Brain monitoring combined with automatic analysis of EEGs provides a clinical decision support tool that can reduce time to diagnosis and assist clinicians in real-time monitoring applications (e.g., neurological intensive care units). Clinicians have indicated that a sensitivity of 95% with specificity below 5% was the minimum requirement for clinical acceptance. In this study, a high-performance automated EEG analysis system based on principles of machine learning and big data is proposed. This hybrid architecture integrates hidden Markov models (...) (HMMs) for sequential decoding of EEG events with deep learning-based postprocessing that incorporates temporal and spatial context. These algorithms are trained and evaluated using the Temple University Hospital EEG, which is the largest publicly available corpus of clinical EEG recordings in the world. This system automatically processes EEG records and classifies three patterns of clinical interest in brain activity that might be useful in diagnosing brain disorders: (1) spike and/or sharp waves, (2) generalized periodic epileptiform discharges, (3) periodic lateralized epileptiform discharges. It also classifies three patterns used to model the background EEG activity: (1) eye movement, (2) artifacts and (3) background. Our approach delivers a sensitivity above 90% while maintaining a specificity below 5%. We also demonstrate that this system delivers a low false alarm rate, which is critical for any spike detection application. (shrink)

In this article we explore the relationship between semiotic analysis of images and quantitative analysis of vast image corpora, in particular the work produced by Lev Manovich and the Cultural Analytics Lab, called “Media Visualization.” Media Visualization has been chosen as corpus because of its metavisual operation (images are visualized and analyzed by images) and its innovating way of conceiving analysis: by visual instruments. In this paper semiotics is used as an approach to Media Visualization and taken (...) as an object of study as well, especially visual semiotics. In this sense, a comparison between visual semiotics (close reading of small corpora) and quantitative analyses of images (distant reading of vast collections) are conducted from a semiotic point of view. Post-Greimassian semiotics guides this study with respect to the issue of the image-within-an-image and metavisual visualization; Peircean semiotics is employed to explain and develop the notion of diagram. (shrink)

L’analisi informatica di testi filosofici, la creazione di database, ipertesti o edizioni elettroniche non costituiscono più unicamente una ricerca di frontiera, ma sono da molti anni una risorsa preziosa per gli studi umanistici. Ora, non si tratta di richiedere alle macchine un ulteriore sforzo per comprendere il linguaggio umano, quanto piuttosto di perfezionare gli strumenti affinché esse possano essere a tutti gli effetti collaboratori di ricerca. Questo articolo è concepito come il resoconto di un esperimento finalizzato a documentare come le (...) associazioni lessicali di un gruppo selezionato di testi medievali possa offrire qualche suggerimento in merito ai loro contenuti teorici. Computer analysis of texts, creation of databases hypertexts and digital editions are not the final frontier of research anymore. Quite the contrary, from many years they have been representing a significant contribution to medieval studies. Therefore, we do not mean to make the computer able to grasp the meaning of human language and penetrate its secrets, but rather we aim at improving their tools, so that they will become an even more efficient equipment employed in research activities. This paper is thought as a sort of technical report with the proposed task to verify if an automatic identification of some word associations within a selected groups of medieval writings produces suggestions on the subject of the processed texts, able to be used in a theoretical inquiry. (shrink)

Interaction mining is about discovering and extracting insightful information from digital conversations, namely those human?human information exchanges mediated by digital network technology. We present in this article a computational model of natural arguments and its implementation for the automatic argumentative analysis of digital conversations, which allows us to produce relevant information to build interaction business analytics applications overcoming the limitations of standard text mining and information retrieval technology. Applications include advanced visualisations and abstractive summaries.

We present methods for automatically producing summary excerpts or thumbnails of music. To find the most representative excerpt, we maximize the average segment similarity to the entire work. After windowbased audio parameterization, a quantitative similarity measure is calculated between every pair of windows, and the results are embedded in a 2D similarity matrix. Summing the similarity matrix over the support of a segment results in a measure of how similar that segment is to the whole. This measure is maximized to (...) find the segment that best represents the entire work. We discuss variations on the method, and present experimental results for orchestral music, popular songs, and jazz. These results demonstrate that the method finds significantly representative excerpts, using very few assumptions about the source audio. (shrink)

Many views define the concept of automaticity in terms of a number of features, but they differ with regard to the features they put most emphasis on, as well as with regard to the coherence they assume among the features. One contemporary account is the gradual and decompositional view, which proposes to investigate each automaticity feature separately and determine the degree to which it is present. In this chapter, we engage in a detailed analysis of the most important features (...) in order to examine whether they can indeed be regarded as gradual, and whether they can be conceptually and logically separated. (shrink)

