Semantic interoperability requires the use of standards, not only for Electronic Health Record (EHR) data to be transferred and structurally mapped into a receiving repository, but also for the clinical content of the EHR to be interpreted in conformity with the original meanings intended by its authors. Accurate and complete clinical documentation, faithful to the patient’s situation, and interoperability between systems, require widespread and dependable access to published and maintained collections of coherent and quality-assured semantic resources, including models such as (...) archetypes and templates that would (1) provide clinical context, (2) be mapped to interoperability standards for EHR data, (3) be linked to well specified, multi-lingual terminology value sets, and (4) be derived from high quality ontologies. Wide-scale engagement with professional bodies, globally, is needed to develop these clinical information standards. (shrink)

. Effective text region extraction and binarization of image embedded text documents on mobile devices having limited computational resources is an open research problem. In this paper, we present one such technique for preprocessing images captured with built-in cameras of handheld devices with an aim of developing an efficient Business Card Reader. At first, the card image is processed for isolating foreground components. These foreground components are classified as either text or non-text using different feature descriptors of texts and images. (...) The non-text components are removed and the textual ones are binarized with a fast adaptive algorithm. Specifically, we propose new techniques for foreground component isolation, text extraction and binarization of text regions from camera captured business card images. Experiments with business card images of various resolutions show that the present technique yields better accuracy and involves low computational overhead in comparison with the state-of-the-art. We achieve optimum text/non-text separation performance with images of resolution 800×600 pixels with an average recall rate of 93.90% and a precision rate of 96.84%. It involves a peak memory consumption of 0.68 MB and processing time of 0.102 seconds on a moderately powerful notebook, and 4 seconds of processing time on a PDA. (shrink)

The philosophy of “presence” seeks to challenge current understandings of meaning and understanding. One can trace its origins back to Vico, Dilthey, and Heidegger, though its more immediate exponents include Jean-Luc Nancy, Hans Ulrich Gumbrecht, and such contemporary philosophers of history as Frank Ankersmit and Eelco Runia. The theoretical paradigm of presence conveys how the past is literally with us in the present in significant and material ways: Things we cannot touch nonetheless touch us. This makes presence a post-linguistic or (...) post-discursive theory that challenges current understandings of “meaning” and “interpretation.” Presence provides an overview of the concept and surveys both its weaknesses and its possible uses. In this book, Ethan Kleinberg and Ranjan Ghosh bring together an interdisciplinary group of contributors to explore the possibilities and limitations of presence from a variety of perspectives—history, sociology, literature, cultural theory, media studies, photography, memory, and political theory. The book features critical engagements with the presence paradigm within intellectual history, literary criticism, and the philosophy of history. In three original case studies, presence illuminates the relationships among photography, the past, memory, and the Other. What these diverse but overlapping essays have in common is a shared commitment to investigate the attempt to reconnect meaning with something “real” and to push the paradigm of presence beyond its current uses. The volume is thus an important intervention in the most fundamental debates within the humanities today. Contributors: Bill Ashcroft, University of New South Wales; Mark Bevir, University of California, Berkeley; Susan A. Crane, University of Arizona; Ranjan Ghosh, University of North Bengal; Suman Gupta, Open University Ethan Kleinberg, Wesleyan University; John Michael, University of Rochester; Vincent P. Pecora, University of Utah; Roger I. Simon. (shrink)

Although not a professional historian, the author raises several issues pertinent to the state of history today.Qualifying the "non-historian" as an "able" interventionist in historical studies, the author explores the relationship between ...

Ghosh introduces the term 'plastic turn' and gives a new direction for how we can interpret and experience the turn today. By what he calls the material-aesthetic, he opens up a fresh direction in our experience and understanding of plastic through the correspondence that plastic as a material brings with the aesthetic that it inspires and figures"-.

This book provides a radical rethinking of the prominent Indian thinker Rabindranath Tagore, exploring how his philosophy of education relates to the ideas of Western theorists such as Kant, Plato and Aristotle. Tagore's thoughts on pedagogy, university and formal education are subjected to a fascinating critique within Ghosh's transcultural framework, referencing a wide range of thinkers across varying time periods, places, and cultures, and developing a greater sensitivity to other traditions, languages, and forms of thinking and writing. The book (...) changes the way we have so far thought about the educationist Tagore, and will be of interest to scholars and specialists of literature, Indian history, and philosophy of education. It is political, deeply philosophical and has a transcultural take on our understanding of a variety of issues relating to Tagore and to philosophy of education in general. (shrink)

