Analysis of MySpace user profiles

Online social networks have attracted millions of users, who have integrated social network web sites into their daily life. Users participate to the changes and to the evolution of these sites because they are producers and reviewers of contents that help them to maintain the existing social relationships, make new friends, collaborate and enrich experiences. This paper presents a study of the characteristics of the users of MySpace web site, with the objective of studying relationships and interactions among users and deriving hints about their behavior. The analysis relies on data collected by monitoring the web site for 12 weeks. Typical user behaviors have been derived and classes of users characterized by different levels of participation to the social network have been identified. In particular, the analysis reveals that most of the users actively participate to the social network and specify many personal details. Social networks web sites allow access to such details; the sharing of information about users and their relationships can lead to non-ethic online activities, which threat the privacy and the security of users themselves.     

Differential evolution solution to the SLAM problem

A new solution to the Simultaneous Localization and Modelling problem is presented in this paper. The algorithm is based on the stochastic search for solutions in the state space to the global localization problem by means of a differential evolution algorithm. This non linear evolutive filter, called Evolutive Localization Filter (ELF), searches stochastically along the state space for the best robot pose estimate. The set of pose solutions (the population) focuses on the most likely areas according to the perception and up to date motion information. The population evolves using the log-likelihood of each candidate pose according to the observation and the motion errors derived from the comparison between observed and predicted data obtained from the probabilistic perception and motion model.The proposed SLAM algorithm operates in two steps: in the first step the ELF filter is used at local level to re-localize the robot based on the robot odometry, the laser scan at a given position and a local map where only a low number of the last scans have been integrated. In the second step, the aligned laser measures and the corrected robot poses are used to detect whether the robot is revisiting a previously crossed area (i.e., a cycle in the robot trajectory exists). Once a cycle is detected, the Evolutive Localization Filter is used again to estimate the accumulated residual drift in the detected loop and then to re-estimate the robot poses in order to integrate the sensor measures in the global map of the environment.The algorithm has been tested in different environments to demonstrate the effectiveness, robustness and computational efficiency of the proposed approach.     

A study of co-occurrence based local features for camera model identification

Camera model identification has great relevance for many forensic applications, and is receiving growing attention in the literature. Virtually all techniques rely on the traces left in the image by the long sequence of in-camera processes which are specific of each model. They differ in the prior assumptions, if any, and in how such evidence is gathered in expressive features. In this work we study a class of blind features, based on the analysis of the image residuals of all color bands. They are extracted locally, based on co-occurrence matrices of selected neighbors, and then used to train a classifier. A number of experiments are carried out on the well-known Dresden Image Database. Besides the full-knowledge case, where all models of interest are known in advance, other scenarios with more limited knowledge and partially corrupted images are also investigated. Experimental results show these features to provide a state-of-the-art performance.     

Supporting Different Dimensions of Adaptability in Workflow Modeling

This paper discusses the theme of workflow systemadaptability in relation to process modeling. Startingfrom a discussion on the role of formal constructs incooperation, the main claim is that adaptabilityinvolves different dimensions of process modeling.These dimensions concern the possibility to flexiblycombine a rich set of basic categories in order toobtain the most suitable language for modeling thetarget business process and the work practices aroundit; to take into account various levels of visibilityof the contexts of definition and use of a processmodel; and finally to allow for temporary as well aspermanent modifications of the process itself.Ariadne, a notation conceived for the above purpose,is illustrated by means of a working example.Moreover, the paper presents the main designprinciples governing Ariadne's implementation.     

High-Energy Physics on the Grid: the ATLAS and CMS Experience

In this paper we present the experience of the ATLAS and CMS High-Energy Physics (HEP) experiments at the Large Hadron Collider (LHC) with the LCG/EGEE Grid infrastructure. The activity developed around the following two main lines: large-scale physics and detector simulations and end-user analysis. The LCG/EGEE Grid infrastructure offers a large amount of computing and storage resources and is growing very rapidly. It provides the natural environment for large-scale physics and detector simulations. Also, the analysis of these detector simulation data (and in the near future of the reconstructed data from physics collisions) requires efficient end-users access to Grid resources. In this paper, the main findings and lessons learned in terms of performance, robustness and scalability of the whole system are discussed in detail.     

Performance evaluation of semantic registries: OWLJessKB and instanceStore

Service discovery is a critical task in distributed computing architectures for finding a particular service instance. Semantic annotations of services help to enrich the service discovery process. Semantic registries are an important component for the discovery of services and they allow for semantic interoperability through ontology-based query formulation and dynamic mapping of terminologies between system domains. This paper evaluates two semantic registries—OWLJessKB implementation and instanceStore—to determine the suitability of these with regards to the query response time and the overall scalability for use in mathematical services. Mathematical ontologies from the MONET project are used to undertake comparison. The results demonstrate that the performance of registries may be compared across two axes: (1) time to initialize (i.e. time to load an initial ontology into memory); (2) time to query (i.e. time to reason with an ontology loaded into memory).     

Ab initio determination of heavy oxide perovskite related structures from precession electron diffraction data

Two complex perovskite-related structures were solved by ab initio from precession electron diffraction intensities. Structure models were firstly derived from HREM images and than have been confirmed independently using two and three-dimensional sets of precession intensities. Patterson techniques prove to be effective for ab initio structure resolution, specially in case of projections with no overlapping atoms. Quality of precession intensity data may be suitable enough to resolve unknown heavy oxide structures.     

Multi-product economic lot scheduling problem with manufacturing and remanufacturing using a basic period policy

In this research we study the multi-product Economic Lot Scheduling Problem (ELSP) with manufacturing and remanufacturing opportunities. Manufacturing and remanufacturing operations are performed on the same production line. Both manufactured and remanufactured products have the same quality thus they fulfil the same demand stream. Tang and Teunter (2006) firstly studied this type of Economic Lot Scheduling Problem with Returns (ELSPR) and presented a complex algorithm for the optimal solution. More recently Teunter, Tang, and Kaparis (2009) proposed several heuristics to deal with the same problem using more computational efficient approaches. However, both studies have limited the attention to the common cycle policy with the assumption that a single (re)manufacturing lot is used for each item in each cycle. Relaxing the constraint of common cycle time and a single (re)manufacturing lot for each item in each cycle, we propose a simple, easy to implement algorithm, based on Segerstedt (1999), to solve the model using a basic period policy. Several numerical examples show the applicability of the algorithm and the cost savings.     

Is cheating a human function? The roles of presence,state hostility,and enjoyment in an unfair video game

In sports and board games, when an opponent cheats, the other players typically greet it with disdain, anger, and disengagement. However, work has yet to fully address the role of the computer cheating in video games. In this study, participants played either a cheating or a non-cheating version of a modified open-source tower-defense game. Results indicate that when a computer competitor cheats, players perceive the opponent as being more human. Cheating also increases player aggravation and presence, but does not affect enjoyment of the experience. Additionally, players that firmly believed that their opponent was controlled by the computer exhibited significantly less state hostility compared to players that were less certain of the nature of their competitor. Game designers can integrate subtle levels of cheating into computer opponents without any real negative responses from the players. The results indicate that minor levels of cheating might also increase player engagement with video games.