Informatica

This paper proposes an access control mechanism of verifiable cloud computing services using chameleon hashing and Diffie–Hellman key exchange protocol. By this mechanism, an entity can apply for cloud computing services and he can authorize other users to access granted data or services. When an authorized user or entity wants to access cloud computing services, he can authenticate the cloud computing service provider. Moreover, no entity secret will be revealed by data kept by cloud servers such that security and cost saving can be both ensured. Security proof under the simulation paradigm is also given.

This paper investigates an approach which is called structural legal visualization (SLV). It is about diagrammatical views which facilitate comprehension of the meaning of legal contents. Complexity reduction is a motive. An issue is the complexity of the entire legal system and the layman’s limited ability to understand legal institutions and the millions of documents. A sequence of views in SLV can be compared with a narrative. SLV differs from information visualization and knowledge visualization. SLV relates to a scenario-centered graphical narrative rather than information display or user interfaces. SLV is about the generation (synthesis) of diagrams. The sequence of images depends on the user’s goals. Different pathways through the informational space are concerned. With respect to an object’s change or non-change, two variations of SLV are identified: dynamic SLV and static SLV. The latter is divided into two: incremental SLV and alternate focuses SLV.

Nowadays the web can serve as a perfect technological environment for personalized learning which is suggested by educators and based on interactive learning objects. While a range of technological solutions for the development of integrated e-learning environments already exists, the most appropriate solutions require further improvement of the implementation of novel learning objects, unification of standardization and integration of learning environments, based on semantic web services that are still in the early stages of development. The aim of the research is to create a model for the development of semantic learning objects, connect it with the architecture of the educational system for semantic learning object design and to present the experimental part of the model’s impact on the course design process. The paper presents the research with the main question on how to improve the e-learning course with semantic learning objects by exploring the application of learning object design approaches, usability, performing modern training facilities and the learning object design model based on semantic web technologies.

We propose a normalized parameter for characterization of similarity/dissimilarity of two sequences providing a smoothly varying measure for varying symmetry score. Such a parameter can be used for analysis of experimental data and fitting to a theoretical model, mirror symmetry estimation with respect to a selected or presumed symmetry axis, in particular, in symmetry detection applications where the selected symmetry parameters must be evaluated multiple times. We compare the proposed parameter, as well as several of the well-known distance and similarity measures, on an ensemble of template functions morphing continuously from symmetric to antisymmetric shape. This comparison allows to evaluate different similarity and symmetry measures in a more controlled and systematic setting than a simple visual estimation in sample images.

Effective movement of materials plays an important role in successful operation of any organization. Proper methods adopted for material movement are also crucial for the overall safety of the personnel involved in the manufacturing processes. Selection of the appropriate material handling equipment (MHE) is a vital task for improving productivity of an organization. In today’s technological era, varieties of MHEs are available to carry out a desired task. Depending on the type of material to be moved, there are many quantitative and qualitative factors influencing the selection decision of a suitable MHE. The problem of selecting the right type of MHE for a given purpose can be solved using multi-criteria decision-making (MCDM) methods which are capable of dealing with the combination of crisp and fuzzy data. In this paper, an MCDM method employing fuzzy axiomatic design principles is applied for selecting the most appropriate MHE for the given task. As a measure of suitability, the total information content is calculated for each MHE and the MHE alternative with the least total information content is regarded as the best choice. Two real time problems from the literature, i.e. selection of an automated guided vehicle, and selection of loading and hauling equipments in surface mines, are solved to validate the applicability, flexibility and potentiality of the adopted approach.

This paper presents a novel approach to the adaptation of multidimensional data models to user-specific needs. The multidimensional data models used in contemporary business-intelligence systems are inherently complex. In order to reduce the complexity of these models, we propose using a qualitative multiple-criteria decision modelling method that is based on using a hierarchical tree of the criteria to decompose the larger problem into a group of smaller problems. The final value is derived by aggregating the criteria values using simple “if-then” rules, which form the knowledge-based expert rules in the hierarchical criteria tree that reflect users’ preferences. The multiple-criteria analysis of the multidimensional model structure results in a multidimensional model that exhibits a reduced complexity and is adapted to users’ needs. The model was validated using sales data from a medium-size enterprise. The qualitative (through questionnaires) and the quantitative (through usage mining) evaluation of the proposed methodology both showed that the proposed approach increases the ease-of-use of business intelligence systems and also contributes to a higher user satisfaction.

In this paper we consider optimal congestion control and routing schemes for multipath networks with non-congestion related packet losses which can be caused by, for example, errors on links on the routes, and develop a relaxed multipath network utility maximization problem. In order to obtain the optimum, we present a primal algorithm which is shown to be globally stable in the absence of round-trip delays. When round-trip delays are considered, decentralized sufficient conditions for local stability of the algorithm are proposed, in both continuous-time and discrete-time forms. Finally, a window-flow control mechanism is presented which can approximate the optimum of the multipath network utility maximization model.

This paper proposes an extension of the ARAS method which, due to the use of interval-valued fuzzy numbers, can be more appropriate for solving real-world problems. In order to overcome the complexity of real-world decision-making problems, the proposed extension also includes the use of linguistic variables and a group decision making approach. In order to highlight the proposed methodology an example of a faculty websites evaluation is considered.

An efficient supervised orthogonal nonlinear dimensionality reduction algorithm, namely orthogonal margin maximization projection (OMMP), is presented for gait recognition in this paper. Taking the local neighborhood geometry structure and class information into account, the proposed algorithm aims to find a projecting matrix by maximizing the local neighborhood margin between the different classes and preserving the local geometry structure of the data. After projecting, the data points in the same class are pulled as close as possible, while the data points in different classes are pushed as far as possible. The highlights of OMMP include (1) takes both of the local information and class information of the data into account; (2) considers the effect of the noisy points and outliers; (3) it is supervised and orthogonal; and (4) its physical meaning is very clear. The experimental results on a public gait database show the effectiveness of the proposed method.