Effectiveness of combined sharing and freeness analysis using abstract interpretation

This paper presents improved unification algorithms, an implementation, and an analysis of the effectiveness of an abstract interpreter based on the sharing + freeness domain presented in a previous paper, which was designed to accurately and concisely represent combined freeness and sharing information for program variables. We first briefly review this domain and the unification algorithms previously proposed. We then improve these algorithms and correct them to deal with some cases which were not well analyzed previously, illustrating the improvement with an example. We then present the implementation of the improved algorithm and evaluate its performance by comparing the effectiveness of the information inferred to that of other interpreters available to us for an application (program parallelization) that is common to all these interpreters. All these systems have been embedded in a real parallelizing compiler. Effectiveness of the analysis is measured in terms of actual final performance of the system: i.e. in terms of the actual speedups obtained. The results show good performance for the combined domain in that it improves the accuracy of both types of information and also in that the analyzer using the combined domain is more effective in the application than any of the other analyzers it is compared to.

The morphofunctional approach to emotion modelling in robotics

In this conceptual paper, we discuss two areas of research in robotics, robotic models of emotion and morphofunctional machines, and we explore the scope for potential cross-fertilization between them. We shift the focus in robot models of emotion from information-theoretic aspects of appraisal to the interactive significance of bodily dispositions. Typical emotional phenomena such as arousal and action readiness can be interpreted as morphofunctional processes, and their functionality may be replicated in robotic systems with morphologies that can be modulated for real-time adaptation. We investigate the control requirements for such systems, and present a possible bio-inspired architecture, based on the division of control between neural and endocrine systems in humans and animals. We suggest that emotional epi- sodes can be understood as emergent from the coordination of action control and action-readiness, respectively. This stress on morphology complements existing research on the information-theoretic aspects of emotion.

Contribution sharing of a fuel mixture components to the fuel cell potencial of a direct alcohol fuel cell

The increasing worldwide demand for electricity impels to develop clean and renewable energy resources. In the field of portable power devices not only size and weight represent important aspects to take into account, but the fuel and its storage are also critical issues to consider. In this last sense, the direct methanol (MeOH) fuel cells (DMFC) play an important role as they can offer high power and energy density, low emissions, ambient operating conditions and fast and convenient refuelling.

Short paper: From streaming data to linked data. A case study with bike sharing systems

Current methods and tools that support Linked Data publication have mainly focused so far on static data, without considering the growing amount of streaming data available on the Web. In this paper we describe a case study that involves the publication of static and streaming Linked Data for bike sharing systems and related entities. We describe some of the challenges that we have faced, the solutions that we have explored, the lessons that we have learned, and the opportunities that lie in the future for exploiting Linked Stream Data.

A sharing-based approach to supporting adaptation in service compositions

Data-related properties of the activities involved in a service composition can be used to facilitate several design-time and run-time adaptation tasks, such as service evolution, distributed enactment, and instance-level adaptation. A number of these properties can be expressed using a notion of sharing. We present an approach for automated inference of data properties based on sharing analysis, which is able to handle service compositions with complex control structures, involving loops and sub-workflows. The properties inferred can include data dependencies, information content, domain-defined attributes, privacy or confidentiality levels, among others. The analysis produces characterizations of the data and the activities in the composition in terms of minimal and maximal sharing, which can then be used to verify compliance of potential adaptation actions, or as supporting information in their generation. This sharing analysis approach can be used both at design time and at run time. In the latter case, the results of analysis can be refined using the composition traces (execution logs) at the point of execution, in order to support run-time adaptation.

A linked data approach to sentiment and emotion analysis of twitter in the financial domain

Sentiment analysis has recently gained popularity in the financial domain thanks to its capability to predict the stock market based on the wisdom of the crowds. Nevertheless, current sentiment indicators are still silos that cannot be combined to get better insight about the mood of different communities. In this article we propose a Linked Data approach for modelling sentiment and emotions about financial entities. We aim at integrating sentiment information from different communities or providers, and complements existing initiatives such as FIBO. The ap- proach has been validated in the semantic annotation of tweets of several stocks in the Spanish stock market, including its sentiment information.

Reviewing technical approaches for sharing and preservation of experimental data

Empirical Software Engineering (ESE) replication researchers need to store and manipulate experimental data for several purposes, in particular analysis and reporting. Current research needs call for sharing and preservation of experimental data as well. In a previous work, we analyzed Replication Data Management (RDM) needs. A novel concept, called Experimental Ecosystem, was proposed to solve current deficiencies in RDMapproaches. The empirical ecosystem provides replication researchers with a common framework that integrates transparently local heterogeneous data sources. A typical situation where the Empirical Ecosystem is applicable, is when several members of a research group, or several research groups collaborating together, need to share and access each other experimental results. However, to be able to apply the Empirical Ecosystem concept and deliver all promised benefits, it is necessary to analyze the software architectures and tools that can properly support it.