This book provides an introduction to Newtonian and relativistic mechanics. Unlike other books on the topic, which generally take a 'top-down' approach, it follows a novel system to show how the concepts of the 'science of motion' evolved through a veritable jungle of intermediate ideas and concepts. Starting with Aristotelian philosophy, the text gradually unravels how the human mind slowly progressed towards the fundamental ideas of inertia physics. The concepts that now appear so obvious to even a high school student (...) took great intellectuals more than a millennium to clarify. The book explores the evolution of these concepts through the history of science. After a comprehensive overview of the discovery of dynamics, it explores fundamental issues of the properties of space and time and their relation with the laws of motion. It also explores the concepts of spatio-temporal locality and fields, and offers a philosophical discussion of relative motion versus absolute motion, as well as the concept of an absolute space. Furthermore, it presents Galilean transformation and the principle of relativity, inadequacy of Galilean relativity and emergence of the spatial theory of relativity with an emphasis on physical understanding, as well as the debate over relative motion versus absolute motion and Mach's principle followed by the principle of equivalence. The natural follow-on to this section is the physical foundations of general theory of relativity. Lastly, the book ends with some new issues and possibilities regarding further modifications of the laws of motion leading to the solution of a number of fundamental issues closely connected with the characteristics of the cosmos. It is a valuable resource for undergraduate students of physics, engineering, mathematics, and related disciplines. It is also suitable for interdisciplinary coursework and introductory reading outside the classroom. (shrink)

Since the conceptualization of unethical pro-organizational behavior ten years ago, scholarly interest in exploring this phenomenon has multiplied. Given a burgeoning body of empirical research, a review of unethical pro-organizational behavior literature is warranted. This study, therefore, systematically reviews the extant literature on unethical pro-organizational behavior and presents a comprehensive theory-based review of the past developments in this field. We classify previous studies based on their underlying theoretical perspectives and discuss the antecedents and consequences of unethical pro-organizational behavior in work (...) context. We also explicate the boundary conditions under which the influence of these antecedents gets accentuated or alleviated. Overall, this study synthesizes past knowledge to elucidate why, how, and when unethical pro-organizational behavior unfolds in the workplace. Finally, the gaps in the extant theorization are identified and an agenda for future research is proposed. (shrink)

We discuss a simple logic to describe one of our favourite games from childhood, hide and seek, and show how a simple addition of an equality constant to describe the winning condition of the seeker makes our logic undecidable. There are certain decidable fragments of first-order logic which behave in a similar fashion and we add a new modal variant to that class of logics. We also discuss the relative expressive power of the proposed logic in comparison to the standard (...) modal counterparts. (shrink)

Summarization of legal case judgement documents is a practical and challenging problem, for which many summarization algorithms of different varieties have been tried. In this work, rather than developing yet another summarization algorithm, we investigate if intelligently ensembling (combining) the outputs of multiple (base) summarization algorithms can lead to better summaries of legal case judgements than any of the base algorithms. Using two datasets of case judgement documents from the Indian Supreme Court, one with extractive gold standard summaries and the (...) other with abstractive gold standard summaries, we apply various ensembling techniques on summaries generated by a wide variety of summarization algorithms. The ensembling methods applied range from simple voting-based methods to ranking-based and graph-based ensembling methods. We show that many of our ensembling methods yield summaries that are better than the summaries produced by any of the individual base algorithms, in terms of ROUGE and METEOR scores. (shrink)

When agents know a protocol, this leads them to have expectations about future observations. Agents can update their knowledge by matching their actual observations with the expected ones. They eliminate states where they do not match. In this paper, we study how agents perceive protocols that are not commonly known, and propose a semantics-driven logical framework to reason about knowledge in such scenarios. In particular, we introduce the notion of epistemic expectation models and a propositional dynamic logic-style epistemic logic for (...) reasoning about knowledge via matching agentsÊ expectations to their observations. It is shown how epistemic expectation models can be obtained from epistemic protocols. Furthermore, a characterization is presented of the effective equivalence of epistemic protocols. We introduce a new logic that incorporates updates of protocols and that can model reasoning about knowledge and observations. Finally, the framework is extended to incorporate fact-changing actions, and a worked-out example is given. © 2013 Elsevier B.V. (shrink)

We make a proposal for formalizing simultaneous games at the abstraction level of player’s powers, combining ideas from dynamic logic of sequential games and concurrent dynamic logic. We prove completeness for a new system of ‘concurrent game logic’ CDGL with respect to finite non-determined games. We also show how this system raises new mathematical issues, and throws light on branching quantifiers and independence-friendly evaluation games for first-order logic.

