Remembering as a mental action

Many philosophers consider that memory is just a passive information retention and retrieval capacity. Some information and experiences are encoded, stored, and subsequently retrieved in a passive way, without any control or intervention on the subject’s part. In this paper, we will defend an active account of memory according to which remembering is a mental action and not merely a passive mental event. According to the reconstructive account, memory is an imaginative reconstruction of past experience. A key feature of the reconstructive account is that given the imperfect character of memory outputs, some kind of control is needed. Metacognition is the control of mental processes and dispositions. Drawing from recent work on the normativity of automaticity and automatic control, we distinguish two kinds of metacognitive control: top-down, reflective control, on the one hand, and automatic, intuitive, feeling-based control on the other. Thus, we propose that whenever the mental process of remembering is controlled by means of intuitive or feeling-based metacognitive processes, it is an action

How to discriminate easily between Directed-percolation and Manna scaling

Here we compare critical properties of systems in the directed-percolation (DP) universality class with those of absorbing-state phase transitions occurring in the presence of a non-diffusive conserved field, i.e. transitions in the so-called Manna or C-DP class. Even if it is clearly established that these constitute two different universality classes, most of their universal features (exponents, moment ratios, scaling functions,...) are very similar, making it difficult to discriminate numerically between them. Nevertheless, as illustrated here, the two classes behave in a rather different way upon introducing a physical boundary or wall. Taking advantage of this, we propose a simple and fast method to discriminate between these two universality classes. This is particularly helpful in solving some existing discrepancies in self-organized critical systems as sandpiles.Comment: 7 Pages, 4 Figure

Framework to Enhance Teaching and Learning in System Analysis and Unified Modelling Language

Cowling, MA ORCiD: 0000-0003-1444-1563; Munoz Carpio, JC ORCiD: 0000-0003-0251-5510Systems Analysis modelling is considered foundational for Information and Communication Technology (ICT) students, with introductory and advanced units included in nearly all ICT and computer science degrees. Yet despite this, novice systems analysts (learners) find modelling and systems thinking quite difficult to learn and master. This makes the process of teaching the fundamentals frustrating and time intensive. This paper will discuss the foundational problems that learners face when learning Systems Analysis modelling. Through a systematic literature review, a framework will be proposed based on the key problems that novice learners experience. In this proposed framework, a sequence of activities has been developed to facilitate understanding of the requirements, solutions and incremental modelling. An example is provided illustrating how the framework could be used to incorporate visualization and gaming elements into a Systems Analysis classroom; therefore, improving motivation and learning. Through this work, a greater understanding of the approach to teaching modelling within the computer science classroom will be provided, as well as a framework to guide future teaching activities

Electoral systems and pork barrel politics: Evidence from Honduras

Can electoral systems determine how particularistic spending is distributed in developing countries? The ways in which legislators seek benefits for their constituencies, have been the subject of longstanding debate in political science. While the discussion has broadly focused on the theoretical consequences of electoral systems on legislators’ behaviour, little evidence has accounted for these alleged effects, especially in developing country settings. This paper focuses on particularistic spending in Honduras, providing a natural experiment to test different relevant hypotheses found in the literature. Since the early 1980s Honduras used a closed-list ballot with single-member and plurinominal districts electoral system. In 2004 the country moved to an open ballot structure keeping the same range of district magnitude. On the basis of original data from the Honduran Social Investment Fund, a battery of statistical tests is conducted. It is expected that under a closed-list system social spending per capita will increase as district magnitude shrinks, and the opposite will happen when an open-list system is in use. The evidence suggests that the change from a closed-list to an open-list system causes an increase in spending per capita. However, the interaction of type of ballot with district magnitude does not produce the results predicted by influential theories

Collaborative Appearance-Based Place Recognition and Improving Place Recognition Using Detection of Dynamic Objects

This dissertation makes contributions to the problem of Long-Term Appearance-Based Place Recognition. We present a framework for place recognition in a collaborative scheme and a method to reduce the impact of dynamic objects on place representations. We demonstrate our findings using a state-of-the-art place recognition approach. We begin in Part I by describing the general problem of place recognition and its importance in applications where accurate localization is crucial. We discuss feature detection and description and also explain the functioning of several place recognition frameworks. In Part II, we present a novel framework for collaboration between agents from a pure appearance-based place recognition perspective. Using this framework, multiple agents can efficiently share partial or complete knowledge about places and benefit from their teamwork. This collaborative framework allows agents with limited storage and memory capacity to become useful in environment exploration tasks (for instance, by enabling remote recognition); includes procedures to manage an agent’s memory load and distributes knowledge of places across agents; allows the reuse of knowledge from one agent to another; and increases the tolerance for failure of individual agents. Part II also defines metrics which allow us to measure the performance of a system that uses the collaborative framework. Finally, in Part III, we present an innovative method to improve the recognition of places in environments densely populated by dynamic objects. We demonstrate that we can improve the recognition performance in these environments by incorporating high- level information from dynamic objects. Tests conducted using a synthetic dataset show the benefits of our approach. The proposed method allows the system to significantly improve the recognition performance in the photo-realistic dataset while reducing storage requirements, resulting in up to 23.7 percent less storage space than the state-of-the-art approach that we have extended; smaller representations also reduced the time required to match places. In Part III, we also formulate the concept of a valid place representation and determine the quality of the observation based on dynamic objects present in the agent’s view. Of course, recognition systems that are sensitive to dynamic objects incur additional computational costs to recognize those objects. We show that this additional cost is outweighed by the benefits that incorporating dynamic object detection in the place recognition pipeline. Our findings can be used in many applications, including applications for navigation, e.g. assisting visually impaired individuals with navigating indoors, or autonomous vehicles

"The War for the Fare": How Driver Compensation Affects Bus System Performance

Two systems of bus driver compensation exist in Santiago, Chile. Most drivers are paid per passenger transported, while a second system compensates other drivers with a fixed wage. Compared with fixed-wage drivers, per-passenger drivers have incentives to engage in "La Guerra por el Boleto" ("The War for the Fare"), in which drivers change their driving patterns to compete for passengers. This paper takes advantage of a natural experiment provided by the coexistence of these two compensation schemes on similar routes in the same city. Using data on intervals between bus arrivals, we find that the fixed-wage contract leads to more bunching of buses, and hence longer average passenger wait times. The per-passenger drivers are assisted by a group of independent information intermediaries called "sapos" who earn their living by standing at bus stops, recording arrival times, and selling the information to subsequent drivers who drive past. We find that a typical bus passenger in Santiago waits roughly 10% longer for a bus on a fixed-wage route relative to an incentive-contract route. However, the incentives also lead drivers to drive noticeably more aggressively, causing approximately 67% more accidents per kilometer driven. Our results have implications for the design of incentives in public transportation systems.