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A Generic Software Framework for Car-Sharing Modelling based on a Large-Scale Multi-Agent Traffic Simulation Platform
No full textOver the last decade, numerous carsharing systems havebeen deployed around the world. Yet, despite this success, net profit margins of carsharing services are still insuffcient due to a complicated demand modelling and high expenses for fleet redistribution. To address these problems, different carsharing paradigms (e.g., one-way versus free oating), operational models and pricing schemes have been proposed. In order to assess the effectiveness of these models and strategies, realistic simulation tools are needed that account for the main parameters that affect system performance. To this end, we have developed ageneric software framework that caters for several avours of carsharingservices, such as hybrid systems where both one-way and free oatingmodes coexist. In addition, the proposed framework accounts for electric vehicles, power sharing capabilities, smart charging policies, booking services, fleet redistribution and membership management. Our tool is based on MATSim, an open-source platform for multi-agent traffic simulation.To validate our simulation model we will use a case study basedon data from the 2006 Lyon conurbation household travel survey, whichprovides information about more than three million trips
Text Encoder and Annotator: an all-in-one editor for transcribing and annotating manuscripts with RDF
No full textIn the context of the digitization of manuscripts, transcription and annotation are often distinct, sequential steps. This could lead to difficulties in improving the transcribed text when annotations have already been defined. In order to avoid this, we devised an approach which merges the two steps into the same process. Text Encoder and Annotator (TEA) is a prototype application embracing this concept. TEA is based on a lightweight language syntax which annotates text using Semantic Web technologies. Our approach is currently being developed within the Clavius on the Web project, devoted to studying the manuscripts of Christophorus Clavius, an influential 16th century mathematician and astronomer
MIB at SemEval-2016 Task 4a: Exploiting lexicon-based features for sentiment analysis in Twitter
No full textThis work presents our team solution for task 4a (Message Polarity Classification) at the SemEval 2016 challenge. Our experiments have been carried out over the Twitter dataset provided by the challenge. We follow a supervised approach, exploiting a SVM polynomial kernel classifier trained with the challenge data. The classifier takes as input advanced NLP features. This paper details the features and discusses the achieved results
Interference-aware Time-Based Fairness for Multihop Wireless Networks
No full textWe consider the problem of maximizing perfor- mance in multihop wireless networks while achieving fairness among flows. While time-based fairness has been widely rec- ognized as the appropriate fairness mechanism in single-hop wireless networks, no analogous notion has been developed for multihop wireless networks. We define the first general notion of time-based fairness for multihop networks by abstracting a net- work into a virtual single-hop network and applying the single- hop time-based fairness notion. This produces rate shares for each flow in the network, and we develop a constructive method for achieving these rate shares through physical-interference- aware scheduling. When combined with an appropriate link transmission policy, this scheduling approach preserves the time- based-fair rate shares for flows even with spatial reuse and the resulting rate reductions that occur among concurrent links. To our best knowledge, this is the first constructive approach for achieving fair rate shares in multihop wireless networks with or without interference consideration. We also prove that, with an appropriate scheduling algorithm, this approach produces an aggregate rate that is within a constant factor of the maximum aggregate rate subject to time-based fairness. Finally, we perform extensive simulations, which show that our approach as much as doubles the aggregate rate of a solution that approximates max- min fairness, while achieving a more natural fairness property
Journal of Limnology: of ancestors and descendants
No full textIn spite of the title, this is not the beginning of a long and boring family saga. I simply need to take a few minutes of your time to explain the history of this journal: where it is coming from, why it is changing and where it is going
Pavlovian-Instrumental transfer: computational models and function
No full textReward-related cues are an important part of our daily life as they often influence and guide our actions. This thesis focuses on one of the experimental paradigms used to study the effects of cues, the Pavlovian to Instrumental Transfer paradigm (PIT). In this paradigm, cues associated with rewards through Pavlovian conditioning alter motivation and choice of instrumental actions. During the last decade, the PIT effect - the influence of Pavlovian stimuli over instrumental actions - has been subdivided into two types: specifc PIT and general PIT, each having its own neural substrates. Specifc PIT happens when a conditioned stimulus (CS) associated with a reward enhances an instrumental response directed to the same reward. Under general PIT instead, the CS enhances a response directed to a different reward as well. While important progress has been made into identifying the neural substrates, the function of specifc and general PIT and how they interact with instrumental responses, are still not clear. In the experimental paradigm that distinguishes specifc and general PIT an effect of PIT inhibition has also been observed and is waiting for an explanation. In this thesis we propose an hypothesis that links these three PIT effects (specifc PIT, general PIT and PIT inhibition) to three aspects of action evaluation. These three aspects, which we call principles of action" are: context, efficacy, and utility. In goaldirected behaviour, an agent