programming optimization problem which maximize the group satisfaction. Unlike the known fuzzy prioritization techniques, the new method proposed in this paper can easily derive crisp weights from incomplete and inconsistency fuzzy set of comparison judgments and does not require additional aggregation producers. Detailed numerical examples are used to illustrate the implement of our approach and compare with the latest fuzzy prioritization method.

Keywords: Fuzzy Analytic Network Process (FANP), Fuzzy Non-linear Programming, Fuzzy Preferences Programming Method (FPP), Multiple Criteria Decision-Making (MCDM), Triangular Fuzzy Number.

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3674 Lithium-Ion Battery State of Charge Estimation Using One State Hysteresis Model with Nonlinear Estimation Strategies

Authors: Mohammed Farag, Mina Attari, S. Andrew Gadsden, Saeid R. Habibi

Abstract:

Battery state of charge (SOC) estimation is an important parameter as it measures the total amount of electrical energy stored at a current time. The SOC percentage acts as a fuel gauge if it is compared with a conventional vehicle. Estimating the SOC is, therefore, essential for monitoring the amount of useful life remaining in the battery system. This paper looks at the implementation of three nonlinear estimation strategies for Li-Ion battery SOC estimation. One of the most common behavioral battery models is the one state hysteresis (OSH) model. The extended Kalman filter (EKF), the smooth variable structure filter (SVSF), and the time-varying smoothing boundary layer SVSF are applied on this model, and the results are compared.

Keywords: State of charge estimation, battery modeling, one-state hysteresis, filtering and estimation.

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3673 A Practical Method for Load Balancing in the LV Distribution Networks Case Study: Tabriz Electrical Network

Authors: A. Raminfard, S. M. Shahrtash

Abstract:

In this paper, a new efficient method for load balancing in low voltage distribution systems is presented. The proposed method introduces an improved Leap-frog method for optimization. The proposed objective function includes the difference between three phase currents, as well as two other terms to provide the integer property of the variables; where the latter are the status of the connection of loads to different phases. Afterwards, a new algorithm is supplemented to undertake the integer values for the load connection status. Finally, the method is applied to different parts of Tabriz low voltage network, where the results have shown the good performance of the proposed method.

Keywords: Load balancing, improved leap-frog method, optimization algorithm, low voltage distribution systems.

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3672 A Java Based Discrete Event Simulation Library

Authors: Brahim Belattar, Abdelhabib Bourouis

Abstract:

This paper describes important features of JAPROSIM, a free and open source simulation library implemented in Java programming language. It provides a framework for building discrete event simulation models. The process interaction world view adopted by JAPROSIM is discussed. We present the architecture and major components of the simulation library. A pedagogical example is given in order to illustrate how to use JAPROSIM for building discrete event simulation models. Further motivations are discussed and suggestions for improving our work are given.

Keywords: Discrete Event Simulation, Object-Oriented Simulation, JAPROSIM, Process Interaction Worldview, Java-based modeling and simulation.

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3671 An Augmented Automatic Choosing Control with Constrained Input Using Weighted Gradient Optimization Automatic Choosing Functions

Authors: Toshinori Nawata

Abstract:

In this paper we consider a nonlinear feedback control called augmented automatic choosing control (AACC) for nonlinear systems with constrained input using weighted gradient optimization automatic choosing functions. Constant term which arises from linearization of a given nonlinear system is treated as a coefficient of a stable zero dynamics. Parameters of the control are suboptimally selected by maximizing the stable region in the sense of Lyapunov with the aid of a genetic algorithm. This approach is applied to a field excitation control problem of power system to demonstrate the splendidness of the AACC. Simulation results show that the new controller can improve performance remarkably well.

Keywords: Augmented automatic choosing control, nonlinear control, genetic algorithm, zero dynamics.

