Trust management towards service-oriented applications

In service-oriented computing (SOC) environments, service clients interact with service providers for services or transactions. From the point view of service clients, the trust status of a service provider is a critical issue to consider, particularly when the service provider is unknown to them. Typically, the trust evaluation is based on the feedback on the service quality provided by service clients. In this paper, we first present a trust management framework that is event-driven and rule-based. In this framework, trust computation is based on formulae. But rules are defined to determine which formula to use and what arguments to use, according to the event occurred during the transaction or service. In addition, we propose some trust evaluation metrics and a formula for trust computation. The formula is designed to be adaptable to different application domains by setting suitable arguments. Particularly, the proposed model addresses the incremental characteristics of trust establishment process. Furthermore, we propose a fuzzy logic based approach for determining reputation ranks that particularly differentiates new service providers and old (long-existing) ones. This is further incentive to new service providers and penalize poor quality services from service providers. Finally, a set of empirical studies has been conducted to study the properties of the proposed approaches, and the method to control the trust changes in both trust increment and decrement cases. The proposed framework is adaptable for different domains and complex trust evaluation systems.

Comparative Study of the Different Variants of the DV-Hop Based Node Localization Algorithms for Wireless Sensor Networks

Wireless Personal Communications - Node localization is one of the essential services where sensor nodes in the wireless sensor network collaborate to provide location information of sensor nodes...     

CP2EH: a comprehensive privacy-preserving e-health scheme over cloud

The Journal of Supercomputing - In the Attribute-Based Encryption (ABE) scheme, patients encrypt their electronic health record (EHR), attach the appropriate attributes with it, and outsource them...     

Dehazing of remote sensing images using improved restoration model based dark channel prior

Haze degrades visual information of remotely sensed images. Therefore, haze removal is a demanding and significant task for visual multispectral information improvement. The existing haze removal techniques utilize different restrictions and before restoring hazy images in an efficient manner. The review of existing haze removal methods demonstrates that the haze-free images suffer from colour distortion and halo artefacts problems. To solve these issues, an improved restoration model based dark channel prior is proposed in this paper. The proposed technique has redefined transmission map, with the aim to reduce the colour distortion problem. The modified joint trilateral filter is also utilized to improve the coarse estimated atmospheric veil. The experimental results reveal that the proposed approach provides visually significant haze-free images and also preserves the significant detail.     

Symmetry in scalar field topology

Study of symmetric or repeating patterns in scalar fields is important in scientific data analysis because it gives deep insights into the properties of the underlying phenomenon. Though geometric symmetry has been well studied within areas like shape processing, identifying symmetry in scalar fields has remained largely unexplored due to the high computational cost of the associated algorithms. We propose a computationally efficient algorithm for detecting symmetric patterns in a scalar field distribution by analysing the topology of level sets of the scalar field. Our algorithm computes the contour tree of a given scalar field and identifies subtrees that are similar. We define a robust similarity measure for comparing subtrees of the contour tree and use it to group similar subtrees together. Regions of the domain corresponding to subtrees that belong to a common group are extracted and reported to be symmetric. Identifying symmetry in scalar fields finds applications in visualization, data exploration, and feature detection. We describe two applications in detail: symmetry-aware transfer function design and symmetry-aware isosurface extraction.     

Selection of industrial robots using compromise ranking and outranking methods

Selection of a robot for a specific industrial application is one of the most challenging problems in real time manufacturing environment. It has become more and more complicated due to increase in complexity, advanced features and facilities that are continuously being incorporated into the robots by different manufacturers. At present, different types of industrial robots with diverse capabilities, features, facilities and specifications are available in the market. Manufacturing environment, product design, production system and cost involved are some of the most influencing factors that directly affect the robot selection decision. The decision maker needs to identify and select the best suited robot in order to achieve the desired output with minimum cost and specific application ability. This paper attempts to solve the robot selection problem using two most appropriate multi-criteria decision-making (MCDM) methods and compares their relative performance for a given industrial application. The first MCDM approach is ‘VIsekriterijumsko KOmpromisno Rangiranje’ (VIKOR), a compromise ranking method and the other one is ‘ELimination and Et Choice Translating REality’ (ELECTRE), an outranking method. Two real time examples are cited in order to demonstrate and validate the applicability and potentiality of both these MCDM methods. It is observed that the relative rankings of the alternative robots as obtained using these two MCDM methods match quite well with those as derived by the past researchers.     

A bandpass filter with adjustable bandwidth and predictable transmission zeros

In this article, a microstrip bandpass filter with an adjustable bandwidth and predictable transmission zeros is proposed. The proposed filter is implemented by combining two hairpin edge‐coupled resonators with interdigital capacitors. Compared to typical edge‐coupled filters, the proposed filter provides a wider bandwidth resulting from a higher coupling strength between its resonators. To further increase the coupling and consequently the bandwidth, a pair of etched slots in the ground plane is used. By adjusting the geometrical parameters of the interdigital capacitors and etched slots, the bandwidth can be easily adjusted. The filter features two transmission zeros, which are determined by means of the semi‐analytical model developed as part of this work. Furthermore, the proposed filters can be cascaded to obtain a sharper cutoff frequency response. Frequency responses of the filters from measurements are in good agreement with those simulated using IE3D in the 5–9 GHz range. © 2009 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2010.     

Simultaneous selection of optimal parameters and tolerance of manipulator using evolutionary optimization technique

For precise industrial applications, a manipulator must have high positioning accuracy and repeatability. However, variations in performance of the manipulator are attributed to improper selection of dimensions of design and process parameters and its tolerance. There have been almost no attempts to optimize these parameters and tolerance of the manipulator, by which performance variations will be minimum. This paper presents an offline approach to select optimal parameters and tolerance simultaneously which minimizes the manufacturing cost and delivers the target performance level. To determine the optimal parameters and tolerances, a modification in differential evolution algorithm is proposed, which helps in incorporating the effect of uncertainty in optimization process. Proposed approach has been illustrated by selecting optimal parameters and tolerance of a 2-DOF RR planar manipulator. The performance of this approach has been compared with modified genetic algorithm. It is observed that differential evolution algorithm provides optimal results with lesser computations compared to genetic algorithm.     

On neighbor discovery in cognitive radio networks

A cognitive radio node is a radio device capable of operating over multiple channels. As a result, a network consisting of one or more cognitive radio nodes can adapt to varying channel availability in its geographical region by dynamically changing the channel (or channels) nodes are using for communication.