Over the last few years, automatic facial micro-expression analysis has garnered increasing attention from experts across different disciplines because of its potential applications in various fields such as clinical diagnosis, forensic investigation and security systems. Advances in computer algorithms and video acquisition technology have rendered machine analysis of facial micro-expressions possible today. Although the study of facial micro-expressions is a well-established field in psychology, it is still relatively new from the computational perspective with many interesting problems. In (...) this survey, we present a comprehensive review of state-of-the-art databases and methods for micro-expressions spotting and recognition. Individual stages involved in the automation of these tasks are also described and reviewed at length. In addition, we also deliberate on the challenges and future directions in this growing field of automatic facial micro-expression analysis. (shrink)

Automatic imitation or “imitative compatibility” is thought to be mediated by the mirror neuron system and to be a laboratory model of the motor mimicry that occurs spontaneously in naturalistic social interaction. Imitative compatibility and spatial compatibility effects are known to depend on different stimulus dimensions—body movement topography and relative spatial position. However, it is not yet clear whether these two types of stimulus–response compatibility effect are mediated by the same or different cognitive processes. We present an interactive activation (...) model of imitative and spatial compatibility, based on a dual-route architecture, which substantiates the view they are mediated by processes of the same kind. The model, which is in many ways a standard application of the interactive activation approach, simulates all key results of a recent study by Catmur and Heyes (2011). Specifically, it captures the difference in the relative size of imitative and spatial compatibility effects; the lack of interaction when the imperative and irrelevant stimuli are presented simultaneously; the relative speed of responses in a quintile analysis when the imperative and irrelevant stimuli are presented simultaneously; and the different time courses of the compatibility effects when the imperative and irrelevant stimuli are presented asynchronously. (shrink)

In this paper, we study the performance of baseline hidden Markov model (HMM) for segmentation of speech signals. It is applied on single-speaker segmentation task, using Hindi speech database. The automatic phoneme segmentation framework evolved imitates the human phoneme segmentation process. A set of 44 Hindi phonemes were chosen for the segmentation experiment, wherein we used continuous density hidden Markov model (CDHMM) with a mixture of Gaussian distribution. The left-to-right topology with no skip states has been selected as it (...) is effective in speech recognition due to its consistency with the natural way of articulating the spoken words. This system accepts speech utterances along with their orthographic “transcriptions” and generates segmentation information of the speech. This corpus was used to develop context-independent hidden Markov models (HMMs) for each of the Hindi phonemes. The system was trained using numerous sentences that are relevant to provide information to the passengers of the Metro Rail. The system was validated against a few manually segmented speech utterances. The evaluation of the experiments shows that the best performance is obtained by using a combination of two Gaussians mixtures and five HMM states. A category-wise phoneme error analysis has been performed, and the performance of the phonetic segmentation has been reported. The modeling of HMMs has been implemented using Microsoft Visual Studio 2005 (C++), and the system is designed to work on Windows operating system. The goal of this study is automatic segmentation of speech at phonetic level. (shrink)

Available corpora for Argument Mining differ along several axes, and one of the key differences is the presence (or absence) of discourse markers to signal argumentative content. Exploring effective ways to use discourse markers has received wide attention in various discourse parsing tasks, from which it is well-known that discourse markers are strong indicators of discourse relations. To improve the robustness of Argument Mining systems across different genres, we propose to automatically augment a given text with discourse markers such that (...) all relations are explicitly signaled. Our analysis unveils that popular language models taken out-of-the-box fail on this task; however, when fine-tuned on a new heterogeneous dataset that we construct (including synthetic and real examples), they perform considerably better. We demonstrate the impact of our approach on an Argument Mining downstream task, evaluated on different corpora, showing that language models can be trained to automatically fill in discourse markers across different corpora, improving the performance of a downstream model in some, but not all, cases. Our proposed approach can further be employed as an assistant tool for better discourse understanding. (shrink)