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3670 Efficient Hardware Architecture of the Direct 2- D Transform for the HEVC Standard

Authors: Fatma Belghith, Hassen Loukil, Nouri Masmoudi

Abstract:

This paper presents the hardware design of a unified architecture to compute the 4x4, 8x8 and 16x16 efficient twodimensional (2-D) transform for the HEVC standard. This architecture is based on fast integer transform algorithms. It is designed only with adders and shifts in order to reduce the hardware cost significantly. The goal is to ensure the maximum circuit reuse during the computing while saving 40% for the number of operations. The architecture is developed using FIFOs to compute the second dimension. The proposed hardware was implemented in VHDL. The VHDL RTL code works at 240 MHZ in an Altera Stratix III FPGA. The number of cycles in this architecture varies from 33 in 4-point- 2D-DCT to 172 when the 16-point-2D-DCT is computed. Results show frequency improvements reaching 96% when compared to an architecture described as the direct transcription of the algorithm.

Keywords: HEVC, Modified Integer Transform, FPGA.

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3669 Supplier Selection by Bi-Objectives Mixed Integer Program Approach

Authors: K.-H. Yang

Abstract:

In the past, there was a lot of excellent research studies conducted on topics related to supplier selection. Because the considered factors of supplier selection are complicated and difficult to be quantified, most researchers deal supplier selection issues by qualitative approaches. Compared to qualitative approaches, quantitative approaches are less applicable in the real world. This study tried to apply the quantitative approach to study a supplier selection problem with considering operation cost and delivery reliability. By those factors, this study applies Normalized Normal Constraint Method to solve the dual objectives mixed integer program of the supplier selection problem.

Keywords: Bi-objectives MIP, normalized normal constraint method, supplier selection, quantitative approach.

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3668 Equations of Pulse Propagation in Three-Layer Structure of As2S3 Chalcogenide Plasmonic Nano-Waveguides

Authors: Leila Motamed-Jahromi, Mohsen Hatami, Alireza Keshavarz

Abstract:

This research aims at obtaining the equations of pulse propagation in nonlinear plasmonic waveguides created with As2S3 chalcogenide materials. Via utilizing Helmholtz equation and first-order perturbation theory, two components of electric field are determined within frequency domain. Afterwards, the equations are formulated in time domain. The obtained equations include two coupled differential equations that considers nonlinear dispersion.

Keywords: Nonlinear optics, propagation equation, plasmonic waveguide.

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3667 Application of Java-based Pointcuts in Aspect Oriented Programming (AOP) for Data Race Detection

Authors: Sadaf Khalid, Fahim Arif

Abstract:

Wide applicability of concurrent programming practices in developing various software applications leads to different concurrency errors amongst which data race is the most important. Java provides greatest support for concurrent programming by introducing various concurrency packages. Aspect oriented programming (AOP) is modern programming paradigm facilitating the runtime interception of events of interest and can be effectively used to handle the concurrency problems. AspectJ being an aspect oriented extension to java facilitates the application of concepts of AOP for data race detection. Volatile variables are usually considered thread safe, but they can become the possible candidates of data races if non-atomic operations are performed concurrently upon them. Various data race detection algorithms have been proposed in the past but this issue of volatility and atomicity is still unaddressed. The aim of this research is to propose some suggestions for incorporating certain conditions for data race detection in java programs at the volatile fields by taking into account support for atomicity in java concurrency packages and making use of pointcuts. Two simple test programs will demonstrate the results of research. The results are verified on two different Java Development Kits (JDKs) for the purpose of comparison.

Keywords: Aspect Bench Compiler (abc), Aspect OrientedProgramming (AOP), AspectJ, Aspects, Concurrency packages, Concurrent programming, Cross-cutting Concerns, Data race, Eclipse, Java, Java Development Kits (JDKs), Pointcuts

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3666 Robot Cell Planning

Authors: Allan Tubaileh, Ibrahim Hammad, Loay Al Kafafi

Abstract:

A new approach to determine the machine layout in flexible manufacturing cell, and to find the feasible robot configuration of the robot to achieve minimum cycle time is presented in this paper. The location of the input/output location and the optimal robot configuration is obtained for all sequences of work tasks of the robot within a specified period of time. A more realistic approach has been presented to model the problem using the robot joint space. The problem is formulated as a nonlinear optimization problem and solved using Sequential Quadratic Programming algorithm.

