Delay Indices for Train Punctuality

Indicators of expected quality of service in public contracts are often based on some kind of “punctuality”, usually defined in terms of the percentage of trains arriving at the final destination (and/or at intermediate significant stops) within a given delay. Passengers, however, tend to use the word “punctuality” with a more general meaning, mostly as a synonym for expected delay at their own destination, and especially in case of commuters are much less tolerant of even smaller delays than train operators would normally allow. In particular, measuring the delay only at the final destination is perceived as largely inadequate, leading to underestimation of the actual percentage of late trains, and in turn undermining passengers’ trust in official performance statistics. In this paper, we take the passengers’ perspective, introducing a family of delay indices called D-indices aimed at capturing the overall performance of a train “as a whole”, taking into account both the delays at the sampling points and the mutual location and order of such sampling points. In this paper, all indicators have the physical dimension of time in order to be easily replaceable to other delay measures. We first present typical approaches and definitions of punctuality in the literature, then introduce D-indices while exploring their features, pros and cons, and relevant properties. We validate and discuss our approach by comparing this model with existing approaches both theoretically and by comparison with selected datasets consisting of about one hundred trains transcribed over the last three years

tuProlog Manual

tuProlog is a light-weight Prolog system for distributed applications and infrastructures, intentionally designed around a minimal core extensible via libraries. tuProlog natively supports multi-paradigm programming, providing a clean, seamless integration model between Prolog and mainstream object-oriented languages -- namely Java, for tuProlog Java version, and any .NET-based language (C#, F#..), for tuProlog .NET version. This manual documents the tuProlog features as of version 3.

tuProlog Manual

tuProlog is a light-weight Prolog system for distributed applications and infrastructures, intentionally designed around a minimal core extensible via libraries. tuProlog natively supports multi-paradigm programming, providing a clean, seamless integration model between Prolog and mainstream object-oriented languages -- namely Java, for tuProlog Java version, and any .NET-based language (C#, F#..), for tuProlog .NET version. This manual documents the tuProlog features as of version 2.5

ANALYST RELUCTANCE IN CONVEYING NEGATIVE INFORMATION TO THE MARKET

This paper investigates one of the main sources of financial markets’ public information: financial analysts’ reports. We analyze reports on S&P 500 index through a multidisciplinary approach integrating behavioral finance with linguistic analysis to understand how financial phenomena reflect in or are deviated by language, i.e. whether financial and linguistic trends follow the same patterns, boosting each other, or diverge. In the latter, language could conceal financial events, mitigating analysts’ feelings and misleading investors. Therefore, we attempt to identify behavioral biases (mainly represented by cognitive dissonances) present in analysts’ reports. In doing so, we try to understand whether analysts try to hide perception of negative price-sensitive events or not, eventually anticipating and controlling the market “mood”. The study focuses on how analysts use linguistic strategies in order to minimize their risk of issuing wrong advice. Our preliminary results show reluctance to incorporate negative information in the reports. A slight asymmetry between the use of positive/negative keywords taken into account and the negative/positive trends of the index seems to emerge. In those weeks characterized by the index poor performances, the frequency of keywords with a negative meaning is lower. On the contrary, in the recovering weeks a higher use of keywords with a positive meaning does not clearly appear. A thorough investigation on the market moods, and the analysis of the text of the reports enable us to assess if and to what extent analysts have been willing to mitigate pessimism or emphasize confidence. Furthermore, we contribute to the existing literature also proposing a possible analysts’ value function based on the Prospect Theory [Kahneman and Tversky, 1979] where analysts try to maximize the value deriving from enhancing their reputation, taking into account the risks that may cause a reputational loss. This theoretical framework supports our preliminary findings and supports the idea that analysts are risk-averse when facing reputational gains and risk-seeking in case of potential reputational losses