Background: The field of voice and speech analysis has become increasingly popular over the last 10 years, and articles on its use in detecting neurodegenerative diseases have proliferated. Many studies have identified characteristic speech features that can be used to draw an accurate distinction between healthy aging among older people and those with mild cognitive impairment and Alzheimer's disease. Speech analysis has been singled out as a cost-effective and reliable method for detecting the presence of both conditions. In (...) this research, a systematic review was conducted to determine these features and their diagnostic accuracy.Methods: Peer-reviewed literature was located across multiple databases, involving studies that apply new procedures of automatic speech analysis to collect behavioral evidence of linguistic impairments along with their diagnostic accuracy on Alzheimer's disease and mild cognitive impairment. The risk of bias was assessed by using JBI and QUADAS-2 checklists.Results: Thirty-five papers met the inclusion criteria; of these, 11 were descriptive studies that either identified voice features or explored their cognitive correlates, and the rest were diagnostic studies. Overall, the studies were of good quality and presented solid evidence of the usefulness of this technique. The distinctive acoustic and rhythmic features found are gathered. Most studies record a diagnostic accuracy over 88% for Alzheimer's and 80% for mild cognitive impairment.Conclusion: Automatic speech analysis is a promising tool for diagnosing mild cognitive impairment and Alzheimer's disease. The reported features seem to be indicators of the cognitive changes in older people. The specific features and the cognitive changes involved could be the subject of further research. (shrink)

This article presents an applied discussion of the possibility of integrating conversation analysis (CA) methodology into that of machine learning. The aim is to improve the detection of that which resembles disengagement in the interaction between a robot and a human. We offer a novel analytical assemblage at the heart of the two disciplines, and namely on the level of the annotation schemes provided by conversation analysis transcription methods. First, we demonstrate that the need for a stable structure (...) in establishing an interaction scenario and in designing robot behaviours does not prevent the emergence of ordinariness or creativity among the participants engaged in this interaction. Secondly, based on an actual case, we emphasize the possibility of systematicness in CA transcription to support the choice (a) of the categories targeted by prediction methods and defined by the annotation scheme, and (b) of the verbal and non-verbal features used to create prediction models. (shrink)

An analysis of the ethical impacts of the use of anAutomatic Milking System (AMS) is employed as a casestudy to illustrate the use of a form of bioethicalanalysis in technology assessment. The approach isbased on the Ethical Matrix, where `impacts' areassessed in terms of (lack of) respect for threeethical principles as applied to interest groups. Inthis case, only impacts on dairy cows are examined,and principally in terms of their behaviouralfreedom.In contrast to traditional milking systems, AMS, inprinciple, allow cows to (...) present for milkingvoluntarily. So with AMS, it is claimed that dairymanagement relies on the autonomous interaction of thecow with her environment. (shrink)

In recent years, somatosensory interaction technology, represented by Microsoft’s Kinect hardware platform, has been widely used in various fields, such as entertainment, education, and medicine. Kinect technology can easily capture and record behavioral data, which provides new opportunities for behavioral and psychological correlation analysis research. In this paper, an automatic decision-style recognition method is proposed. Experiments involving 240 subjects were conducted to obtain face data and individual decision-making style score. The face data was obtained using the Kinect camera, (...) and the decision-style score were obtained via a questionnaire. To realize automatic recognition of an individual decision-making style, machine learning was employed to establish the mapping relationship between the face data and a scaled evaluation of the decision-making style score. This study adopts a variety of classical machine learning algorithms, including Linear regression, Support vector machine regression, Ridge regression, and Bayesian ridge regression. The experimental results show that the linear regression model returns the best results. The correlation coefficient between the linear regression model evaluation results and the scale evaluation results was 0.6, which represents a medium and higher correlation. The results verify the feasibility of automatic decision-making style recognition method based on facial analysis. (shrink)

The installation error of metallurgical machinery parts is one of the common sources of errors in mechanical equipment. Because the installation error of different parts has different influences on different mechanical equipment, a simple linear formula cannot be used to identify the installation error. In the past, the manual recognition method and the touch recognition method lack of error information analysis, which leads to inaccurate recognition results. To improve the problem, an automatic recognition method based on the neural (...) network for metallurgical machinery parts installation error is proposed. According to the principle of automatic recognition of installation error based on the neural network, the nonlinear relation matrix between layers of the neural network is established. The operating state parameters of mechanical equipment are calculated, and the time series of the parameters are divided into several segments averagely. Based on the recognition algorithm, the inspection steps of depth, perpendicularity and center position of reserved hole, base board construction, short-circuit motor line and terminal installation, center mark board, and reference point installation are designed. The experimental results show that the recall rate of the proposed method is 97.66%, and the maximum absolute deviation is 0.09. The experimental data verify the feasibility of the proposed method. (shrink)

We apply Dienes & Perner's (D&P's) framework to the automatic/nonautomatic processing contrast. Our analysis leads to the conclusion that automatic and nonautomatic processing result in representations that have explicit results. We propose equating consciousness with explicitness of aspects rather than with full explicitness as defined by D&P.