Keywords: Robotics, Layout.

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3665 An Augmented Automatic Choosing Control Designed by Extremizing a Combination of Hamiltonian and Lyapunov Functions for Nonlinear Systems with Constrained Input

Authors: Toshinori Nawata, Hitoshi Takata

Abstract:

In this paper we consider a nonlinear feedback control called augmented automatic choosing control (AACC) for nonlinear systems with constrained input. Constant terms which arise from section wise linearization of a given nonlinear system are treated as coefficients of a stable zero dynamics.Parameters included in the control are suboptimally selectedby extremizing a combination of Hamiltonian and Lyapunov functions with the aid of the genetic algorithm. This approach is applied to a field excitation control problem of power system to demonstrate the splendidness of the AACC. Simulation results show that the new controller can improve performance remarkably well.

Keywords: Augmented Automatic Choosing Control, NonlinearControl, Genetic Algorithm, Hamiltonian, Lyapunovfunction

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3664 Solving Fuzzy Multi-Objective Linear Programming Problems with Fuzzy Decision Variables

Authors: Mahnaz Hosseinzadeh, Aliyeh Kazemi

Abstract:

In this paper, a method is proposed for solving Fuzzy Multi-Objective Linear Programming problems (FMOLPP) with fuzzy right hand side and fuzzy decision variables. To illustrate the proposed method, it is applied to the problem of selecting suppliers for an automotive parts producer company in Iran in order to find the number of optimal orders allocated to each supplier considering the conflicting objectives. Finally, the obtained results are discussed.

Keywords: Fuzzy multi-objective linear programming problems, triangular fuzzy numbers, fuzzy ranking, supplier selection problem.

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3663 A Survey on the Requirements of University Course Timetabling

Authors: Nurul Liyana Abdul Aziz, Nur Aidya Hanum Aizam

Abstract:

Course timetabling problems occur every semester in a university which includes the allocation of resources (subjects, lecturers and students) to a number of fixed rooms and timeslots. The assignment is carried out in a way such that there are no conflicts within rooms, students and lecturers, as well as fulfilling a range of constraints. The constraints consist of rules and policies set up by the universities as well as lecturers’ and students’ preferences of courses to be allocated in specific timeslots. This paper specifically focuses on the preferences of the course timetabling problem in one of the public universities in Malaysia. The demands will be considered into our existing mathematical model to make it more generalized and can be used widely. We have distributed questionnaires to a number of lecturers and students of the university to investigate their demands and preferences for their desired course timetable. We classify the preferences thus converting them to construct one mathematical model that can produce such timetable.

Keywords: University course timetabling problem, integer programming, preferences, constraints.

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3662 Explicit Feedback Linearization of Magnetic Levitation System

Authors: Bhawna Tandon, Shiv Narayan, Jagdish Kumar

Abstract:

This study proposes the transformation of nonlinear Magnetic Levitation System into linear one, via state and feedback transformations using explicit algorithm. This algorithm allows computing explicitly the linearizing state coordinates and feedback for any nonlinear control system, which is feedback linearizable, without solving the Partial Differential Equations. The algorithm is performed using a maximum of N-1 steps where N being the dimension of the system.

Keywords: Explicit Algorithm, Feedback Linearization, Nonlinear control, Magnetic Levitation System.