Onyx: A Linked Data approach to emotion representation

Extracting opinions and emotions from text is becoming increasingly important, especially since the advent of micro-blogging and social networking. Opinion mining is particularly popular and now gathers many public services, datasets and lexical resources. Unfortunately, there are few available lexical and semantic resources for emotion recognition that could foster the development of new emotion aware services and applications. The diversity of theories of emotion and the absence of a common vocabulary are two of the main barriers to the development of such resources. This situation motivated the creation of Onyx, a semantic vocabulary of emotions with a focus on lexical resources and emotion analysis services. It follows a linguistic Linked Data approach, it is aligned with the Provenance Ontology, and it has been integrated with the Lexicon Model for Ontologies (lemon), a popular RDF model for representing lexical entries. This approach also means a new and interesting way to work with different theories of emotion. As part of this work, Onyx has been aligned with EmotionML and WordNet-Affect.

Linked Data for sharing, discovery and re-use of Language Resources at a Web scale

Conferencia por invitación, impartida el 31 d mayo de 2014 en el Workshop on Language Technology Service Platforms: Synergies, Standards, Sharing at LREC2014

Analysis of the Optimal Sharing of Construction Risk in Public Procurement Contracts

This paper discusses a model based on the agency theory to analyze the optimal transfer of construction risk in public works contracts. The base assumption is that of a contract between a principal (public authority) and an agent (firm), where the payment mechanism is linear and contains an incentive mechanism to enhance the effort of the agent to reduce construction costs. A theoretical model is proposed starting from a cost function with a random component and assuming that both the public authority and the firm are risk averse. The main outcome of the paper is that the optimal transfer of construction risk will be lower when the variance of errors in cost forecast, the risk aversion of the firm and the marginal cost of public funds are larger, while the optimal transfer of construction risk will grow when the variance of errors in cost monitoring and the risk aversion of the public authority are larger

Engineering Computational Emotion - A Reference Model for Emotion in Artificial Systems

Emotion is generally argued to be an influence on the behavior of life systems, largely concerning flexibility and adaptivity. The way in which life systems acts in response to a particular situations of the environment, has revealed the decisive and crucial importance of this feature in the success of behaviors. And this source of inspiration has influenced the way of thinking artificial systems. During the last decades, artificial systems have undergone such an evolution that each day more are integrated in our daily life. They have become greater in complexity, and the subsequent effects are related to an increased demand of systems that ensure resilience, robustness, availability, security or safety among others. All of them questions that raise quite a fundamental challenges in control design. This thesis has been developed under the framework of the Autonomous System project, a.k.a the ASys-Project. Short-term objectives of immediate application are focused on to design improved systems, and the approaching of intelligence in control strategies. Besides this, long-term objectives underlying ASys-Project concentrate on high order capabilities such as cognition, awareness and autonomy. This thesis is placed within the general fields of Engineery and Emotion science, and provides a theoretical foundation for engineering and designing computational emotion for artificial systems. The starting question that has grounded this thesis aims the problem of emotion--based autonomy. And how to feedback systems with valuable meaning has conformed the general objective. Both the starting question and the general objective, have underlaid the study of emotion, the influence on systems behavior, the key foundations that justify this feature in life systems, how emotion is integrated within the normal operation, and how this entire problem of emotion can be explained in artificial systems. By assuming essential differences concerning structure, purpose and operation between life and artificial systems, the essential motivation has been the exploration of what emotion solves in nature to afterwards analyze analogies for man--made systems. This work provides a reference model in which a collection of entities, relationships, models, functions and informational artifacts, are all interacting to provide the system with non-explicit knowledge under the form of emotion-like relevances. This solution aims to provide a reference model under which to design solutions for emotional operation, but related to the real needs of artificial systems. The proposal consists of a multi-purpose architecture that implement two broad modules in order to attend: (a) the range of processes related to the environment affectation, and (b) the range or processes related to the emotion perception-like and the higher levels of reasoning. This has required an intense and critical analysis beyond the state of the art around the most relevant theories of emotion and technical systems, in order to obtain the required support for those foundations that sustain each model. The problem has been interpreted and is described on the basis of AGSys, an agent assumed with the minimum rationality as to provide the capability to perform emotional assessment. AGSys is a conceptualization of a Model-based Cognitive agent that embodies an inner agent ESys, the responsible of performing the emotional operation inside of AGSys. The solution consists of multiple computational modules working federated, and aimed at conforming a mutual feedback loop between AGSys and ESys. Throughout this solution, the environment and the effects that might influence over the system are described as different problems. While AGSys operates as a common system within the external environment, ESys is designed to operate within a conceptualized inner environment. And this inner environment is built on the basis of those relevances that might occur inside of AGSys in the interaction with the external environment. This allows for a high-quality separate reasoning concerning mission goals defined in AGSys, and emotional goals defined in ESys. This way, it is provided a possible path for high-level reasoning under the influence of goals congruence. High-level reasoning model uses knowledge about emotional goals stability, letting this way new directions in which mission goals might be assessed under the situational state of this stability. This high-level reasoning is grounded by the work of MEP, a model of emotion perception that is thought as an analogy of a well-known theory in emotion science. The work of this model is described under the operation of a recursive-like process labeled as R-Loop, together with a system of emotional goals that are assumed as individual agents. This way, AGSys integrates knowledge that concerns the relation between a perceived object, and the effect which this perception induces on the situational state of the emotional goals. This knowledge enables a high-order system of information that provides the sustain for a high-level reasoning. The extent to which this reasoning might be approached is just delineated and assumed as future work. This thesis has been studied beyond a long range of fields of knowledge. This knowledge can be structured into two main objectives: (a) the fields of psychology, cognitive science, neurology and biological sciences in order to obtain understanding concerning the problem of the emotional phenomena, and (b) a large amount of computer science branches such as Autonomic Computing (AC), Self-adaptive software, Self-X systems, Model Integrated Computing (MIC) or the paradigm of models@runtime among others, in order to obtain knowledge about tools for designing each part of the solution. The final approach has been mainly performed on the basis of the entire acquired knowledge, and described under the fields of Artificial Intelligence, Model-Based Systems (MBS), and additional mathematical formalizations to provide punctual understanding in those cases that it has been required. This approach describes a reference model to feedback systems with valuable meaning, allowing for reasoning with regard to (a) the relationship between the environment and the relevance of the effects on the system, and (b) dynamical evaluations concerning the inner situational state of the system as a result of those effects. And this reasoning provides a framework of distinguishable states of AGSys derived from its own circumstances, that can be assumed as artificial emotion.