A classical definition of automaticity establishes that automatic processing occurs without attention or consciousness, and cannot be controlled. Previous studies have demonstrated that semantic priming can be reduced if attention is directed to a low-level of analysis. This finding suggests that semantic processing is not automatic since it can be controlled. In this paper, we present two experiments that demonstrate that semantic processing may occur in the absence of attention and consciousness. A negative semantic priming effect was (...) found when a low-level prime-task was required and when a masked lexical decision prime-task was performed . This paper also discusses the limitations of the inhibitory mechanism involved in negative semantic priming effect. (shrink)

Part-of-speech tagging for English composition is the basis for automatic correction of English composition. The performance of the part-of-speech tagging system directly affects the performance of the marking and analysis of the correction system. Therefore, this paper proposes an automatic scoring model for English composition based on article part-of-speech tagging. First, use the convolutional neural network to extract the word information from the character level and use this part of the information in the coarse-grained learning layer. Secondly, (...) the word-level vector is introduced, and the residual network is used to establish an information path to integrate the coarse-grained annotation and word vector information. Then, the model relies on the recurrent neural network to extract the overall information of the sequence data to obtain accurate annotation results. Then, the features of the text content are extracted, and the automatic scoring model of English composition is constructed by means of model fusion. Finally, this paper uses the English composition scoring competition data set on the international data mining competition platform Kaggle to verify the effect of the model. (shrink)

Contemporary feminist critics have often described Surrealism as a misogynist movement. In Automatic Woman, Katharine Conley addresses this issue, confirming some feminist allegations while qualifying and overturning others. Through insightfuløanalyses of works by a range of writers and artists, Conley develops a complex view of Surrealist portrayals of Woman. Conley begins with a discussion of the composite image of Woman developed by such early male Surrealists as Andrä Breton, Francis Picabia, and Paul Eluard. She labels that image ?Automatic (...) Woman??a term that comprises views of Woman as provocative and revolutionary but also as a depersonalized object largely devoid of individuality and volition. This analysis largely confirms feminist critiques of Surrealism. The heart of the book, however, examines the writings of Leonora Carrington and Unica Z_rn, two women in the Surrealist movement whose works, Conley argues, anticipate much contemporary feminist art and theory. In concluding, Conley shows how Breton?s own views on women evolved in the course of his long career, arriving at last at a position far more congenial to contemporary feminists. Automatic Woman is distinguished by Katharine Conley?s judicious understanding of how women?and the image of Woman?figured in Surrealism. The book is an important contemporary account of a cultural movement that continues to fascinate, influence, and provoke us. (shrink)

Four experiments were conducted to evaluate explanations of picture superiority effects previously found for several tasks. In a process dissociation procedure with word stem completion, picture fragment completion, and category production tasks, conscious and automatic memory processes were compared for studied pictures and words with an independent retrieval model and a generate-source model. The predictions of a transfer appropriate processing account of picture superiority were tested and validated in “process pure” latent measures of conscious and unconscious, or automatic (...) and source, memory processes. Results from both model fits verified that pictures had a conceptual processing advantage over words for all tasks. The effects of perceptual compatibility depended on task type, with pictorial tasks favoring pictures and linguistic tasks favoring words. Results show support for an explanation of the picture superiority effect that involves an interaction of encoding and retrieval processes. (shrink)

Critical analysis of the biotechnological reproduction of biological life increasingly emphasises the role of value-producing labour in biotechnologically reproductive processes, while also arguing that Marx’s use of the terms ‘labour’ and ‘value’ is inadequate to the critical scrutiny of these processes. Focusing especially on the reformulation of the value-labour relation in recent work in this area by Melinda Cooper and Catherine Waldby, this paper both critiques this reformulation and questions the explanatory efficacy of the category ‘labour’ in this context. (...) Emphasising the contemporary global expansion of capital relative to value-producing labour – specifically, the expansion of fictitious capital and debt on the one hand, and of global surplus populations on the other – it argues that this reformulation misrepresents the mediated capacities of capital as the immediate capacities of labour. This reformulation, moreover, is indicative of broader tendencies in the contemporary theorisation of labour, tendencies exemplified by autonomist Marxism. (shrink)

In this paper, we discuss previous research in automatic prediction of court decisions. We define the difference between outcome identification, outcome-based judgement categorisation and outcome forecasting, and review how various studies fall into these categories. We discuss how important it is to understand the legal data that one works with in order to determine which task can be performed. Finally, we reflect on the needs of the legal discipline regarding the analysis of court judgements.