has to evaluate if the context is suitable to accomplish the goal, the efficacy of his action in getting the goal and the utility of the goal itself: we suggest that each of the three PIT effects is related to one of these aspects of action evaluation. In particular, we link specific PIT with the estimation of efficacy, general PIT with the evaluation of utility and PIT inhibition with the adequacy of context. We then provide a first computational model that exemplifies this hypothesis. The model is a Bayesian generative model with latent variables, based on a Bayesian understanding of conditioning that has been gaining grounds in the latest years. The underlying hypothesis is that animals learn hidden (latent) causes that jointly explain the co-occurrences of several observables (namely, sounds, levers, foods) { as opposed to learning simple associations between these events as more commonly assumed in the animal learning literature. In this scheme, PIT depends on Bayesian inference on the presence or absence of such hidden causes. We have then tested one part of our hypothesis and its predictions in a human behavioral experiment. In particular, we investigated the hypothesis that cues associated to an outcome elicit specific PIT by rising the estimates of reward probability of actions associated to that same outcome. In other words, cues reduce the uncertainty on the efficacy of instrumental actions. We used a human PIT experimental paradigm to test the effects of two different instrumental contingencies: one group of participants had a 33% chance of being rewarded for each button press, while another had a 100% chance. The group trained with 33% reward probability showed a stronger PIT effect than the 100% group, in line with the hypothesis that Pavlovian cues linked to an outcome work by reducing the uncertainty of receiving it. However, contrary to our prediction, the 100% group also showed a significant specific PIT effect, highlighting additional factors that could contribute to specifc PIT beyond the instrumental training contingency. In the last chapter, we developed a second Bayesian computational model on transfer, to account for the above experimental results. Compared to the previous model, this second model explicitly models Pavlovian and instrumental conditioning into two different components, arranged in a hierarchical fashion. We posited that the key link between the two components is the prediction of food availability by the Pavlovian process, which is then used by the instrumental process to determine which instrumental context is active and subsequently determine the best course of action. The model correctly reproduces the qualitative pattern of the behavioral experiment, albeit it is so far limited to specific transfer only
Effects of Spatiality on Value-Sensitive Decisions Made by Robot Swarms
No full textValue-sensitive decision-making is an essential task for organisms at all levels of biological complexity and consists of choosing options among a set of alternatives and being rewarded according to the quality value of the chosen op- tion. Provided that the chosen option has an above-threshold quality value, value- sensitive decisions are particularly relevant in case not all of the possible options are available at decision time. This means that the decision-maker may refrain from deciding until a sufficient-quality option becomes available. Value-sensitive collec- tive decisions are interesting for swarm robotics when the options are dispersed in space (e.g., resources in a foraging problem), and may be discovered at different times. However, current design methodologies for collective decision-making often assume a well-mixed system, and clever design workarounds are suggested to deal with a heterogeneous distribution of opinions within the swarm (e.g., due to spatial constraints on the interaction network). Here, we quantify the effects of spatiality in a value-sensitive decision problem involving a swarm of 150 kilobots. We present a macroscopic model of value-sensitive decision-making inspired by house-hunting honeybees, and implement a solution for both a multiagent system and a kilobot swarm. Notably, no workaround is implemented to deal with the spatial distribu- tion of opinions within the swarm. We show how the dynamics presented by the robotic system match or depart from the model predictions in both a qualitative and quantitative way as a result of spatial constraints
EMDR and CBT: A Comparative Clinical Study With Oncological Patients
No full textResearch in clinical psycho-oncology is becoming an area of key importance in investigating the effects of the interventions of support and/or psychotherapy with patients. This study was conducted with the aim of evaluating the effectiveness of the eye movement desensitization and reprocessing (EMDR) approach compared to a non-trauma-focused cognitive behavioral therapy (CBT) intervention. There were 11 male and 46 female participants, with mixed cancer diagnoses. Thirty-one subjects received EMDR therapy, and 26 received CBT for 12 sessions of 60 minutes each. The Symptom Checklist-90-R (SCL-90-R), COPE inventory, and Davidson Trauma Scale (DTS) were administered at three different times (T0, before intervention; T1, after the sixth session; and T2, after the 12th session); the Karnofsky Performance Status was administered at T0 only. In the EMDR group, a significant improvement was reported for the following 11 of the 17 dependent variables: COPE subscales, Avoidance Strategies and Positive Attitude; all three DTS subscales, Intrusion, Avoidance, and Hyperarousal; and 6 SCL-90-R subscales. In the CBT group, a significant improvement was reported for the following 4 of the 17 dependent variables: COPE subscales Positive Attitude and Transcendent Orientation; two DTS subscales, Intrusion, and Avoidance, with no improvement on any of the SCL-90-R subscales. This innovative study shows the value of trauma-focused treatment for patients with cancer and allows important preliminary suggestions on the usefulness of applying EMDR therapy in an oncological setting, although further research in this context is still needed
