A flexible semantic inference methodology to reason about user preferences in knowledge-based recommender systems

Recommender systems arose with the goal of helping users search in overloaded information domains (like e-commerce, e-learning or Digital TV). These tools automatically select items (commercial products, educational courses, TV programs, etc.) that may be appealing to each user taking into account his/her personal preferences. The personalization strategies used to compare these preferences with the available items suffer from well-known deficiencies that reduce the quality of the recommendations. Most of the limitations arise from using syntactic matching techniques because they miss a lot of useful knowledge during the recommendation process. In this paper, we propose a personalization strategy that overcomes these drawbacks by applying inference techniques borrowed from the Semantic Web. Our approach reasons about the semantics of items and user preferences to discover complex associations between them. These semantic associations provide additional knowledge about the user preferences, and permit the recommender system to compare them with the available items in a more effective way. The proposed strategy is flexible enough to be applied in many recommender systems, regardless of their application domain. Here, we illustrate its use in AVATAR, a tool that selects appealing audiovisual programs from among the myriad available in Digital TV.     

一种自适应的数字图像信息隐藏算法

给出一种新的自适应数字图像信息隐藏算法.在传统混合算法的基础上,根据公开图像本身的像素分布和颜色特点,对混合系数进行改变.算法结合图像的局部特征,充分利用人类视觉的各种掩蔽特性自适应地嵌入秘密信息,对原图像所作的改变具有很好的不可见性.算法简单、信息隐藏量大,且具有一定的鲁棒性.     

WSN 中基于粒子滤波的目标跟踪研究

针对无线传感器网络中仅有角度测量的目标跟踪问题,详细分析其定位过程,提出一种基于改进粒子滤波算法的新解决方案.方案采用高斯混合模型(GMM)代替单一模型近似概率密度分布,融入粒子滤波算法,提议分布采用SRUKF-PF算法更新粒子.算法中增加改进措施以提高滤波性能如:残差重采样算法用于重采样、K-means算法用于构建预估起始点、EM算法用于拟合GMM近似等.仿真结果验证了方案的有效性.     

Medical image segmentation with transform and moment based features and incremental supervised neural network

In this study, a novel incremental supervised neural network (ISNN) is proposed for the segmentation of medical images. Performance of the ISNN is investigated for tissue segmentation in medical images obtained from various imaging modalities. Two feature extraction methods based on transform and moments are comparatively investigated to segment the tissues in medical images. Two-dimensional (2D) continuous wavelet transform (CWT) and the moments of the gray-level histogram (MGH) are computed in order to form the feature vectors of ultrasound (US) bladder and phantom images, X-ray computerized tomography (CT) and magnetic resonance (MR) head images. In the 2D-CWT method, feature vectors are formed by the intensity of one pixel of each wavelet-plane of different energy bands. The MGH represents the tissues within the sub-windows by using the spatial variation of image intensities. In this study, the ISNN and Grow and Learn (GAL) network are employed for the segmentation task. It is observed that the ISNN has significantly eliminated the disadvantages of the GAL network in the segmentation of the medical images.     

Analytical formulation to compute QFT bounds: The envelope method

This paper describes an analytical formulation to compute quantitative feedback theory (QFT) bounds in one‐degree‐of‐freedom feedback control problems. The new approach is based on envelope curves and shows that a QFT control specification can be expressed as a family of circumferences. Then, the controller bound is defined by the envelope curve of this family and can be obtained as an analytical function. This offers the possibility of studying the QFT bounds in an analytical way with several useful properties. Gridding methods are avoided, resulting in a lower computational effort procedure. The new formulation improves the accuracy of previous methods and allows the designer to calculate multivalued bounds. Copyright © 2009 John Wiley & Sons, Ltd.     

Interpretation of MR images using self-organizing maps and knowledge-based expert systems

A new image segmentation system is presented to automatically segment and label brain magnetic resonance (MR) images to show normal and abnormal brain tissues using self-organizing maps (SOM) and knowledge-based expert systems. Elements of a feature vector are formed by image intensities, first-order features, texture features extracted from gray-level co-occurrence matrix and multiscale features. This feature vector is used as an input to the SOM. SOM is used to over segment images and a knowledge-based expert system is used to join and label the segments. Spatial distributions of segments extracted from the SOM are also considered as well as gray level properties. Segments are labeled as background, skull, white matter, gray matter, cerebrospinal fluid (CSF) and suspicious regions.     

LCD motion‐blur estimation using different measurement methods

Abstract— The primary goal of this study was to find a measurement method for motion blur which is easy to carry out and gives results that can be reproduced from one lab to another. This method should be able to also take into account methods for reduction of motion blur such as backlight flashing. Two methods have been compared. The first method uses a high‐speed camera that permits us to directly picture the blurred‐edge profile. The second one exploits the mathematical analysis of the motion‐blur formation to construct the blurred‐edge profile from the temporal step response. Measurement results and method proposals are given and discussed.     

BerlinMOD: a benchmark for moving object databases

This document presents a method to design scalable and representative moving object data (MOD) and two sets of queries for benchmarking spatio-temporal DBMS. Instead of programming a dedicated generator software, we use the existing Secondo DBMS to create benchmark data. The benchmark is based on a simulation scenario, where the positions of a sample of vehicles are observed for an arbitrary period of time within the street network of Berlin. We demonstrate the data generator’s extensibility by showing how to achieve more natural movement generation patterns, and how to disturb the vehicles’ positions to create noisy data. As an application and for reference, we also present first benchmarking results for the Secondo DBMS. Whereas the benchmark focuses on range queries, we demonstrate its ability to incorporate new future classes of queries by presenting a preliminary extension handling various nearest neighbour queries. Such a benchmark is useful in several ways: It provides well-defined data sets and queries for experimental evaluations; it simplifies experimental repeatability; it emphasizes the development of complete systems; it points out weaknesses in existing systems motivating further research. Moreover, the BerlinMOD benchmark allows one to compare different representations of the same moving objects.     

The Influence of the Internet on European Journalism

This study investigates how European journalists evaluate the changes that have occurred in their profession since the Internet has been integrated in newsrooms. How do journalists perceive the features and innovations associated with the Internet? What are the principal changes in the profession? Do practitioners believe that the quality of journalism has been raised or lowered? To answer to these research questions, we carried out a survey across 11 European countries–Cyprus, Estonia, Finland, Greece, Ireland, Italy, Lithuania, United Kingdom, Slovenia, Spain, Sweden–of 239 journalists, working for 40 of the most‐read print/online news outlets in these countries. The survey shows that the opportunity to use the Internet to reinforce the social functions of journalism has not been fully recognised.     

GLSV: Graphics library stereo vision for OpenGL

This work proposes the development of an auxiliary library for use with OpenGL, to facilitate the creation of graphic applications incorporating stereoscopic representation. This library, christened graphics library stereo vision (GLSV), is designed to remove all calculations involving knowledge of stereo vision theory from the task performed by the programmer without the latter having to change the way he/she has been working with the OpenGL library. The GLSV is distributed under the terms of the GNU Library General Public License agreement.