As one of the traditional entertainment items, video background music has gradually changed from traditional consumption to network consumption, which naturally also has the problem of information overload. From the perspective of model design and auxiliary information, this paper proposes a tightly coupled fusion model based on deep learning and collaborative filtering to alleviate the problem of poor prediction accuracy due to sparse matrix in the scoring prediction problem. In the use of auxiliary information, this paper uses crawler technology to (...) obtain auxiliary information on the user side and the video background music side and compensates for the model’s sensitivity to the sparsity of the score matrix from a data perspective. In terms of model design, this paper conducts auxiliary information mining based on the diversity and structural differences of auxiliary information, uses an improved stack autoencoder to learn user’s interests, and uses convolutional neural networks to mine hidden features of video background music. Based on the idea of probabilistic matrix decomposition, the tightly coupled fusion of multiple deep learning models and collaborative filtering is realized. By comprehensively considering user’s interest and video background music characteristics, the collaborative filtering process is supervised, and the optimized prediction result is finally obtained. The performance test and function test of the system were carried out, respectively, to verify the effectiveness of the hybrid recommendation algorithm and the effect of the system for recommendation. Through experimental analysis, it is proved that the algorithm designed in this paper can improve the recommendation quality and achieve the expected goal. (shrink)

This paper considers the connection between automaticity, control and agency. Indeed, recent philosophical and psychological works play up the incompatibility of automaticity and agency. Specifically, there is a threat of automaticity, for automaticity eliminates agency. Such conclusions stem from a tension between two thoughts: that automaticity pervades agency and yet automaticity rules out control. I provide an analysis of the notions of automaticity and control that maintains a simple connection: automaticity entails the absence of control. An appropriate analysis, (...) however, shows that actions are forms of control and pervasively automatic even if automaticity implies the absence of control. Consequences are drawn for the theory of mental agency and the psychological concepts of automaticity and control. (shrink)

In this paper, we present a case study of how well subject metadata (comprising headings from an international classification scheme) has been deployed in a national data catalogue, and how often data seekers use subject metadata when searching for data. Through an analysis of user search behaviour as recorded in search logs, we find evidence that users utilise the subject metadata for data discovery. Since approximately half of the records ingested by the catalogue did not include subject metadata at (...) the time of harvest, we experimented with automatic subject classification approaches in order to enrich these records and to provide additional support for user search and data discovery. Our results show that automatic methods work well for well represented categories of subject metadata, and these categories tend to have features that can distinguish themselves from the other categories. Our findings raise implications for data catalogue providers; they should invest more effort to enhance the quality of data records by providing an adequate description of these records for under-represented subject categories. (shrink)

This article proposes a method for the semi-automatic extraction of resemblance metaphor terms from a manually annotated corpus of marine biology texts in English and Spanish. The corpus was first searched for target domain terms as well as for lexical markers indicative of metaphors. The combination of these search strategies for metaphor extraction resulted in a set of English-Spanish term pairs. After analysing and comparing these metaphor candidates, a quantitative analysis provided comparative statistical data regarding marine biology metaphor. (...) Finally, the metaphorical nature of marine biology terms was verified in three ways. The first verification strategy entailed an adapted version of the Metaphor Identification Procedure (CitationPragglejaz Group, 2007). The second involved the analysis of contextual data extracted from the corpus, and the third involved the analysis of visual images from an online marine biology database and from the Google search engine. (shrink)

This paper seeks to build on the extensive connections that have arisen between automata theory, combinatorics on words, fractal geometry, and model theory. Results in this paper establish a characterization for the behavior of the fractal geometry of “k-automatic” sets, subsets of $[0,1]^d$ that are recognized by Büchi automata. The primary tools for building this characterization include the entropy of a regular language and the digraph structure of an automaton. Via an analysis of the strongly connected components of (...) such a structure, we give an algorithmic description of the box-counting dimension, Hausdorff dimension, and Hausdorff measure of the corresponding subset of the unit box. Applications to definability in model-theoretic expansions of the real additive group are laid out as well. (shrink)