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3661 Novel Schemes of Pilot-Aided Integer Frequency Offset Estimation for OFDM-Based DVB-T Systems

Authors: Youngyoon Lee, Dahae Chong, Myungsoo Lee, Seongho Chae, Seokho Yoon

Abstract:

This paper proposes two novel schemes for pilot-aided integer frequency offset (IFO) estimation in orthogonal frequency division multiplexing (OFDM)-based digital video broadcastingterrestrial (DVB-T) systems. The conventional scheme proposed for estimating the IFO uses only partial information of combinations that pilots can provide, which stems from a rigorous assumption that the channel responses of pilots used for estimating the IFO change very rapidly. Thus, in this paper, we propose the novel IFO estimation schemes exploiting all information of combinations that pilots can provide to improve the performance of IFO estimation. The simulation results show that the proposed schemes are highly accurate in terms of the IFO detection probability.

Keywords: OFDM, DVB-T, pilot, IFO, estimation

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3660 Applying Genetic Algorithms for Inventory Lot-Sizing Problem with Supplier Selection under Storage Space

Authors: Vichai Rungreunganaun, Chirawat Woarawichai

Abstract:

The objective of this research is to calculate the optimal inventory lot-sizing for each supplier and minimize the total inventory cost which includes joint purchase cost of the products, transaction cost for the suppliers, and holding cost for remaining inventory. Genetic algorithms (GAs) are applied to the multi-product and multi-period inventory lot-sizing problems with supplier selection under storage space. Also a maximum storage space for the decision maker in each period is considered. The decision maker needs to determine what products to order in what quantities with which suppliers in which periods. It is assumed that demand of multiple products is known over a planning horizon. The problem is formulated as a mixed integer programming and is solved with the GAs. The detailed computation results are presented.

Keywords: Genetic Algorithms, Inventory lot-sizing, Supplier selection, Storage space.

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3659 Multi-Objective Multi-Mode Resource-Constrained Project Scheduling Problem by Preemptive Fuzzy Goal Programming

Authors: Phruksaphanrat B.

Abstract:

This research proposes a preemptive fuzzy goal programming model for multi-objective multi-mode resource constrained project scheduling problem. The objectives of the problem are minimization of the total time and the total cost of the project. Objective in a multi-mode resource-constrained project scheduling problem is often a minimization of makespan. However, both time and cost should be considered at the same time with different level of important priorities. Moreover, all elements of cost functions in a project are not included in the conventional cost objective function. Incomplete total project cost causes an error in finding the project scheduling time. In this research, preemptive fuzzy goal programming is presented to solve the multi-objective multi-mode resource constrained project scheduling problem. It can find the compromise solution of the problem. Moreover, it is also flexible in adjusting to find a variety of alternative solutions. 

Keywords: Multi-mode resource constrained project scheduling problem, Fuzzy set, Goal programming, Preemptive fuzzy goal programming.

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3658 CAD Based Predictive Models of the Undeformed Chip Geometry in Drilling

Authors: Panagiotis Kyratsis, Dr. Ing. Nikolaos Bilalis, Dr. Ing. Aristomenis Antoniadis

Abstract:

Twist drills are geometrical complex tools and thus various researchers have adopted different mathematical and experimental approaches for their simulation. The present paper acknowledges the increasing use of modern CAD systems and using the API (Application Programming Interface) of a CAD system, drilling simulations are carried out. The developed DRILL3D software routine, creates parametrically controlled tool geometries and using different cutting conditions, achieves the generation of solid models for all the relevant data involved (drilling tool, cut workpiece, undeformed chip). The final data derived, consist a platform for further direct simulations regarding the determination of cutting forces, tool wear, drilling optimizations etc.

Keywords: Drilling, CAD based simulation, 3D-modelling.

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3657 A Comparison between Heuristic and Meta-Heuristic Methods for Solving the Multiple Traveling Salesman Problem

Authors: San Nah Sze, Wei King Tiong

Abstract:

The multiple traveling salesman problem (mTSP) can be used to model many practical problems. The mTSP is more complicated than the traveling salesman problem (TSP) because it requires determining which cities to assign to each salesman, as well as the optimal ordering of the cities within each salesman's tour. Previous studies proposed that Genetic Algorithm (GA), Integer Programming (IP) and several neural network (NN) approaches could be used to solve mTSP. This paper compared the results for mTSP, solved with Genetic Algorithm (GA) and Nearest Neighbor Algorithm (NNA). The number of cities is clustered into a few groups using k-means clustering technique. The number of groups depends on the number of salesman. Then, each group is solved with NNA and GA as an independent TSP. It is found that k-means clustering and NNA are superior to GA in terms of performance (evaluated by fitness function) and computing time.