Labelled variables in logic programming: Foundations

none4noWe define a new notion of truth for logic programs extended with labelled variables, interpreted in non-Herbrand domains. There, usual terms maintain their Herbrand interpretations, whereas diverse domain-specific computational models depending on the local situation of the computing device can be expressed via suitably-tailored labelled models. After some introductory examples, we define the theoretical model for labelled variables in logic programming (LVLP). Then, we present both the fixpoint and the operational semantics, and discuss their correctness and completeness, as well as their equivalence.openRoberta Calegari; Enrico Denti; Agostino Dovier; Andrea OmiciniRoberta Calegari; Enrico Denti; Agostino Dovier; Andrea Omicin

Privacy through Anonymisation in Large-scale Socio-technical Systems: Multi-lingual Contact Centres across the EU

Large-scale socio-technical systems (STS) inextricably interconnect individual – e.g., the right to privacy –, social – e.g., the effectiveness of organisational processes –, and technology issues —e.g., the software engineering process. As a result, the design of the complex software infrastructure involves also non-technological aspects such as the legal ones—so that, e.g., law-abidingness can be ensured since the early stages of the software engineering process. By focussing on contact centres (CC) as relevant examples of knowledge-intensive STS, we elaborate on the articulate aspects of anonymisation: there, individual and organisational needs clash, so that only an accurate balancing between legal and technical aspects could possibly ensure the system efficiency while preserving the individual right to privacy. We discuss first the overall legal framework, then the general theme of anonymisation in CC. Finally we overview the technical process developed in the context of the BISON project

Logic Programming as a Service (LPaaS): Intelligence for the IoT

The widespread diffusion of low-cost computing devices, such as Arduino boards and Raspberry Pi, along with improvements of Cloud computing platforms, are paving the way towards a whole new set of opportunities for Internet of Things (IoT) applications and services. Varying degrees of intelligence are often required for supporting adaptation and self-management—yet, they should be provided in a light-weight, easy to use and customise, highly-interoperable way. Accordingly, in this paper we explore the idea of Logic Programming as a Service (LPaaS) as a novel and promising re-interpretation of distributed logic programming in the IoT era. After introducing the reference context and motivating scenarios of LPaaS as a key enabling technology for intelligent IoT, we define the LPaaS general system architecture. Then, we present a prototype implementation built on top of the tuProlog system, which provides the required interoperability and customisation. We showcase the LPaaS potential through a case study designed as a simplification of the motivating scenarios

Logic-based Technologies for Intelligent Systems: State of the Art and Perspectives

Together with the disruptive development of modern sub-symbolic approaches to artificial intelligence (AI), symbolic approaches to classical AI are re-gaining momentum, as more and more researchers exploit their potential to make AI more comprehensible, explainable, and therefore trustworthy. Since logic-based approaches lay at the core of symbolic AI, summarizing their state of the art is of paramount importance now more than ever, in order to identify trends, benefits, key features, gaps, and limitations of the techniques proposed so far, as well as to identify promising research perspectives. Along this line, this paper provides an overview of logic-based approaches and technologies by sketching their evolution and pointing out their main application areas. Future perspectives for exploitation of logic-based technologies are discussed as well, in order to identify those research fields that deserve more attention, considering the areas that already exploit logic-based approaches as well as those that are more likely to adopt logic-based approaches in the future

Logic Programming in Space-Time: The Case of Situatedness in LPaaS

Situatedness is a fundamental requirement for today\u2019s complex software systems, as well as for the computational models and programming languages used to build them. Spatial and temporal situatedness, in particular, are essential features for AI, enabling actors of the system to take autonomous decisions contextual to the space-time they live in. To support spatio-temporal awareness in distributed pervasive systems, we adopt the standpoint of Logic Programming (LP) by focussing on the Logic Programming as a Service (LPaaS) approach, promoting the distribution of situated intelligence. Accordingly, we provide an interpretation about what it means to make LP span across space and time, then we extend the LPaaS model and architecture towards spatio-temporal situatedness, by identifying a set of suitably-expressive spatio-temporal primitives