Introduction: Motherese, or emotional infant directed speech, is the specific form of speech used by parents to address their infants. The prosody of IDS has affective properties, expresses caregiver involvement, is a marker of caregiver-infant interaction quality. IDS prosodic characteristics can be detected with automatic analysis. We aimed to explore whether pregnant women “speak” to their unborn baby, whether they use motherese while speaking and whether anxio-depressive or obstetrical status impacts speaking to the fetus.Participants and Methods: We conducted (...) an observational study of pregnant women with gestational ages from 26 to 38 weeks. Women were recruited in a university hospital department of obstetrics. Thirty-five women agreed to participate in the study, and 26 audio records were exploitable. We collected obstetrical and sociodemographic data, pregnancy outcomes, anxiety and depressive status using the Covy and Raskin Scales, and life events using the Sensations During Pregnancy and Life Event Questionnaire. Each participant was left alone with an audio recorder with a recommendation to feel free to speak to her fetus as she would have done at home. The recording was stopped after 3 min. Audio recordings were analyzed by two methods: psycholinguist experts' annotation and computational objective automatic analyses.Results: Most mothers reported speaking to their fetuses. We found a correlation between maternal first perceptions of fetal movements and the start of mother's speaking to fetus. Motherese prosody was detected with both annotation and automatic analysis with a significant correlation between the two methods. In this exploratory study, motherese use was not associated with maternal anxiodepressive or obstetrical status. However, the more future mothers were depressed, the less they spoke with their fetuses during the recording.Conclusion: Fetal directed speech can be detected during pregnancy, and it contains a period of prosody that shares the same characteristics of motherese that can be described as prenatal motherese or emotional fetal-directed speech. This means that pregnant women start using motherese much earlier than expected. FDS seems to be correlated with maternal first perceptions of fetal movements and depression scores. However, more research is needed to confirm these exploratory results. (shrink)

The paper presents a cross-country analysis of the second generation of currency boards introduced in three East European countries: Bulgaria, Estonia and Lithuania. We focus on their institutional, legal and political characteristics which are closely associated with the operation of the automatic mechanism of currency boards. The presence of an automatic mechanism within the framework of the currency board is often cited as a major counterpoint to the “discretion and subjectivity” of a classical central bank. Since there (...) is no precise definition of automatic mechanisms in the literature, we define it as: “the presence of a positive cointegration relationship between the balance of payments and the reserve money and absence of discretionary variables in the model.” When discretionary variables are present in the model in one form or another, we may speak of a “mechanism for adjustment through discretion – conscious or unconscious.” Within the framework of the second generation of currency boards, we reduce the channel of discretion to the presence of atypical balance sheet items and employment of a number of monetary policy instruments. We seek in this article to compare currency board automatic mechanism in Bulgaria, Estonia and Lithuania.L’article procède d’une analyse transversale par pays de la deuxième génération des “bureaux d’émission” introduits dans trois pays de l’Europe de l’Est. L’accent est mis sur les caractéristiques institutionnelles, juridiques et politiques qui sont étroitement associées à l’opération du mécanisme automatique des bureaux d’émission. L’existence d’un mécanisme automatique dans la structure d’un bureau d’émission est souvent mise en avant comme l’argument majeur à l’encontre de la “discrétion” et la “subjectivité” d’une banque centrale classique. Parce qu’il n’existe aucune définition précise du mécanisme automatique dans la littérature, nous la définissons comme “la présence d’une relation positive de cointégration entre la balance des paiements et les réserves monétaires et l’absence de variables discrétionna- ires dans le modèle”. Quand des variables discrétionnaires sont présentes dans le modèle sous une forme ou une autre, nous pouvons parler d’un “mécanisme d’ajustement discrétionnaire – conscient ou inconscient”. Au sein de la structure de la deuxième génération des bureaux d’émission, la discrétion se réduit à la présence de postes atypiques dans le bilan et à l’emploi d’un certain nombre d’instruments de politique monétaire.L’article propose une comparaison du mécanisme automatique en Bulgarie, Estonie et Lithuanie. (shrink)

During the second half of the 20th century, attempts were made to operationally redefine various social activities, including those related to science, the military, administration and industry. These attempts were aided by scientific and technical innovations developed in the Second World War, and subsequently by the increase in use of automation in various domains. This Ph.D. thesis addresses these attempts from a sociohistorical perspective, focusing on the specific case of archaeology. During this period, the domain of archaeology underwent a process (...) of disciplinarisation and professionalisation. The same occurred in applied mathematics and then computer science: this thesis focuses on the relationships between these three domains. In France, during the 1950's and 1960's, there were significant methodological and conceptual innovations. Their subsequent scientific recognition, was, however, relatively minor. In archaeology, innovations related to applied mathematics and automatics did not lead to the emergence of an archaeological speciality based on computation. This situation was in striking contrast to what happened in other scientific domains and in archaeology in other countries, where new theoretical and methodological Anglophone definitions in ‘New Archaeology’ were spreading worldwide. This thesis explores three collective attempts to redefine the conceptual and methodological basis of archaeology, led by Georges Laplace, Jean-Claude Gardin and Jean Lesage, across France, Spain and Italy. These cases are completed by other people who had significant careers in both engineering and archaeology. In general, this thesis studies a scientific activity by investigating the cognitive and social aspects of peoples’ methodological contributions. Three models of the relationships between experts in a scientific domain and experts in an applied science (here mathematics and computing) are empirically identified and described. The effects of introducing mathematical and automation procedures on the division of labour and the distribution of recognition are analysed. The success or failure of the methodological propositions are discussed with reference to several factors and models of scientific innovation. This thesis generates new information on the development of rescue and preventive archaeology and on the use of digital technologies in human sciences. The analysis draws on 82 interviews, 23 archives and several bibliometric datasets (extracted from pre-existing databases or constructed for the purpose of this research). Mirroring the archaeological propositions under study, this research also intends to illustrate the possible use of computing and formalised procedures in social sciences. The documentation and demonstrative principles underlying this work, implemented by using Wiki, the methods of literate programming and reproducible research, are themselves analysed. (shrink)