Keywords: Multiple Traveling Salesman Problem, GeneticAlgorithm, Nearest Neighbor Algorithm, k-Means Clustering.

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3656 Software Tools for System Identification and Control using Neural Networks in Process Engineering

Authors: J. Fernandez de Canete, S. Gonzalez-Perez, P. del Saz-Orozco

Abstract:

Neural networks offer an alternative approach both for identification and control of nonlinear processes in process engineering. The lack of software tools for the design of controllers based on neural network models is particularly pronounced in this field. SIMULINK is properly a widely used graphical code development environment which allows system-level developers to perform rapid prototyping and testing. Such graphical based programming environment involves block-based code development and offers a more intuitive approach to modeling and control task in a great variety of engineering disciplines. In this paper a SIMULINK based Neural Tool has been developed for analysis and design of multivariable neural based control systems. This tool has been applied to the control of a high purity distillation column including non linear hydrodynamic effects. The proposed control scheme offers an optimal response for both theoretical and practical challenges posed in process control task, in particular when both, the quality improvement of distillation products and the operation efficiency in economical terms are considered.

Keywords: Distillation, neural networks, software tools, identification, control.

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3655 New Delay-dependent Stability Conditions for Neutral Systems with Nonlinear Perturbations

Authors: Lianglin Xiong, Xiuyong Ding, Shouming Zhong

Abstract:

In this paper, the problem of asymptotical stability of neutral systems with nonlinear perturbations is investigated. Based on a class of novel augment Lyapunov functionals which contain freeweighting matrices, some new delay-dependent asymptotical stability criteria are formulated in terms of linear matrix inequalities (LMIs) by using new inequality analysis technique. Numerical examples are given to demonstrate the derived condition are much less conservative than those given in the literature.

Keywords: Asymptotical stability, neutral system, nonlinear perturbation, delay-dependent, linear matrix inequality (LMI).

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3654 Numerical Study of a Class of Nonlinear Partial Differential Equations

Authors: Kholod M. Abu-Alnaja

Abstract:

In this work, we derive two numerical schemes for solving a class of nonlinear partial differential equations. The first method is of second order accuracy in space and time directions, the scheme is unconditionally stable using Von Neumann stability analysis, the scheme produced a nonlinear block system where Newton-s method is used to solve it. The second method is of fourth order accuracy in space and second order in time. The method is unconditionally stable and Newton's method is used to solve the nonlinear block system obtained. The exact single soliton solution and the conserved quantities are used to assess the accuracy and to show the robustness of the schemes. The interaction of two solitary waves for different parameters are also discussed.

Keywords: Crank-Nicolson Scheme, Douglas Scheme, Partial Differential Equations

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3653 Stability Analysis for a Multicriteria Problem with Linear Criteria and Parameterized Principle of Optimality “from Lexicographic to Slater“

Authors: Yury Nikulin

Abstract:

A multicriteria linear programming problem with integer variables and parameterized optimality principle "from lexicographic to Slater" is considered. A situation in which initial coefficients of penalty cost functions are not fixed but may be potentially a subject to variations is studied. For any efficient solution, appropriate measures of the quality are introduced which incorporate information about variations of penalty cost function coefficients. These measures correspond to the so-called stability and accuracy functions defined earlier for efficient solutions of a generic multicriteria combinatorial optimization problem with Pareto and lexicographic optimality principles. Various properties of such functions are studied and maximum norms of perturbations for which an efficient solution preserves the property of being efficient are calculated.

Keywords: Stability and accuracy, multicriteria optimization, lexicographic optimality.

