Computer Science Journal (AGH University of Science and Technology, Krakow)
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A Hierarchical State Machine Model for Hazard Analysis of Real-time Safety Critical Systems
No full textReal-time systems must avoid hazardous situations. To achieve this, their functionality should be investigated under time constraints. In this paper, a modeling based on Hierarchical Communicating Real-time State Machine (H- CRSM) and analysis methodology is proposed to examine statically ANSI-C code to obtain the hazardous events in the input system. A hazardous event equation is taken as input to the proposed system. The output is a list of hazardous scenarios. A path in the code showing the cause of the undesirable event is associated with each hazardous scenario. The strength of the proposed methodology is that the process of hazardous situations detection does not require running the ANSI-C program multiple times with different input values. It also focuses on analyzing the software level of the life cycle. Most of the verification tools check the system level. The system level may be bug-free but the software level may not
Energy redistribution in autonomous hybridization of agent-based computing
Full text linkEvolutionary multi-agent systems (EMAS) are very good at dealing with difficult, multi-dimensional problems. Currently, research is underway to improve this algorithm, giving even more freedom to agents not only in solving the problem but also in making decisions on the behavior of the algorithm. One way is to hybridize this algorithm with other existing algorithms creating Hybrid Evolutionary Multi Agent-System (HEMAS). Unfortunately, such connections generate problems in the form of an unbalanced energy level of agents who have made the decision to use such an improvement. One of the solutions is the mechanism of redistributing the agents\u27 energy in the form of an operator. The article presents several proposals of redistribution operators along with numerous experimental results
Falcon Optimization Algorithm for Bayesian Networks Structure Learning
Full text linkIn machine-learning, one of the useful scientific models for producing the structure of knowledge is Bayesian network, which can draw probabilistic dependency relationships between variables. The score and search is a method used for learning the structure of a Bayesian network. The authors apply the Falcon Optimization Algorithm (FOA) as a new approach to learning the structure of Bayesian networks. This paper uses the Reversing, Deleting, Moving and Inserting operations to adopt the FOA for approaching the optimal solution of Bayesian network structure. Essentially, the falcon prey search strategy is used in the FOA algorithm. The result of the proposed technique is compared with Pigeon Inspired optimization, Greedy Search, and Simulated Annealing using the BDeu score function. The authors have also examined the performances of the confusion matrix of these techniques utilizing several benchmark data sets. As shown by the evaluations, the proposed method has more reliable performance than the other algorithms including producing better scores and accuracy values
Efficient Simulations of Large Scale Convective Heat Transfer Problems
Full text linkWe describe an approach for efficient solution of large scale convective heat transfer problems, formulated as coupled unsteady heat conduction and incompressible fluid flow equations. The original problem is discretized in time using classical implicit methods, while stabilized finite elements are used for space discretization. The algorithm employed for the discretization of the fluid flow problem uses Picard\u27s iterations to solve the arising nonlinear equations. Both problems, heat transfer and Navier-Stokes quations, give rise to large sparse systems of linear equations. The systems are solved using iterative GMRES solver with suitable preconditioning. For the incompressible flow equations we employ a special preconditioner based on algebraic multigrid (AMG) technique. The paper presents algorithmic and implementation details of the solution procedure, which is suitably tuned, especially for ill conditioned systems arising from discretizations of incompressible Navier-Stokes equations. We describe parallel implementation of the solver using MPI and elements of PETSC library. The scalability of the solver is favourably compared with other methods such as direct solvers and standard GMRES method with ILU preconditioning.