Tendencies of approach and avoidance seem to be a universal characteristic of humans. Specifically, individuals are faster in avoiding than in approaching negative stimuli and they are faster in approaching than in avoiding positive stimuli. The existence of this automatic approach-avoidance bias has been demonstrated in many studies. Furthermore, this bias is thought to play a key role in psychiatric disorders like drug addiction and phobias. However, its mechanisms are far from clear. Theories of embodied cognition postulate that the (...) nature of gestures plays a key role in this process. To shed light on the role of the involved gesture we employed a 2 × 2 factorial design with two types of stimuli. Participants had either to approach positive and avoid negative stimuli or to avoid positive stimuli and approach negative stimuli. Further, they responded either with a joystick or a button press on a response pad. Participants reacted faster in congruent conditions, i.e., avoiding negative stimuli and approaching positive stimuli, than in incongruent conditions. This replicates the known approach and avoidance bias. However, direct analysis of the button press condition revealed no reaction time advantage for congruent trials compared to incongruent trials. In contrast, in the joystick condition participants were significantly faster performing congruent reactions than incongruent reactions. This interaction, a significant reaction time advantage, when the response is enacted by moving a joystick towards or away from the body provides evidence that approach-avoidance tendencies have a crucial bodily component. (shrink)

This paper describes the relationship between technics and desire in light of Bernard Stiegler’s new critique of political economy. The starting point for the analysis is Stiegler’s critique of the reinterpretation of Freud’s legacy by Herbert Marcuse in Eros and Civilization. The context of the analysis is the ongoing mutation of consumer capitalism into computational capitalism—one in which automated calculation systems are used to control all forms of mental and affective human activity. Digital automatization, I argue, encourages a (...) different view of what Marcuse called “the automatization of the superego.” It also requires us to rethink to what extent desire is conditioned techno-logically beyond the limits of Marcuse’s critique of Freud, capitalism and technology. The article pays special attention to Stiegler’s reinterpretation of the theory of sublimation in relation to contemporary capitalism and its technological infrastructure (from television to digital platforms). It is also an attempt to include the question concerning technology in psychoanalytic thinking. (shrink)

In the automatic detection of epileptic seizures, the monitoring of critically ill patients with time varying EEG signals is an essential procedure in intensive care units. There is an increasing interest in using EEG analysis to detect seizure, and in this study we aim to get a better understanding of how to visualize the information in the EEG time-frequency feature, and design and train a novel random forest algorithm for EEG decoding, especially for multiple-levels of illness. Here, we (...) propose an automatic detection framework for epileptic seizure based on multiple time-frequency analysis approaches; it involves a novel random forest model combined with grid search optimization. The short-time Fourier transformation visualizes seizure features after normalization. The dimensionality of features is reduced through principal component analysis before feeding them into the classification model. The training parameters are optimized using grid search optimization to improve detection performance and diagnostic accuracy by in the recognition of three different levels epileptic of conditions (healthy subjects, seizure-free intervals, seizure activity). Our proposed model was used to classify 500 samples of raw EEG data, and multiple cross-validations were adopted to boost the modeling accuracy. Experimental results were evaluated by an accuracy, a confusion matrix, a receiver operating characteristic curve and an area under the curve. The evaluations indicated that our model achieved the more effective classification than some previous typical methods. Such a scheme for computer-assisted clinical diagnosis of seizures has a potential guiding significance, which not only relieves the suffering of patient with epilepsy to improve quality of life, but also helps neurologists reduce their workload. (shrink)

