A hybrid image restoration approach: fuzzy logic and directional weighted median based uniform impulse noise removal

In this paper, a hybrid image restoration technique based on fuzzy logic and directional weighted median is presented. The proposed technique consists of noise detection and fuzzy filtering processes to detect and remove uniform (random-valued) impulse noise while preserving the image details efficiently. In order to preserve image details such as edges and texture information, a two-stage robust noise detection is presented in this paper. Pixels detected as noisy by both the noise detection stages are considered for noise removal by the fuzzy filtering process, which utilizes the direction based weighted median to construct fuzzy membership function, which is the main contributing factor in noise removal and detail preservation. Extensive experimentation shows that the proposed technique performs significantly better than state-of-the-art filters based on peak signal-to-noise ratio, structural similarity index measure and subjective evaluation criteria.     

Performance evaluation of a non-linear error model for underwater range computation utilizing GPS sonobuoys

Deployed from an airborne platform or a surface vessel, arrays of GPS sonobuoys can be used to efficiently track and localize submarines. The range of the target of interest can be monitored with the deployed sonobuoys. However, the accuracy deteriorates when the target is on the detection range of only one sonobuoy. The objective of this research is to improve the range computation of the target of interest by establishing a non-linear error model for range error using adaptive neuro-fuzzy inference systems (ANFIS), which has the capabilities of dealing with data of high level of uncertainty and the advantage of being based on neural computation. Furthermore, the performance of the proposed model is examined with both experimental real field data and contact-level simulation data considering different scenarios for both the array of GPS sonobuoys and the target. The results discuss merits and the limitations of the proposed method.     

Beam‐pattern synthesis using slotted Rotman lenses

In this article, the design principle of the Rotman lens is reviewed, and an X‐band lens for 10‐GHz operating frequency is simulated and analyzed. Rotman lenses with circular and elliptical slots of different orientations are simulated, and their associated radiation patterns are plotted too. The characteristics of the radiation patterns generated by a linear array antenna and the slotted Rotman lenses are functions of the shape, dimensions, location, and orientation of the slots etched on the metallic surface of the lenses that feed the array. The computer simulation results demonstrate that, in addition to the other significant advantages of microwave lenses, there is a strong potential for using slotted Rotman lenses as convenient microwave devices for beam‐pattern synthesis. © 2011 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2011.     

RiSeG: a ring based secure group communication protocol for resource-constrained wireless sensor networks

Securing group communication in wireless sensor networks has recently been extensively investigated. Many works have addressed this issue, and they have considered the grouping concept differently. In this paper, we consider a group as being a set of nodes sensing the same data type, and we alternatively propose an efficient secure group communication scheme guaranteeing secure group management and secure group key distribution. The proposed scheme (RiSeG) is based on a logical ring architecture, which permits to alleviate the group controller’s task in updating the group key. The proposed scheme also provides backward and forward secrecy, addresses the node compromise attack, and gives a solution to detect and eliminate the compromised nodes. The security analysis and performance evaluation show that the proposed scheme is secure, highly efficient, and lightweight. A comparison with the logical key hierarchy is preformed to prove the rekeying process efficiency of RiSeG. Finally, we present the implementation details of RiSeG on top of TelosB sensor nodes to demonstrate its feasibility.     

Stability routing with constrained path length for improved routability in dynamic MANETs

Quality of service (QoS) routing is known to be an NP-hard problem in case of two or more additive constraints, and several exact algorithms and heuristics have been proposed to address this issue. In this paper, we consider a particular two-constrained quality of service routing problem maximizing path stability with a limited path length in the quest of improving routability in dynamic multi-hop mobile wireless ad hoc networks. First, we propose a novel exact algorithm to solve the optimal weight-constrained path problem. We instantiate our algorithm to solve the most stable path not exceeding a certain number of hops, in polynomial time. This algorithm is then applied to the practical case of proactive routing in dynamic multi-hop wireless ad hoc networks. In these networks, an adequate compromise between route stability and its length in hops is essential for appropriately mitigating the impact of the network dynamics on the validity of established routes. Secondly, we set up a common framework for the comparison between three families of proactive routing: the shortest path-based routing, the most stable path-based routing and our proposed most stable constrained path routing. We show then through extensive simulations that routing based on our proposed algorithm selects appropriate stable paths yielding a very high routability with an average path length just above that of the shortest paths.     

