Designing for User Confidence in Intelligent Environments

Intelligent environments aim at supporting and assisting users in their daily activities. Their reliability, i.e., the capability of correctly accomplishing the intended tasks and of limiting or avoiding damage in case of malfunctions, is essential as for any user-facing technology. One aspect of reliability, often neglected, is guaranteeing the consistency between system operation and user expectations, so that users may build confidence over the correct behavior of the system and its reaction to their actions. The paper will review the literature concerning methodologies and tools that directly involve users and have been specifically applied or adopted for intelligent environments, throughout the entire design flow – from requirements gathering to interface design. The paper will then propose, building on top of the previous analysis, a set of guidelines that system designers should follow to ensure user confidence in their intelligent environments

The Emerging Philippine Investment Environment

The change in the country’s investment policies has been a crucial factor in building up confidence in the country’s economic prospects. Despite the reforms undertaken, the country’s performance in attracting foreign direct investment is still lower than its neighboring countries. This paper examines the factors that determine the foreign direct investment (FDI) and its behavior over time. It also analyzes the effectiveness of the Philippine incentive system particularly in the firms from the export processing and special economic zones.investment opportunities, investment incentive system

Supporting the migration towards model-driven robotic systems

Robots are increasingly deployed to perform every-day tasks. It is crucial to implement reliable and reusable systems to reduce development effort. The complexity of robotic systems requires the collaboration of experts from different backgrounds. Therefore, clear and communicatable abstraction of components is essential for successful development process. There has been a demand in the community for increased adoption of software engineering approaches to support better robotic systems. Adopting model-driven approaches has been proved successful in supporting this movement. We aim to support the adaptation of model-driven approaches in robotic domain in three interest areas: behavior models, structural models and guaranteeing confidence in system behavior.The overall goal is to support the creation of reusable, verifiable and easy to communicate robotic missions and systems. To achieve that, we conducted a mix of knowledge-seeking and solution-seeking studies. We started with behavior models. We wanted to build knowledge about used behavior models in practice. We investigated the state-of-practice of an emerging behavior model, behavior trees, in comparison to two standardized UML models and a traditional roboticists choice. Moving to the second interest area, we wanted to support the creation of light-weight tools for building an understanding of system structure using feature models. We conducted a pilot evaluation of an already light-weight tool, called FeatureVista. The final interest area was guaranteeing confidence in system behavior. The usual engineering process of self-adaptive controllers in robotic involves different model-based approaches. We wanted to investigate an approach that reaffirm, at code-level, control properties while keeping the usual engineering process. We investigated an approach for mapping control properties to software ones using an appropriate input format for software model-based checking.Our investigations in the different interest areas have built knowledge and shed light on opportunities. We provided characteristics of behavior models, behavior trees and state machines, in popular robotic implementations and highlighted opportunities for improvements. We also provided usage trend for studied implementations in open-source projects. In addition, we provided corestructural characteristic and code-reuse patterns for studied behavior models in open-source projects. For feature models, our results showed promising results for using an interactive tool that provides an easy and initiative navigation between feature models and software components. Improvement aspects were also highlighted for developing similar tools. Finally, our work for the confidence of system behavior showed promising results in reaffirming the correctness of a control property at code-level using appropriate software notation, specification patterns. Also, our approach allowed keeping the current practices of using model-based approaches in self-adaptive robotic systems

Like Me, Do What I Say, & Think About My Influence: The Effects on Witness Choosing and Metacognition

Confidence can be a strong predictor of accuracy if circumstances are ideal (Wixted & Wells, 2017), but ideal circumstances are not always present. As such it is important to understand ways to ameliorate potentially negative effects on eyewitness metacognition. Rapport building, though seen as an important element of police/witness interaction (Vallano et al., 2015), can lead to some potentially negative memory effects (Wright et al., 2015). Additionally steering, or the process of directing a witness toward a particular suspect, can increase false identifications. Recently the researcher has developed a paradigm meant to better calibrate confidence by reinstating the context of making the identification decision. All of these variables were examined with their relation to choosing behavior and self reports of confidence in choosing. Rapport did not significantly affect anything. Steering increased the likelihood of choosing the designated suspect and decreased confidence in decisions. All of the variables interacted providing the most confidence in those who underwent the novel paradigm, had positive rapport, had not been steered, and correctly identified the guilty suspect. The implications of this research both in terms of the greater eyewitness literature and in terms of the effects on the judicial system are discussed

Benchmarking of localization solutions : guidelines for the selection of evaluation points

Indoor localization solutions are key enablers for next-generation indoor navigation and track and tracing solutions. As a result, an increasing number of different localization algorithms have been proposed and evaluated in scientific literature. However, many of these publications do not accurately substantiate the used evaluation methods. In particular, many authors utilize a different number of evaluation points, but they do not (i) analyze if the number of used evaluation points is sufficient to accurately evaluate the performance of their solutions and (ii) report on the uncertainty of the published results. To remedy this, this paper evaluates the influence of the selection of evaluation points. Based on statistical parameters such as the standard error of the mean value, an estimator is defined that can be used to quantitatively analyze the impact of the number of used evaluation points on the confidence interval of the mean value of the obtained results. This estimator is used to estimate the uncertainty of the presented accuracy results, and can be used to identify if more evaluations are required. To validate the proposed estimator, two different localization algorithms are evaluated in different testbeds and using different types of technology, showing that the number of required evaluation points does indeed vary significantly depending on the evaluated solution. (C) 2017 Elsevier B.V. All rights reserved

Trust Based Participant Driven Privacy Control in Participatory Sensing

Widespread use of sensors and multisensory personal devices generate a lot of personal information. Sharing this information with others could help in various ways. However, this information may be misused when shared with all. Sharing of information between trusted parties overcomes this problem. This paper describes a model to share information based on interactions and opinions to build trust among peers. It also considers institutional and other controls, which influence the behaviour of the peers. The trust and control build confidence. The computed confidence bespeaks whether to reveal information or not thereby increasing trusted cooperation among peers.Comment: 14 page