Transparent Provenance Derivation for User Decisions

It is rare for data's history to include computational processes alone. Even when software generates data, users ultimately decide to execute software procedures, choose their configuration and inputs, reconfigure, halt and restart processes, and so on. Understanding the provenance of data thus involves understanding the reasoning of users behind these decisions, but demanding that users explicitly document decisions could be intrusive if implemented naively, and impractical in some cases. In this paper, therefore, we explore an approach to transparently deriving the provenance of user decisions at query time. The user reasoning is simulated, and if the result of the simulation matches the documented decision, the simulation is taken to approximate the actual reasoning. The plausibility of this approach requires that the simulation mirror human decision -making, so we adopt an automated process explicitly modelled on human psychology. The provenance of the decision is modelled in OPM, allowing it to be queried as part of a larger provenance graph, and an OPM profile is provided to allow consistent querying of provenance across user decisions.

Dynamically Adapting BDI Agent Architectures based on High-level User Specifications

Users are facing an increasing challenge of managing information and being available anytime anywhere, as the web exponentially grows. As a consequence, assisting them in their routine tasks has become a relevant issue to be addressed. In this paper, we introduce a software framework that supports the development of Personal Assistance Software (PAS). It relies on the idea of exposing a high level user model in order to increase user trust in the task delegation process as well as empowering them to manage it. The framework provides a synchronization mechanism that is responsible for dynamically adapting an underlying BDI agent-based running implementation in order to keep this high-level view of user customizations consistent with it.

Do virtual platforms impact user behavior? An experimental comparison between messages on the company's website and Facebook page.

Companies have looked for many new ways to communicate with their customers. In the current scenario, Facebook has proven to be an efficient communication tool between consumers and businesses. This study aims to understand the differences in the complaint messages sent to companies, through an experiment that measured the emotional tone and the lack of formality in each message received by the website and the Facebook page of the company. As expected, people are more informal on Facebook. However, contrary to our intuition, participants tended to display more emotions on the company website. The social norms theory and the impression management contributed to explain the phenomena found.

The impact of content marketing on attitudes and purchase intentions of online shoppers : the case videos & tutorials and user-generated content

This thesis was written as part of a Double-Degree Masters program in Management, with focus in Marketing. Aligned with the nature of the degree, this study aims to be a useful tool for managers and marketers, which conduct business online. This thesis is a study of Content Marketing in the content of online commercial product pages. Its aim is to understand how to use content marketing to drive conversion, by understanding consumer attitudes and purchase intention towards content. A in-depth study of existing theories and exploratory primary research was developed in other to attain these objectives. Business-to-consumer electronic commerce (B2C e-commerce) has provided consumers and online retailers with a more effective medium to perform online transactions through commercial websites. Although consumers have realized that the benefits of online shopping; such as time saving, minimizing effort, convenience, broader selection, and wider access to information, they are still greatly unwilling to shop online. Consumers shop essentially for two motives, to meet experiential (fun) or goal-oriented (efficiency) needs (Wolfinbarger & Gilly, 2001). The information provided by content marketing seeks to focus on consumers need for information and entertainment, instead of focusing on the brand. Thus, it is expected that the type of content format will have different effects on the attitudes and purchase intention on the online shopper, depending on the online shopping purpose. Concretely, a goal-oriented shopper should find user generated content (UGC) to be more valuable content formats, since they decrease the amount of search effort. While on the other hand, videos & tutorials (VT) might be perceived as more valuable for a consumer looking to spend time and being entertained through online shopping. The exploratory research was characterized by a survey experiment with online consumers. Participants were exposed to stimuli of content marketing tested according to their attitudes and purchase intention. The focus was to understand the impact of two different content marketing tactics—User-generated content and Videos & Tutorials—on attitudes and purchase intentions and how they interact with content complexity. The results indicate that content marketing in commercial product pages is relevant in driving consumer attitudes and purchase intentions. Consumers are not motivated by a specific content marketing tactic, unless that content has a certain level of complexity. In that case, Ur-Generated Content becomes a relevant tactic in product pages, however VT is not.