Improvement of tropical vegetation mapping using a remote sensing technique: A case of Khao Yai National Park,Thailand

The forest ecosystems of Thailand are characterized by a diverse and complex vegetation structure. Classification of vegetation types of such forest ecosystems has been experienced as a difficult task, even with large-scale aerial photography. Satellite remote sensing, the digital technique in particular, has not been widely used for vegetation mapping in Thailand until now. The objective of this study was to explore the potential of digital image processing over the existing technique of visual interpretation of Landsat Thematic Mapper (TM) false colour composite (BGR-2, 3, 4) to produce forest cover maps in Thailand. Supervised and unsupervised classification methods were employed with different band combinations to discriminate vegetation types in the Khao Yai National Park using Landsat TM data. The results indicated that thematic classes derived from supervised classification produced higher overall accuracy than unsupervised classification. In addition, the combination of ratio bands R4/3, R5/2, R5/4 and R5/7 ranked the highest in terms of accuracy (65% for unsupervised and 79% for supervised) and the combination of bands 2, 3 and 4 gave the lowest (56% for both methods). Finally, it was concluded that, even within the limit of spectral information available in the image, the digital classification can improve the result of visual interpretation.     

A genetic approach to the identification of linear dynamical systems with static nonlinearities

This paper investigates the use of genetic algorithms in the identification of linear systems with static nonlinearitites. Linear systems with static nonlinearities at the input known as the Hammerstein model, and linear systems with static nonlinearities at the output known as the Wiener model are considered in this paper. The parameters of the Hammerstein and the Wiener models are estimated using genetic algorithms from the input-output data by minimizing the error between the true model output and the identified model output. Using genetic algorithms, the Hammerstein and the Wiener models with known nonlinearity structure and unknown parameters can be identified. Moreover, systems with non-minimum phase characteristics can be identified. Extensive simulations have been used to study the convergence properties of the proposed scheme. Simulation examples are included to demonstrate the effectiveness and robustness of the proposed identification scheme.     

A Parallel Implementation of ALE Moving Mesh Technique for FSI Problems using OpenMP

This paper investigates a high performance implementation of an Arbitrary Lagrangian Eulerian moving mesh technique on shared memory systems using OpenMP environment. Moving mesh techniques are considered an integral part of a wider class of fluid mechanics problems that involve moving and deforming spatial domains, namely, free-surface flows and Fluid Structure Interaction (FSI). The moving mesh technique adopted in this work is based on the notion of nodes relocation, subjected to a certain evolution as well as constraint conditions. A conjugate gradient method augmented with preconditioning is employed for solution of the resulting system of equations. The proposed algorithm, initially, reorders the mesh using an efficient divide and conquer approach and then parallelizes the ALE moving mesh scheme. Numerical simulations are conducted on the multicore AMD Opteron and Intel Xeon processors, and unstructured triangular and tetrahedral meshes are used for the 2D and 3D problems. The quality of generated meshes is checked by comparing the element Jacobians in the reference and current meshes, and by keeping track of the change in the interior angles in triangles and tetrahedrons. Overall, 51 and 72% efficiencies in terms of speedup are achieved for both the parallel mesh reordering and ALE moving mesh algorithms, respectively.     

Some properties of soft topological spaces

For dealing with uncertainty researchers introduced the concept of soft sets. Shabir and Naz (2011) [28], defined several basic notions on soft topology and studied many properties. In this paper, we continue investigating the properties of soft open (closed), soft nbd and soft closure. We also define and discuss the properties of soft interior, soft exterior and soft boundary which are fundamental for further research on soft topology and will strengthen the foundations of the theory of soft topological spaces.