Related Fritz Carlson type inequalities for Sugeno integrals

In this paper, two general related inequalities to Carlson type inequality for the Sugeno integrals on an abstract fuzzy measure space $(X, \mathcal{F})$ are studied. Several examples are given to illustrate the validity of these inequalities.     

基于MATLAB的小波包信号消噪处理

信噪分离是小波包应用于信号分析的一个重要方面。本文在基于MATLAB的基础上,采用小波包对含高斯白噪声信号进行分解,通过不同的量化阈值对小波包系数进行处理、重构得出小波包消噪后的信号。计算机仿真结果表明,用不同量化阈值的小波包可对含高斯白声信号进行消噪重构。     

Predictors of user perceptions of web recommender systems: How the basis for generating experience and search product recommendations affects user responses

One critical question suggested by Web 2.0 is as follows: When is it better to leverage the knowledge of other users vs. rely on the product characteristic-based metrics for online product recommenders? Three recent and notable changes of recommender systems have been as follows: (1) a shift from characteristic-based recommendation algorithms to social-based recommendation algorithms; (2) an increase in the number of dimensions on which algorithms are based; and (3) availability of products that cannot be examined for quality before purchase. The combination of these elements is affecting users’ perceptions and attitudes regarding recommender systems and the products recommended by them, but the psychological effects of these trends remain unexplored. The current study empirically examines the effects of these elements, using a 2 (recommendation approach: content-based vs. collaborative-based, within)×2 (dimensions used to generate recommendations: 6 vs. 30, between)×2 (product type: experience products (fragrances) vs. search products (rugs), between) Web-based study (N=80). Participants were told that they would use two recommender systems distinguished by recommendation approach (in fact, the recommendations were identical). There were no substantive main effects, but all three variables exhibited two-way interactions, indicating that design strategies must be grounded in a multi-dimensional understanding of these variables. The implications of this research for the psychology and design of recommender systems are presented.     

Implementation and performance evaluation of a scheduling algorithm for divisible load parallel applications in a cloud computing environment

Cloud computing is an emerging technology in which information technology resources are virtualized to users in a set of computing resources on a pay‐per‐use basis. It is seen as an effective infrastructure for high performance applications. Divisible load applications occur in many scientific and engineering applications. However, dividing an application and deploying it in a cloud computing environment face challenges to obtain an optimal performance due to the overheads introduced by the cloud virtualization and the supporting cloud middleware. Therefore, we provide results of series of extensive experiments in scheduling divisible load application in a Cloud environment to decrease the overall application execution time considering the cloud networking and computing capacities presented to the application's user. We experiment with real applications within the Amazon cloud computing environment. Our extensive experiments analyze the reasons of the discrepancies between a theoretical model and the reality and propose adequate solutions. These discrepancies are due to three factors: the network behavior, the application behavior and the cloud computing virtualization. Our results show that applying the algorithm result in a maximum ratio of 1.41 of the measured normalized makespan versus the ideal makespan for application in which the communication to computation ratio is big. They show that the algorithm is effective for those applications in a heterogeneous setting reaching a ratio of 1.28 for large data sets. For application following the ensemble clustering model in which the computation to communication ratio is big and variable, we obtained a maximum ratio of 4.7 for large data set and a ratio of 2.11 for small data set. Applying the algorithm also results in an important speedup. These results are revealing for the type of applications we consider under experiments. The experiments also reveal the impact of the choice of the platforms provided by Amazon on the performance of the applications under study. Considering the emergence of cloud computing for high performance applications, the results in this paper can be widely adopted by cloud computing developers. Copyright © 2014 John Wiley & Sons, Ltd.     

Verifying Object-based Graph Grammars

The development of concurrent and reactive systems is gaining importance since they are well-suited to modern computing platforms, such as the Internet. However, the development of correct concurrent and reactive systems is a non-trivial task. Object-based graph grammar (OBGG) is a visual formal language suitable for the specification of this class of systems. In previous work, a translation from OBGG to PROMELA (the input language of the SPIN model checker) was defined, enabling the verification of OBGG models using SPIN. In this paper we extend this approach in two different ways: (1) the approach for property specification is improved, enabling to prove properties not only about possible OBGG derivations, but also about the internal state of involved objects; (2) an approach is defined to interpret PROMELA races as OBGG derivations, generating graphical counter-examples for properties that are not true for a given OBGG model. Another contribution of this paper is (3) the definition of a method for model checking partial systems (isolated objects or a set of objects) using an assume-guarantee approach. A gas station system modeled with OBGGs is used to illustrate the contributions.This work is partially sponsored by projects IQ-MObile (CNPq-Brazil/CNR-Italy) and PLATUS (CNPq).Osmar Marchi dos Santos is partially sponsored by CAPES-Brazil.     

计算机取证有效打击计算机犯罪

计算机取证研究的是如何为调查计算机犯罪提供彻底、有效和安全的技术,其关键是确保证据的真实性、可靠性、完整性和符合法律规定。本文首先分析计算机取证的产生背景,重点介绍计算机取证的原则和取证的步骤,进一步阐述计算机取证所采用的技术以及国内外在计算机取证领域研究的进展。     

On sorting triangles in a delaunay tessellation

In a two-dimensional Delaunay-triangulated domain, there exists a partial ordering of the triangles (with respect to a vertex) that is consistent with the two-dimensional visibility of the triangles from that vertex. An equivalent statement is that a polygon that is star-shaped with respect to a given vertex can be extended, one triangle at a time, until it includes the entire domain. Arbitrary planar triangulations do not possess this useful property which allows incremental processing of the triangles.This work was partially supported by the National Science Foundation's US-Italy Collaborative Research Program under Grant INT-8714578 and Information, Robotics, and Intelligent Research Grant IRI-8704781.     

Contextual web searches in Facebook using learning materials and discussion messages

The web is nowadays one of the main information sources, and information search is an important area in which many advances have been registered. One approach to improve web search results is to consider contextual information. Usually, information about context has been provided through user logs on previous searches or the monitoring of clicks on first results, but different approaches can be used in specific environments. In a web based learning environment, existing documents and exchanged messages could provide contextual information. So, the main goal of this work is to provide a contextual web search engine based on shared documents and messages posted in a social network used for collaborative learning. Contextual search is provided through query expansion using learning documents (material provided by the teacher) and discussion messages (posts, links and comments that result from the participants’ interactions). A prototype was implemented and used in a learning scenario to acquire the context in a learning community. The proposed approach makes the context acquisition faster and more dynamic as it considers an automatic approach over text processing of documents and discussions. In addition, the results of the query engine with and without the contextual information were compared and the proposed approach using contextual information showed improvements in the precision of the results.     

Unbiased parameter estimation of linear systems in the presence of input and output noise

It is well known that in practical situations the observed input-output data of an identified plant are usually corrupted by measurement noise. In this case the ordinary least-squares estimator of the system parameters is biased. In order to obtain a consistent estimator, a new type of modified least-squares estimation method, which is called the bias-eliminated least-squares (BELS) method, is presented in this paper. It is shown that the estimation bias can be determined if the variance of the white measurement noise can be obtained accurately. A designed first-order prefilter is connected in parallel to the input of the identified system. Based on asymptotic analysis, the noise variance can be estimated correctly by using the processed sampled data. Both a batch algorithm and a recursive algorithm are presented. It is shown that the presented BELS method gives a consistent estimate without a priori knowledge of the variance of the white input and output noise. Simulation results are presented to support the theoretical discussions.