A new online updating framework for constructing monotonicity-preserving fuzzy inference systems

In this paper, a new online updating framework for constructing monotonicity-preserving Fuzzy Inference Systems (FISs) is proposed. The framework encompasses an optimization-based Similarity Reasoning (SR) scheme and a new monotone fuzzy rule relabeling technique. A complete and monotonically-ordered fuzzy rule base is necessary to maintain the monotonicity property of an FIS model. The proposed framework attempts to allow a monotonicity-preserving FIS model to be constructed when the fuzzy rules are incomplete and not monotonically-ordered. An online feature is introduced to allow the FIS model to be updated from time to time. We further investigate three useful measures, i.e., the belief, plausibility, and evidential mass measures, which are inspired from the Dempster- Shafer theory of evidence, to analyze the proposed framework and to give an insight for the inferred outcomes from the FIS model.

Updating RIGs : including the systematic influence of online study on student evaluation of teaching

Based on student evaluation of teaching (SET) ratings from 1,432 units of study over a period of a year, representing 74,490 individual sets of ratings, and including a significant number of units offered in wholly online mode, we confirm the significant influence of class size, year level, and discipline area on at least some SET ratings. We also find online mode of offer to significantly influence at least some SET ratings. We reveal both the statistical significance and effect sizes of these influences, and find that the magnitudes of the effect sizes of all factors are small, but potentially cumulative. We also show that the influence of online mode of offer is of the same magnitude as the other 3 factors. These results support and extend the rating interpretation guides (RIGs) model proposed by Neumann and colleagues, and we present a general method for the development of a RIGs system.

Online multiple classifier boosting for object tracking

This paper presents a new online multi-classifier boosting algorithm for learning object appearance models. In many cases the appearance model is multi-modal, which we capture by training and updating multiple strong classifiers. The proposed algorithm jointly learns the classifiers and a soft partitioning of the input space, defining an area of expertise for each classifier. We show how this formulation improves the specificity of the strong classifiers, allowing simultaneous location and pose estimation in a tracking task. The proposed online scheme iteratively adapts the classifiers during tracking. Experiments show that the algorithm successfully learns multi-modal appearance models during a short initial training phase, subsequently updating them for tracking an object under rapid appearance changes. © 2010 IEEE.

Regularized Online Mixture of Gaussians for Background Subtraction

Mixture of Gaussians (MoG) modelling [13] is a popular approach to background subtraction in video sequences. Although the algorithm shows good empirical performance, it lacks theoretical justification. In this paper, we give a justification for it from an online stochastic expectation maximization (EM) viewpoint and extend it to a general framework of regularized online classification EM for MoG with guaranteed convergence. By choosing a special regularization function, l1 norm, we derived a new set of updating equations for l1 regularized online MoG. It is shown empirically that l1 regularized online MoG converge faster than the original online MoG .

Fair Copyright for Canada: Lessons for Online Social Movements from the First Canadian Facebook Uprising

Despite their growing importance, the political effectiveness of social media remains understudied. Drawing on and updating resource mobilization theory and political process theory, this article considers how social media make “political engagement more probable,” and the determinants of success for online social movements. It does so by examining the mainstreaming of the Canadian “user rights” copyright movement, focusing on the Fair Copyright for Canada Facebook page, created in December 2007. This decentralized, grassroots, social media-focused action – the first successful campaign of its kind in Canada and one of the first in the world – changed the terms of the Canadian copyright debate and legitimized Canadian user rights. As this case demonstrates, social media have changed the type and amount of resources needed to create and sustain social movements, creating openings for new groups and interests. Their success, however, remains dependent on the political context within which they operate.

Online blind source separation using incremental nonnegative matrix factorization with volume constraint

Online blind source separation (BSS) is proposed to overcome the high computational cost problem, which limits the practical applications of traditional batch BSS algorithms. However, the existing online BSS methods are mainly used to separate independent or uncorrelated sources. Recently, nonnegative matrix factorization (NMF) shows great potential to separate the correlative sources, where some constraints are often imposed to overcome the non-uniqueness of the factorization. In this paper, an incremental NMF with volume constraint is derived and utilized for solving online BSS. The volume constraint to the mixing matrix enhances the identifiability of the sources, while the incremental learning mode reduces the computational cost. The proposed method takes advantage of the natural gradient based multiplication updating rule, and it performs especially well in the recovery of dependent sources. Simulations in BSS for dual-energy X-ray images, online encrypted speech signals, and high correlative face images show the validity of the proposed method.

