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.

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.     

Automated dynamic detection of busy–wait synchronizations

With the advent of multicores, multithreaded programming has acquired increased importance. In order to obtain good performance, the synchronization constructs in multithreaded programs need to be carefully implemented. These implementations can be broadly classified into two categories: busy–wait and schedule‐based. For shared memory architectures, busy–wait synchronizations are preferred over schedule‐based synchronizations because they can achieve lower wakeup latency, especially when the expected wait time is much shorter than the scheduling time. While busy–wait synchronizations can improve the performance of multithreaded programs running on multicore machines, they create a challenge in program debugging, especially in detecting and identifying the causes of data races. Although significant research has been done on data race detection, prior works rely on one important assumption—the debuggers are aware of all the synchronization operations performed during a program run. This assumption is a significant limitation as multithreaded programs, including the popular SPLASH‐2 benchmark have busy–wait synchronizations such as barriers and flag synchronizations implemented in the user code. We show that the lack of knowledge of these synchronization operations leads to unnecessary reporting of numerous races. To tackle this problem, we propose a dynamic technique for identifying user‐defined synchronizations that are performed during a program run. Both software and hardware implementations are presented. Furthermore, our technique can be easily exploited by a record/replay system to significantly speedup the replay. It can also be leveraged by a transactional memory system to effectively resolve a livelock situation. Our evaluation confirms that our synchronization detector is highly accurate with no false negatives and very few false positives. We further observe that the knowledge of synchronization operations results in 23% reduction in replay time. Finally, we show that using synchronization knowledge livelocks can be efficiently avoided during runtime monitoring of programs. Copyright © 2009 John Wiley & Sons, Ltd.     

Identifying and overcoming the challenges of implementing a project management office

With the ongoing challenge of successfully managing information technology (IT) projects, organizations are recognizing the need for greater project management discipline. For many organizations, this has meant ratcheting up project management skills, processes, and governance structures by implementing a project management office (PMO). While anecdotal evidence suggests that implementing a PMO can be quite difficult, few studies discuss the specific challenges involved, and how organizations can overcome them. To address this gap in existing knowledge, we conducted a Delphi study to (1) identify the challenges of implementing a PMO for managing IT projects, (2) rank these challenges in order of importance, (3) discover ways in which some organizations have overcome the top-ranked challenges, and (4) understand the role of PMO structure, metrics, and tools in the implementation of a PMO.We identified 34 unique challenges to implementing a PMO and refined this list to 13 challenges that our Delphi panelists considered most important. The top-three challenges were (1) rigid corporate culture and failure to manage organizational resistance to change, (2) lack of experienced project managers (PMs) and PMO leadership, and (3) lack of appropriate change management strategy. Through follow-up interviews with selected panelists, we identified a series of actions that can be taken to overcome these challenges including having a strong PMO champion, starting small and demonstrating the value of the PMO, obtaining support from opinion leaders, hiring an experienced program manager who understands the organization, bringing the most talented PMs into the PMO implementation team, adopting a flexible change management strategy, and standardizing processes prior to PMO implementation. The interviews were also used to better understand the role of PMO structure, metrics, and tools. In terms of PMO structure, we found that ‘light’ PMOs were more likely to be implemented successfully. Most organizations eschew formal metrics, instead relying on subjective indicators of PMO success. Lastly, it appears that PMO tools are difficult to implement unless a project management culture has been established.     

Intelligent adaptive observer-based optimal control of overhead transmission line de-icing robot manipulator

In cold season, wet snow ice accretion on overhead transmission lines increases wind load effects which in turn increases line tension. This increased line tension causes undesirable effects in power systems. This paper discusses the design of an observer-based boundary sliding mode control (BSMC) for 3 DOF overhead transmission line de-icing robot manipulator (OTDIRM). A robust radial basis functional neural network (RBFNN) observer-based neural network (NN) controller is developed for the motion control of OTDIRM, which is a combination of BSMC, NN approximation and adaptation law. The RBFNN-based adaptive observer is designed to estimate the positions and velocities. The weights of both NN observer and NN approximator are tuned off-line using particle swarm optimization. Using Lyapunov analysis the closed loop tracking error was verified for a 3 DOF OTDIRM. Finally, the robustness of the proposed neural network-based adaptive observer boundary sliding mode control (NNAOBSMC) was verified against the input disturbances and uncertainties.     

Classification of patterns representing Apples and Oranges in three-qubit system

The study of the classification of Apples and Oranges in a warehouse has been undertaken in a three-qubit system using the method of repeated iterations in Grover’s algorithm and Ventura’s algorithm separately. Operator describing an inversion about average has been constructed as a square matrix of order eight, the phase inversion operators and corresponding iteration operators for patterns separately representing Apples and Oranges have been derived, and various possible superpositions as the choice for search states for the classification of these patterns have been obtained for starting states consisting of two patterns and a single pattern, respectively. It has been demonstrated that on the second iteration of the exclusion superposition by the corresponding iteration operators, the patterns Apples and Oranges, respectively, are most suitably classified using the Grover’s algorithm. The probabilities of classifications of Apples have also been calculated by using Ventura’s algorithm (Ventura and Martinez in Inf Sci 124:273–296, 2000; Found Phys Lett 12:547–559, 1999) for all the possible superpositions as the search states, and the results have been compared with those of Grover’s algorithm and it has been demonstrated that in general for classification of a given pattern (Apples) in three-qubit system, the Grover’s and Ventura’s algorithms are effective in the cases where the number of patterns in the stored database is larger or smaller, respectively.