Emotion transplantation through adaptation in HMM-based speech synthesis

This paper proposes an emotion transplantation method capable of modifying a synthetic speech model through the use of CSMAPLR adaptation in order to incorporate emotional information learned from a different speaker model while maintaining the identity of the original speaker as much as possible. The proposed method relies on learning both emotional and speaker identity information by means of their adaptation function from an average voice model, and combining them into a single cascade transform capable of imbuing the desired emotion into the target speaker. This method is then applied to the task of transplanting four emotions (anger, happiness, sadness and surprise) into 3 male speakers and 3 female speakers and evaluated in a number of perceptual tests. The results of the evaluations show how the perceived naturalness for emotional text significantly favors the use of the proposed transplanted emotional speech synthesis when compared to traditional neutral speech synthesis, evidenced by a big increase in the perceived emotional strength of the synthesized utterances at a slight cost in speech quality. A final evaluation with a robotic laboratory assistant application shows how by using emotional speech we can significantly increase the students’ satisfaction with the dialog system, proving how the proposed emotion transplantation system provides benefits in real applications.

Measuring emotion: the long and short of it

Estudio de la eficiencia en la reducción del número de términos empleados en los léxicos de respuesta emocional del consumidor: aplicación en cerveza

Cultural universals: Measuring the semantic structure of emotion terms in English and Japanese

Research is presented on the semantic structure of 15 emotion terms as measured by judged-similarity tasks for monolingual English-speaking and monolingual and bilingual Japanese subjects. A major question is the relative explanatory power of a single shared model for English and Japanese versus culture-specific models for each language. The data support a shared model for the semantic structure of emotion terms even though some robust and significant differences are found between English and Japanese structures. The Japanese bilingual subjects use a model more like English when performing tasks in English than when performing the same task in Japanese.

A unique human gene that spans over 230 kb in the human chromosome 8p11-12 and codes multiple family proteins sharing RNA-binding motifs.

A unique gene, RBP-MS, spanning over 230 kb in the human chromosome 8p11-12 near the Werner syndrome gene locus is described. The single-copy RBP-MS gene is alternatively spliced, resulting in a family of at least 12 transcripts (average length of 1.5 kb). Nine different types of cDNAs that encode an RNa-binding motif at the N terminus and helix-rich sequences at the C terminus have been identified thus far. Among the 16 exons identified, four 5'-proximal exons contained sequences homologous to the RNA-binding domain of Drosophila couch potato gene. Northern blot analysis showed that the RBP-MS gene was expressed strongly in the heart, prostate, intestine, and ovary, and poorly in the skeletal muscle, spleen, thymus, brain, and peripheral leukocytes. The possible role of this gene in RNA metabolism is discussed.