Object modeling for user-centered development and user interface design: the wisdom approach

João Bernardo de Sena Esteves Falcão e Cunha

Graphical constraints: a graphical user interface for constraint problems

A constraint satisfaction problem is a classical artificial intelligence paradigm characterized by a set of variables (each variable with an associated domain of possible values), and a set of constraints that specify relations among subsets of these variables. Solutions are assignments of values to all variables that satisfy all the constraints. Many real world problems may be modelled by means of constraints. The range of problems that can use this representation is very diverse and embraces areas like resource allocation, scheduling, timetabling or vehicle routing. Constraint programming is a form of declarative programming in the sense that instead of specifying a sequence of steps to execute, it relies on properties of the solutions to be found, which are explicitly defined by constraints. The idea of constraint programming is to solve problems by stating constraints which must be satisfied by the solutions. Constraint programming is based on specialized constraint solvers that take advantage of constraints to search for solutions. The success and popularity of complex problem solving tools can be greatly enhanced by the availability of friendly user interfaces. User interfaces cover two fundamental areas: receiving information from the user and communicating it to the system; and getting information from the system and deliver it to the user. Despite its potential impact, adequate user interfaces are uncommon in constraint programming in general. The main goal of this project is to develop a graphical user interface that allows to, intuitively, represent constraint satisfaction problems. The idea is to visually represent the variables of the problem, their domains and the problem constraints and enable the user to interact with an adequate constraint solver to process the constraints and compute the solutions. Moreover, the graphical interface should be capable of configure the solver’s parameters and present solutions in an appealing interactive way. As a proof of concept, the developed application – GraphicalConstraints – focus on continuous constraint programming, which deals with real valued variables and numerical constraints (equations and inequalities). RealPaver, a state-of-the-art solver in continuous domains, was used in the application. The graphical interface supports all stages of constraint processing, from the design of the constraint network to the presentation of the end feasible space solutions as 2D or 3D boxes.

Power flow for primary distribution networks considering uncertainty in demand and user connection

This paper presents a method for calculating the power flow in distribution networks considering uncertainties in the distribution system. Active and reactive power are used as uncertain variables and probabilistically modeled through probability distribution functions. Uncertainty about the connection of the users with the different feeders is also considered. A Monte Carlo simulation is used to generate the possible load scenarios of the users. The results of the power flow considering uncertainty are the mean values and standard deviations of the variables of interest (voltages in all nodes, active and reactive power flows, etc.), giving the user valuable information about how the network will behave under uncertainty rather than the traditional fixed values at one point in time. The method is tested using real data from a primary feeder system, and results are presented considering uncertainty in demand and also in the connection. To demonstrate the usefulness of the approach, the results are then used in a probabilistic risk analysis to identify potential problems of undervoltage in distribution systems. (C) 2012 Elsevier Ltd. All rights reserved.

An extended query-the-user tool for expert systems

An extended version of HIER, a query-the-user facility for expert systems is presented. HIER was developed to run over Prolog programs, and has been incorporated to systems that support the design of large and complex applications. The framework of the extended version is described,; as well as the major features of the implementation. An example is included to illustrate the use of the tool, involving the design of a specific database application.

User Manual for the Gender Equality Observatory for Latin America and the Caribbean

Includes bibliography

Module for the analysis of growth in international commerce (MAGIC Plus): user guide (updated)

Includes bibliography

LUTS: A lightweight user-level transaction scheduler

Software Transactional Memory (STM) systems have poor performance under high contention scenarios. Since many transactions compete for the same data, most of them are aborted, wasting processor runtime. Contention management policies are typically used to avoid that, but they are passive approaches as they wait for an abort to happen so they can take action. More proactive approaches have emerged, trying to predict when a transaction is likely to abort so its execution can be delayed. Such techniques are limited, as they do not replace the doomed transaction by another or, when they do, they rely on the operating system for that, having little or no control on which transaction should run. In this paper we propose LUTS, a Lightweight User-Level Transaction Scheduler, which is based on an execution context record mechanism. Unlike other techniques, LUTS provides the means for selecting another transaction to run in parallel, thus improving system throughput. Moreover, it avoids most of the issues caused by pseudo parallelism, as it only launches as many system-level threads as the number of available processor cores. We discuss LUTS design and present three conflict-avoidance heuristics built around LUTS scheduling capabilities. Experimental results, conducted with STMBench7 and STAMP benchmark suites, show LUTS efficiency when running high contention applications and how conflict-avoidance heuristics can improve STM performance even more. In fact, our transaction scheduling techniques are capable of improving program performance even in overloaded scenarios. © 2011 Springer-Verlag.

Is it possible to make pixel-based radar image classification user-friendly?

In this paper we would like to shed light the problem of efficiency and effectiveness of image classification in large datasets. As the amount of data to be processed and further classified has increased in the last years, there is a need for faster and more precise pattern recognition algorithms in order to perform online and offline training and classification procedures. We deal here with the problem of moist area classification in radar image in a fast manner. Experimental results using Optimum-Path Forest and its training set pruning algorithm also provided and discussed. © 2011 IEEE.

REDATAM: manual del usuario = REDATAM: user's manual

Incluye Bibliografía