Internet Giants as Quasi-Governmental Actors and the Limits of Contractual Consent

Although the government’s data-mining program relied heavily on information and technology that the government received from private companies, relatively little of the public outrage generated by Edward Snowden’s revelations was directed at those private companies. We argue that the mystique of the Internet giants and the myth of contractual consent combine to mute criticisms that otherwise might be directed at the real data-mining masterminds. As a result, consumers are deemed to have consented to the use of their private information in ways that they would not agree to had they known the purposes to which their information would be put and the entities – including the federal government – with whom their information would be shared. We also call into question the distinction between governmental actors and private actors in this realm, as the Internet giants increasingly exploit contractual mechanisms to operate with quasi-governmental powers in their relations with consumers. As regulators and policymakers focus on how to better protect consumer data, we propose that solutions that rely upon consumer permission adopt a more exacting and limited concept of the consent required before private entities may collect or make use of consumer’s information where such uses touch upon privacy interests

Experiences In Migrating An Industrial Application To Aspects

Aspect-Oriented Software Development (AOSD) is a paradigm aiming to solve problems of object-oriented programming (OOP). With normal OOP it’s often unlikely to accomplish fine system modularity due to crosscutting concerns being scattered and tangled throughout the system. AOSD resolves this problem by its capability to crosscut the regular code and as a consequence transfer the crosscutting concerns to a single model called aspect. This thesis describes an experiment on industrial application wherein the effectiveness of aspect-oriented techniques is explained in migration the OOP application into aspects. The experiment goals at first to identify the crosscutting concerns in source code of the industrial application and transform these concerns to a functionally equivalent aspect-oriented version. In addition to presenting experiences gained through the experiment, the thesis aims to provide practical guidance of aspect solutions in a real application

Festival Spaces and the Visitor Experience

A festival implies a special use of space for both the organiser and the visitor. On the practical level of events management, it is a series of temporary per - formance venues presenting special organisational problems. For the festivalgoers, it is a space set apart to which they come seeking an extraordinary experience. This experience can have an emotional and symbolic significance, which they then come to associate with the place itself. For this reason, festivals and special events are increasingly used as part of strategies to regenerate or reposition urban areas or coastal resorts. Events attract additional visitors, creating economic benefits for retail, leisure and other businesses. The publicity can be used for place marketing aimed not only at attracting visitors but also new businesses and investment to the area (Jago et al., 2003; Morgan et al, 2002). They can also give a boost to the cultural or sporting life of the residents and increase local pride and selfesteem. Festivals are part of the area’s ‘experience economy’ to use Pine and Gilmore’s (1999) term, creating a temporary ‘creative space’ which can attract visitors (Richards and Wilson, 2006). But how should that space be designed to optimise the experience of the festival-goers and contribute to the success of the event? Answering this question requires an awareness of how festival-goers perceive the impact of the location and its layout on their enjoyment of the event. The role of space can best be explored within a wider conceptual framework that maps the visitor experience of the event. This chapter is based on research into the 2005 Sidmouth Folk Festival, a long-established event which saw a significant change in ownership and organisation from previous years. This sparked a lengthy discussion on an enthusiasts’ internet message board about how successful it had been. One aspect of this was the rival merits of a festival based in a showground and one spread over existing venues around the town. An analysis of these discussions was used to explore the elements of the event experience and the ways in which festival-goers evaluate i

Weka: A machine learning workbench for data mining

The Weka workbench is an organized collection of state-of-the-art machine learning algorithms and data preprocessing tools. The basic way of interacting with these methods is by invoking them from the command line. However, convenient interactive graphical user interfaces are provided for data exploration, for setting up large-scale experiments on distributed computing platforms, and for designing configurations for streamed data processing. These interfaces constitute an advanced environment for experimental data mining. The system is written in Java and distributed under the terms of the GNU General Public License

Movie Popularity Classification based on Inherent Movie Attributes using C4.5,PART and Correlation Coefficient

Abundance of movie data across the internet makes it an obvious candidate for machine learning and knowledge discovery. But most researches are directed towards bi-polar classification of movie or generation of a movie recommendation system based on reviews given by viewers on various internet sites. Classification of movie popularity based solely on attributes of a movie i.e. actor, actress, director rating, language, country and budget etc. has been less highlighted due to large number of attributes that are associated with each movie and their differences in dimensions. In this paper, we propose classification scheme of pre-release movie popularity based on inherent attributes using C4.5 and PART classifier algorithm and define the relation between attributes of post release movies using correlation coefficient.Comment: 6 page

Geometric reasoning via internet crowdsourcing

The ability to interpret and reason about shapes is a peculiarly human capability that has proven difficult to reproduce algorithmically. So despite the fact that geometric modeling technology has made significant advances in the representation, display and modification of shapes, there have only been incremental advances in geometric reasoning. For example, although today's CAD systems can confidently identify isolated cylindrical holes, they struggle with more ambiguous tasks such as the identification of partial symmetries or similarities in arbitrary geometries. Even well defined problems such as 2D shape nesting or 3D packing generally resist elegant solution and rely instead on brute force explorations of a subset of the many possible solutions. Identifying economic ways to solving such problems would result in significant productivity gains across a wide range of industrial applications. The authors hypothesize that Internet Crowdsourcing might provide a pragmatic way of removing many geometric reasoning bottlenecks.This paper reports the results of experiments conducted with Amazon's mTurk site and designed to determine the feasibility of using Internet Crowdsourcing to carry out geometric reasoning tasks as well as establish some benchmark data for the quality, speed and costs of using this approach.After describing the general architecture and terminology of the mTurk Crowdsourcing system, the paper details the implementation and results of the following three investigations; 1) the identification of "Canonical" viewpoints for individual shapes, 2) the quantification of "similarity" relationships with-in collections of 3D models and 3) the efficient packing of 2D Strips into rectangular areas. The paper concludes with a discussion of the possibilities and limitations of the approach