In the domain of legal information retrieval, an important challenge is to compute similarity between two legal documents. Precedents play an important role in The Common Law system, where lawyers need to frequently refer to relevant prior cases. Measuring document similarity is one of the most crucial aspects of any document retrieval system which decides the speed, scalability and accuracy of the system. Text-based and network-based methods for computing similarity among case reports have already been proposed in prior works but (...) not without a few pitfalls. Since legal citation networks are generally highly disconnected, network based metrics are not suited for them. Till date, only a few text-based and predominant embedding based methods have been employed, for instance, TF-IDF based approaches, Word2Vec and Doc2Vec based approaches. We investigate the performance of 56 different methodologies for computing textual similarity across court case statements when applied on a dataset of Indian Supreme Court Cases. Among the 56 different methods, thirty are adaptations of existing methods and twenty-six are our proposed methods. The methods studied include models such as BERT and Law2Vec. It is observed that the more traditional methods that rely on a bag-of-words representation performs better than the more advanced context-aware methods for computing document-level similarity. Finally we nominate, via empirical validation, five of our best performing methods as appropriate for measuring similarity between case reports. Among these five, two are adaptations of existing methods and the other three are our proposed methods. (shrink)

The task of rhetorical role labeling is to assign labels (such as Fact, Argument, Final Judgement, etc.) to sentences of a court case document. Rhetorical role labeling is an important problem in the field of Legal Analytics, since it can aid in various downstream tasks as well as enhances the readability of lengthy case documents. The task is challenging as case documents are highly various in structure and the rhetorical labels are often subjective. Previous works for automatic rhetorical role identification (...) (i) mainly used Conditional Random Fields over manually handcrafted features, and (ii) focused on certain law domains only (e.g., Immigration cases, Rent law), and a particular jurisdiction/country (e.g., US, Canada, India). In this work, we improve upon the prior works on rhetorical role identification by proposing novel Deep Learning models for automatically identifying rhetorical roles, which substantially outperform the prior methods. Additionally, we show the effectiveness of the proposed models over documents from five different law domains, and from two different jurisdictions—the Supreme Court of India and the Supreme Court of the UK. Through extensive experiments over different variations of the Deep Learning models, including Transformer models based on BERT and LegalBERT, we show the robustness of the methods for the task. We also perform an extensive inter-annotator study and analyse the agreement of the predictions of the proposed model with the annotations by domain experts. We find that some rhetorical labels are inherently hard/subjective and both law experts and neural models frequently get confused in predicting them correctly. (shrink)

The Transforming growth factor beta (TGF‐β) family of secreted proteins regulates a variety of key events in normal development and physiology. In mammals, this family, represented by 33 ligands, including TGF‐β, activins, nodal, bone morphogenetic proteins (BMPs), and growth and differentiation factors (GDFs), regulate biological processes as diverse as cell proliferation, differentiation, apoptosis, metabolism, homeostasis, immune response, wound repair, and endocrine functions. In Drosophila, only 7 members of this family are present, with 4 TGF‐β/BMP and 3 TGF‐β/activin ligands. Studies in (...) the fly have illustrated the role of TGF‐β/BMP ligands during embryogenesis and organ patterning, while the TGF‐β/activin ligands have been implicated in the control of wing growth and neuronal functions. In this review, we focus on the emerging roles of Drosophila TGF‐β/activins in inter‐organ communication via long‐distance regulation, especially in systemic lipid and carbohydrate homeostasis, and discuss findings relevant to metabolic diseases in humans. -/- . (shrink)

As health systems around the world turn towards highly distributed, specialized and cooperative structures to increase quality and safety of care as well as efficiency and efficacy of delivery processes, there is a growing need for supporting communication and collaboration of all parties involved with advanced ICT solutions. The Electronic Health Record (EHR) provides the information platform which is maturing towards the eHealth core application. To meet the requirements for sustainable, semantically interoperable, and trustworthy EHR solutions, different standards and different (...) national strategies have been established. The workshop summarizes the requirements for such advanced EHR systems and their underlying architecture, presents different strategies and solutions advocated by corresponding protagonists, discusses pros and cons as well as harmonization and migration strategies for those approaches. It particularly highlights a turn towards ontology-driven architectures. (shrink)