The automated parsing of 130,213 news articles about the 2012 US presidential elections produces a network formed by the key political actors and issues, which were linked by relations of support and opposition. The nodes are formed by noun phrases and links by verbs, directly expressing the action of one node upon the other. This network is studied by applying insights from several theories and techniques, and by combining existing tools in an innovative way, including: graph partitioning, centrality, assortativity, hierarchy (...) and structural balance. The analysis yields various patterns. First, we observe that the fundamental split between the Republican and Democrat camps can be easily detected by network partitioning, which provides a strong validation check of the approach adopted, as well as a sound way to assign actors and topics to one of the two camps. Second, we identify the most central nodes of the political camps. We also learnt that Clinton played a more central role than Biden in the Democrat camp; the overall campaign was much focused on economy and rights; the Republican Party is the most divisive subject in the campaign, and is portrayed more negatively than the Democrats; and, overall, the media reported positive statements more frequently for the Democrats than the Republicans. This is the first study in which political positions are automatically extracted and derived from a very large corpus of online news, generating a network that goes well beyond traditional word-association networks by means of richer linguistic analysis of texts. (shrink)

Community detection is a major issue in network analysis. This paper combines a socio-historical approach with an experimental reconstruction of programs to investigate the early automation of clique detection algorithms, which remains one of the unsolved NP-complete problems today. The research led by the archaeologist Jean-Claude Gardin from the 1950s on non-numerical information and graph analysis is retraced to demonstrate the early contributions of social sciences and humanities. The limited recognition and reception of Gardin's innovative computer application to (...) the humanities are addressed through two factors, in addition to the effects of historiography and bibliographies on the recording, discoverability, and reuse of scientific productions: (1) funding policies, evidenced by the transfer of research effort on graph applications from temporary interdisciplinary spaces to disciplinary organizations related to the then-emerging field of computer science; and (2) the erratic careers of algorithms, in which efficiency, flaws, corrections, and authors’ status, were determining factors. (shrink)

AimsThis study evaluates a protocol for early, routine ethics consultation for patients on extracorporeal membrane oxygenation to support decision-making in the context of clinical uncertainty with the aim of mitigating ethical conflict and moral distress.MethodsWe conducted a single-site qualitative analysis of EC documentation for all patients receiving ECMO support from 15 August 2018 to 15 May 2019. Detailed analysis of 20 ethically complex cases with protracted ethics involvement identifies four key ethical domains: limits of prognostication, bridge to nowhere, (...) burden of treatment and system-level concerns. There are three subthemes: relevant contextual factors, the role of EC and observed outcomes. Content analysis of transcripts from interviews with 20 members of the multidisciplinary ECMO team yields supplemental data on providers’ perceptions of the impact of the early intervention protocol.ResultsLimited outcome data for ECMO, unclear indications for withdrawal, adverse effects of treatment and an obligation to attend to programme metrics present significant ethical challenges in the care of this patient population. Upstream EC mitigates ethical conflict by setting clear expectations about ECMO as a time limited trial, promoting consistent messaging among multiple services and supporting surrogate decision-makers. When ECMO becomes a ‘bridge to nowhere’, EC facilitates decision-making that respects patient values yet successfully sets limits on non-beneficial use of this novel therapy.ConclusionData from this study support the conclusion that ECMO poses unique ethical challenges that necessitate a standardised protocol for early, routine EC—at least while this medical technology is in its nascent stages. (shrink)

This article discusses the foresight of philosopher/mathematician Norbert Wiener who, in the 1940s, founded Information Ethics as a research discipline. Wiener envisioned the coming of an “automatic age” in which information technology would have profound social and ethical impacts upon the world. He predicted, for example, machines that will learn, reason and play games; “automatic factories” that will replace assembly‐line workers and middle managers with computerized devices; workers who will perform their jobs over great distances with the aid (...) of new communication technologies; and people who will gain remarkable powers by adding computerized “prostheses” to their bodies. To analyze the ethical implications of such developments, Wiener presented some principles of justice and employed a powerful practical method of ethical analysis. (shrink)

This article echoes concerns recently formulated regarding CDA’s lack of attention to cognitive science. From a cognitive pragmatic viewpoint, I argue that discourse analysis should undergo an epistemological change in order to seriously take into account what cognitive approaches have to offer, in particular as regards the automatic processing of utterances and the subsequent non-conscious evaluation of contents vis-a-vis previously held beliefs. I regard the epistemological tension in CDA as stemming from a wider tension of the same sort (...) affecting social science in general. Considering discourse as a process of interpretation and evaluation, I address briefly the influence of evidentiality as a pragmatic category in persuasive discourse and conclude that the uptake of new beliefs on the basis of discourse is oriented towards the maximization of relevance in the sense of Sperber and Wilson. (shrink)