Population Diversity in Ant-inspired Optimization Algorithms
Full text linkFinding a balance between exploration and exploitation is very important in the case of metaheuristics optimization, especially in the systems leveraging population of individuals expressing (as in Evolutionary Algorithms, etc.) or constructing (as in Ant Colony Optimization) solutions. Premature convergence is a real problem and finding means of its automatic detection and counteracting are of great importance. Measuring diversity in Evolutionary Algorithms working in real-value search space is often computationally complex, but feasible while measuring diversity in combinatorial domain is practically impossible (cf. Closest String Problem). Nevertheless, we propose several practical and feasible diversity measurement techniques dedicated to Ant Colony Optimization algorithms, leveraging the fact that even though analysis of the search space is at least an NP problem, we can focus on the pheromone table, where the direct outcomes of the search are expressed and can be analyzed. Besides proposing the measurement techniques, we apply them to assess the diversity of several variants of ACO, and closely analyze their features for the classic ACO. The discussion of the results is the first step towards applying the proposed measurement techniques in auto-adaptation of the parameters affecting directly the exploitation and exploration features in ACO in the future
Optimized jk-nearest neighbor based online signature verification and evaluation of the main parameters
Full text linkIn this paper, we propose an enhanced jk-nearest neighbor (jk-NN) classifier for online signature verification. After studying the algorithm\u27s main parameters, we use four separate databases to present and evaluate each algorithm parameter. The results show that the proposed method can increase the verification accuracy by 0.73-10% compared to a traditional one class k-NN classifier. The algorithm has achieved reasonable accuracy for different databases, a 3.93% error rate when using the SVC2004 database, 2.6% for MCYT-100 database, 1.75% for the SigComp\u2711 database, and 6% for the SigComp\u2715 database.The proposed algorithm uses specifically chosen parameters and a procedure to pick the optimal value for K using only the signer\u27s reference signatures, to build a practical verification system for real-life scenarios where only these signatures are available. By applying the proposed algorithm, the average error achieved was 8% for SVC2004, 3.26% for MCYT-100, 13% for SigComp\u2715, and 2.22% for SigComp\u2711
A Novel Anchor Selection Scheme for Distributed Mobility Management
No full textThe number of subscribers in mobile networks is growing rapidly, which challenges the network management and data delivery. The efficient management and routing are key solutions. An important one of the solutions is the Distributed Mobility Management (DMM) that to handles the mobility of subscribers at the edge of mobile networks and load balancing. Otherwise, mobility anchors are distributed across the network, which can manage the handover procedures. In this paper, we propose a novel mobility anchor selection scheme based on the results of a cost function with three factors, to select a suitable cell and anchor for moving subscribers and improve the handover performances of the network. Our results illustrate that the proposed scheme provides significantly enhanced handover performance
Circle formation by asynchronous opaque robots on infinite grid
Full text linkThis paper presents a distributed algorithm for circle formation problem under the infinite grid environment by asynchronous mobile opaque robots. Initially all the robots are acquiring distinct positions and they have to form a circle over the grid. Movements of the robots are restricted only along the grid lines. They do not share any global co-ordinate system. Robots are controlled by an asynchronous adversarial scheduler that operates in Look-Compute-Move cycles. The robots are indistinguishable by their nature, do not have any memory of their past configurations and previous actions. We consider the problem under luminous model, where robots communicate via lights, other than that they do not have any external communication system. Our protocol solves the circle formation problem using seven colors. A subroutine of our algorithm also solves the line formation problem using three colors
An investigation of the aerodynamic parameters for Solar Plane wing profile using CFD modelling
No full textThe technology of solar-powered aerial vehicles requires enormous financial support and further development. For this purpose, the computational fluid dynamic can be used. In order to carry out necessary analyses and model development in this research, ANSYS Fluent software was used. Using the first version of the AGH Solar Plane model, preliminary analysis of lift, drag and tearing off the stream were performed. Numerical experiments made it possible to verify many various profiles and final selection that the best suits the target model. Through these studies, it was also possible to analyse fluid flow at various speeds and angles of attack. This provided an insight into important aspects of vehiclesaerodynamic design, which should be taken into account when making the second model version. At this stage, the classical and laminar - Wortmann aerodynamic profiles were selected on the basis of the aerodynamic perfection criterion. Moreover, four new geometries were prepared on which the flattening of upper surfaces (for fixing solar panels) was tested. The results of the numerical analysis were validated in the aerodynamic tunnel using particle image velocimetry method. Taking into account all analyses, a number of recommendations have been prepared that will be implemented in order to create an aircraft, which meets all target requirements. Some of these hints were: testing new ways of connecting the wing to the nacelle, which would reduce the drag as well as considering the usage of winglets in order to minimize induced drag
A UML 2.0 Activity Diagrams/CSP Integrated Approach for Modeling and Verification of Software Systems
Full text linkThis paper proposes an approach integrating UML 2.0 Activity Diagrams (UML2-AD) and Communicating Sequential Process (CSP) for modeling and verication of software systems. A UML2-AD is used for modeling a software system while CSP is used for verication purposes. The proposed approach consists of another way of transforming UML2-AD models to Communicating Sequential Process (CSP) models. It focuses also on checking the correctness of some properties of the transformation itself. These properties are specified using Linear Temporal Logic (LTL) and verified using the GROOVE model checker. This approach is based on Model Driven Engineering (MDE). The meta-modelling is realized using AToMPM tool while the model transformation and the correctness of its properties are realized using GROOVE tool. Finally, we illustrated this approach through a case study