Connected vehicle fleets have formed significant component of industrial internet of things scenarios as part of Industry 4.0 worldwide. The number of vehicles in these fleets has grown at a steady pace. The vehicles monitoring with machine learning algorithms has significantly improved maintenance activities. Predictive maintenance potential has increased where machines are controlled through networked smart devices. Here, benefits are accrued considering uptimes optimization. This has resulted in reduction of associated time and labor costs. It has also provided significant increase (...) in cost benefit ratios. Considering vehicle fault trends in this research predictive maintenance problem is addressed through hybrid deep learning-based ensemble method (HDLEM). The ensemble framework which acts as predictive analytics engine comprises of three deep learning algorithms viz modified cox proportional hazard deep learning (MCoxPHDL), modified deep learning embedded semi supervised learning (MDLeSSL) and merged LSTM (MLSTM) networks. Both sensor as well as historical maintenance data are collected and prepared using benchmarking methods for HDLEM training and testing. Here, times between failures (TBF) modeling and prediction on multi-source data are successfully achieved. The results obtained are compared with stated deep learning models. This ensemble framework offers great potential towards achieving more profitable, efficient and sustainable vehicle fleet management solutions. This helps better telematics data implementation which ensures preventative management towards desired solution. The ensemble method's superiority is highlighted through several experimental results. (shrink)

In a Common Law system, legal practitioners need frequent access to prior case documents that discuss relevant legal issues. Case documents are generally very lengthy, containing complex sentence structures, and reading them fully is a strenuous task even for legal practitioners. Having a concise overview of these documents can relieve legal practitioners from the task of reading the complete case statements. Legal catchphrases are (multi-word) phrases that provide a concise overview of the contents of a case document, and automated generation (...) of catchphrases is a challenging problem in legal analytics. In this paper, we propose a novel supervised neural sequence tagging model for the extraction of catchphrases from legal case documents. Specifically, we show that incorporating document-specific information along with a sequence tagging model can enhance the performance of catchphrase extraction. We perform experiments over a set of Indian Supreme Court case documents, for which the gold-standard catchphrases (annotated by legal practitioners) are obtained from a popular legal information system. The performance of our proposed method is compared with that of several existing supervised and unsupervised methods, and our proposed method is empirically shown to be superior to all baselines. (shrink)

This paper attempts to unravel how a reader embraces the idea of moral education while enjoying the aesthetic pleasure of the Harry Potter series. It develops a view on moral education through literary experience, which is intrinsically intertwined with aesthetic experience. The amalgamation of reality and fantasy in the Harry Potter novels creates an authenticity that can easily capture the moral attention of a reader by which his/her self-realized valuable emotional intelligence takes place. The well-knit plot encourages reader's self-efficacy (“I” (...) reactive attitude) that triggers the sui-generis, first-personal sense of morality and gradually develops the third-personal “we” attitude. Finally, based on an empirical study, the article explains how the Harry Potter series is productive in building the reader's positive moral psychology through different applications like moral agency, moral point of view, and moral judgment. (shrink)

Introduction: Intimate Partner Violence (IPV) has unfavorable consequences for women as well as for newborn babies, which is very serious and preventable public health problem. It is believed to have an excessive occurrence in lives of women in South Asia. The objective of this study is to describe the prevalence, risk factors and consequences of IPV in Bangladesh. Methods: A scoping review was carried out based on the past 12 years of posted and gray literature about IPV in Bangladesh using (...) Arksey and O’Malley’s framework. Only the literature addressing abuses or violence in households or outside including physical, sexual or mental violence on the married woman in Bangladesh were taken into consideration for the study. Results: The overall prevalence of IPV in Bangladesh, the latest reviews of rates ranging from 15.5-82.7%.Most of the IPV in Bangladesh was based totally on the experience of legally married women. The main risk factors of IPV in Bangladesh were women being younger, from lower socioeconomic reputation, from lower academic attainment and lower education of husband, dowry, child marriage, perceived disobedience of wives, family conflict, children had recently been ill, and incapability of to furnish sexual satisfaction. Maternal depressive symptoms, signs of stress, anxiety and constraint to the better health of young children are the main consequences of IPV in Bangladesh. Besides, IPV causes unwanted pregnancy, pregnancy loss in the form of miscarriage, induced abortion, or stillbirth and termination of pregnancy in Bangladesh. Conclusions: Woman’s empowerment may reduce IPV and understanding attitudes towards IPV in cultural context could be crucial for developing interventions to reduce IPV and its consequences. (shrink)

We discuss a simple logic to describe one of our favourite games from childhood, hide and seek, and show how a simple addition of an equality constant to describe the winning condition of the seeker makes our logic undecidable. There are certain decidable fragments of first-order logic which behave in a similar fashion with respect to such a language extension, and we add a new modal variant to that class. We discuss the relative expressive power of the proposed logic in (...) comparison to the standard modal counterparts. We prove that the model checking problem for the resulting logic is \(\textsf{P}\) -complete. In addition, by exploring the connection with related product logics, we gain more insight towards having a better understanding of the subtleties of the proposed framework. (shrink)