Cultural Protectionism 2.0 : Updating Cultural Policy Tools for the Digital Age

This chapter explores cultural protectionism 2.0, i.e. the normative dimensions of cultural diversity policies in the global digital space, asking what adjustments are needed and in fact, how feasible the entire project of diversity regulation in this environment may be. The complexities of the shift from offline to online and from analogue to digital, and the inherent policy challenges are illustrated with some (positive and negative) instances of existing media initiatives. Taking into account the specificities of cyberspace and in a forward-looking manner, the chapter suggests some adjustments to current media policy practices in order to better serve the goal of sustainably diverse cultural environment.

FORA - A Fuzzy Set Based Framework for Online Reputation Management

The Social Web offers increasingly simple ways to publish and disseminate personal or opinionated information, which can rapidly exhibit a disastrous influence on the online reputation of organizations. Based on social Web data, this study describes the building of an ontology based on fuzzy sets. At the end of a recurring harvesting of folksonomies by Web agents, the aggregated tags are purified, linked, and transformed to a so-called fuzzy grassroots ontology by means of a fuzzy clustering algorithm. This self-updating ontology is used for online reputation analysis, a crucial task of reputation management, with the goal to follow the online conversation going on around an organization to discover and monitor its reputation. In addition, an application of the Fuzzy Online Reputation Analysis (FORA) framework, lesson learned, and potential extensions are discussed in this article.

Updating the marine biostratigraphy of the Granada Basin (central Betic Cordillera). Insight for the Late Miocene palaeogeographic evolution of the Atlantic – Mediterranean seaway

The marine stratigraphic record of the Granada Basin (central Betic Cordillera, Spain) is composed of three Late Miocene genetic units deposited in different sea-level contexts (from base to top): Unit I (sea-level rise), Unit II (high sea-level), and Unit III (low sea-level). The latter mainly consists of evaporites precipitated in a shallow-basin setting. Biostratigraphic analyses based on planktonic foraminifera and calcareous nannoplankton indicate four late Tortonian bioevents (PF1-CN1, PF2, PF3, and PF4), which can be correlated with astronomically-dated events in other sections of the Mediterranean. PF1-CN1 (7.89 Ma) is characterized by the influx of the Globorotalia conomiozea group (including typical forms of Globorotalia mediterranea) and by the first common occurrence of Discoaster surculus; PF2 (7.84 Ma) is marked by the first common occurrence of Globorotalia suterae; PF3 (7.69 Ma) is typified by the influx of dextral Neogloboquadrina acostaensis; and PF4 (7.37 Ma) is defined by the influx of the Globorotalia menardii group II (dextral forms). The PF1 event occurred in the upper part of Unit I, whereas PF2 to PF4 events occurred successively within Unit II. The age of Unit III (evaporites) can only be estimated in its lower part based on the presence of dextral Globorotalia scitula, which, together with the absence of the first common occurrence of the G. conomiozea group (7.24 Ma), points to the latest Tortonian. Comparisons with data from the other Betic basins indicate that the evaporitic phase of the Granada Basin (7.37–7.24 Ma) is not synchronous with those from the Lorca Basin (7.80 Ma) and the Fortuna Basin (7.6 Ma). In the Bajo Segura Basin (easternmost Betic Cordillera), no evaporite deposition occurred during the late Tortonian. The evaporitic unit of the Granada Basin (central Betics) records the late Tortonian restriction of the Betic seaway (the marine connection between the Atlantic and Mediterranean). The diachrony in the restriction of the Betic seaway is related to differing tectonic movements in the central and eastern sectors of the Betic Cordillera.

AN EMPIRICAL ASSESSMENT OF USER ONLINE SECURITY BEHAVIOR: EVIDENCE FROM A UNIVERSITY

The ever-increasing number and severity of cybersecurity breaches makes it vital to understand the factors that make organizations vulnerable. Since humans are considered the weakest link in the cybersecurity chain of an organization, this study evaluates users’ individual differences (demographic factors, risk-taking preferences, decision-making styles and personality traits) to understand online security behavior. This thesis studies four different yet tightly related online security behaviors that influence organizational cybersecurity: device securement, password generation, proactive awareness and updating. A survey (N=369) of students, faculty and staff in a large mid-Atlantic U.S. public university identifies individual characteristics that relate to online security behavior and characterizes the higher-risk individuals that pose threats to the university’s cybersecurity. Based on these findings and insights from interviews with phishing victims, the study concludes with recommendations to help similat organizations increase end-user cybersecurity compliance and mitigate the risks caused by humans in the organizational cybersecurity chain.