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3652 Emotional Learning based Intelligent Robust Adaptive Controller for Stable Uncertain Nonlinear Systems

Authors: Ali Reza Mehrabian, Caro Lucas

Abstract:

In this paper a new control strategy based on Brain Emotional Learning (BEL) model has been introduced. A modified BEL model has been proposed to increase the degree of freedom, controlling capability, reliability and robustness, which can be implemented in real engineering systems. The performance of the proposed BEL controller has been illustrated by applying it on different nonlinear uncertain systems, showing very good adaptability and robustness, while maintaining stability.

Keywords: Learning control systems, emotional decision making, nonlinear systems, adaptive control.

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3651 Solution of Nonlinear Second-Order Pantograph Equations via Differential Transformation Method

Authors: Nemat Abazari, Reza Abazari

Abstract:

In this work, we successfully extended one-dimensional differential transform method (DTM), by presenting and proving some theorems, to solving nonlinear high-order multi-pantograph equations. This technique provides a sequence of functions which converges to the exact solution of the problem. Some examples are given to demonstrate the validity and applicability of the present method and a comparison is made with existing results.

Keywords: Nonlinear multi-pantograph equation, delay differential equation, differential transformation method, proportional delay conditions, closed form solution.

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3650 Extending the Aspect Oriented Programming Joinpoint Model for Memory and Type Safety

Authors: Amjad Nusayr

Abstract:

Software security is a general term used to any type of software architecture or model in which security aspects are incorporated in this architecture. These aspects are not part of the main logic of the underlying program. Software security can be achieved using a combination of approaches including but not limited to secure software designs, third part component validation, and secure coding practices. Memory safety is one feature in software security where we ensure that any object in memory is have a valid pointer or a reference with a valid type. Aspect Oriented Programming (AOP) is a paradigm that is concerned with capturing the cross-cutting concerns in code development. AOP is generally used for common cross-cutting concerns like logging and Database transaction managing. In this paper we introduce the concepts that enable AOP to be used for the purpose of memory and type safety. We also present ideas for extending AOP in software security practices.

Keywords: Aspect oriented programming, programming languages, software security, memory and type safety.

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3649 Customization of a Real-Time Operating System Scheduler with Aspect-Oriented Programming

Authors: Kazuki Abe, Myungryun Yoo, Takanori Yokoyama

Abstract:

Tasks of an application program of an embedded system are managed by the scheduler of a real-time operating system (RTOS). Most RTOSs adopt just fixed priority scheduling, which is not optimal in all cases. Some applications require earliest deadline first (EDF) scheduling, which is an optimal scheduling algorithm. In order to develop an efficient real-time embedded system, the scheduling algorithm of the RTOS should be selectable. The paper presents a method to customize the scheduler using aspectoriented programming. We define aspects to replace the fixed priority scheduling mechanism of an OSEK OS with an EDF scheduling mechanism. By using the aspects, we can customize the scheduler without modifying the original source code. We have applied the aspects to an OSEK OS and get a customized operating system with EDF scheduling. The evaluation results show that the overhead of aspect-oriented programming is small enough.

Keywords: aspect-oriented programming, embedded system, operating system, real-time system

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3648 Gaussian Process Model Identification Using Artificial Bee Colony Algorithm and Its Application to Modeling of Power Systems

Authors: Tomohiro Hachino, Hitoshi Takata, Shigeru Nakayama, Ichiro Iimura, Seiji Fukushima, Yasutaka Igarashi

Abstract:

This paper presents a nonparametric identification of continuous-time nonlinear systems by using a Gaussian process (GP) model. The GP prior model is trained by artificial bee colony algorithm. The nonlinear function of the objective system is estimated as the predictive mean function of the GP, and the confidence measure of the estimated nonlinear function is given by the predictive covariance of the GP. The proposed identification method is applied to modeling of a simplified electric power system. Simulation results are shown to demonstrate the effectiveness of the proposed method.

Keywords: Artificial bee colony algorithm, Gaussian process model, identification, nonlinear system, electric power system.

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