scholarly journals Term Spotting: A Quick-and-dirty Method for Extracting Typological Features of Language from Grammatical Descriptions

2021 ◽  
Author(s):  
Harald Hammarström ◽  
One-Soon Her ◽  
Marc Tang
Keyword(s):  
Vector Space ◽  
Gold Standard ◽  
Training Data ◽  
Large Collection ◽  
General Technique ◽  
Background Theory ◽  
Specific Term ◽  
The World ◽  
Morphological Variants

Starting from a large collection of digitized raw-text descriptions of languages of the world, we address the problem of extracting information of interest to linguists from these. We describe a general technique to extract properties of the described languages associated with a specific term. The technique is simple to implement, simple to explain, requires no training data or annotation, and requires no manual tuning of thresholds. The results are evaluated on a large gold standard database on classifiers with accuracy results that match or supersede human inter-coder agreement on similar tasks. Although accuracy is competitive, the method may still be enhanced by a more rigorous probabilistic background theory and usage of extant NLP tools for morphological variants, collocations and vector-space semantics.

Introduction: The Translation History of Virgil

2018 ◽  
Author(s):  
Susanna Braund ◽  
Zara Martirosova Torlone
Keyword(s):  
Case Studies ◽  
Large Collection ◽  
The World ◽  
History Of ◽  
The Individual

The introduction describes the broad landscape of translation of Virgil from both the theoretical and the practical perspectives. It then explains the genesis of the volume and indicates how the individual chapters, each one of which is summarized, fit into the complex tapestry of Virgilian translation activity through the centuries and across the world. The volume editors indicate points of connection between the chapters in order to render the whole greater than the sum of its parts. Braund and Torlone emphasize that a project such as this could look like a (rather large) collection of case studies; they therefore consider it important to extrapolate larger phenomena from the specifics presented here

scholarly journals Quantum chemical benchmark databases of gold-standard dimer interaction energies

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Alexander G. Donchev ◽  
Andrew G. Taube ◽  
Elizabeth Decolvenaere ◽  
Cory Hargus ◽  
Robert T. McGibbon ◽  
...  
Keyword(s):  
Machine Learning ◽  
Gold Standard ◽  
Training Data ◽  
Structure Theory ◽  
Cluster Method ◽  
Coupled Cluster ◽  
Interaction Energies ◽  
Gold Standard Method ◽  
Representative Subset ◽  
Semi Empirical

AbstractAdvances in computational chemistry create an ongoing need for larger and higher-quality datasets that characterize noncovalent molecular interactions. We present three benchmark collections of quantum mechanical data, covering approximately 3,700 distinct types of interacting molecule pairs. The first collection, which we refer to as DES370K, contains interaction energies for more than 370,000 dimer geometries. These were computed using the coupled-cluster method with single, double, and perturbative triple excitations [CCSD(T)], which is widely regarded as the gold-standard method in electronic structure theory. Our second benchmark collection, a core representative subset of DES370K called DES15K, is intended for more computationally demanding applications of the data. Finally, DES5M, our third collection, comprises interaction energies for nearly 5,000,000 dimer geometries; these were calculated using SNS-MP2, a machine learning approach that provides results with accuracy comparable to that of our coupled-cluster training data. These datasets may prove useful in the development of density functionals, empirically corrected wavefunction-based approaches, semi-empirical methods, force fields, and models trained using machine learning methods.

scholarly journals Experiments of Image Classification Using Dissimilarity Spaces Built with Siamese Networks

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1573
Author(s):  
Loris Nanni ◽  
Giovanni Minchio ◽  
Sheryl Brahnam ◽  
Gianluca Maguolo ◽  
Alessandra Lumini
Keyword(s):  
Vector Space ◽  
Image Classification ◽  
Ad Hoc ◽  
Feature Space ◽  
Medical Data ◽  
Training Data ◽  
Data Sets ◽  
Large Set ◽  
Clustering Methods ◽  
Siamese Networks

Traditionally, classifiers are trained to predict patterns within a feature space. The image classification system presented here trains classifiers to predict patterns within a vector space by combining the dissimilarity spaces generated by a large set of Siamese Neural Networks (SNNs). A set of centroids from the patterns in the training data sets is calculated with supervised k-means clustering. The centroids are used to generate the dissimilarity space via the Siamese networks. The vector space descriptors are extracted by projecting patterns onto the similarity spaces, and SVMs classify an image by its dissimilarity vector. The versatility of the proposed approach in image classification is demonstrated by evaluating the system on different types of images across two domains: two medical data sets and two animal audio data sets with vocalizations represented as images (spectrograms). Results show that the proposed system’s performance competes competitively against the best-performing methods in the literature, obtaining state-of-the-art performance on one of the medical data sets, and does so without ad-hoc optimization of the clustering methods on the tested data sets.

scholarly journals Histamine Intolerance—The More We Know the Less We Know. A Review

Nutrients ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 2228
Author(s):  
Martin Hrubisko ◽  
Radoslav Danis ◽  
Martin Huorka ◽  
Martin Wawruch
Keyword(s):  
Gold Standard ◽  
Multidisciplinary Approach ◽  
Adverse Reactions ◽  
Immunological Response ◽  
Food Intolerance ◽  
Therapeutic Approaches ◽  
Complex Time ◽  
Histamine Intolerance ◽  
The World ◽  
H1 Antihistamines

The intake of food may be an initiator of adverse reactions. Food intolerance is an abnormal non-immunological response of the organism to the ingestion of food or its components in a dosage normally tolerated. Despite the fact that food intolerance is spread throughout the world, its diagnosing is still difficult. Histamine intolerance (HIT) is the term for that type of food intolerance which includes a set of undesirable reactions as a result of accumulated or ingested histamine. Manifestations may be caused by various pathophysiological mechanisms or a combination of them. The problem with a “diagnosis” of HIT is precisely the inconstancy and variety of the manifestations in the same individual following similar stimuli. The diagnosing of HIT therefore requires a complex time-demanding multidisciplinary approach, including the systematic elimination of disorders with a similar manifestation of symptoms. Among therapeutic approaches, the gold standard is a low-histamine diet. A good response to such a diet is considered to be confirmation of HIT. Alongside the dietary measures, DAO supplementation supporting the degradation of ingested histamine may be considered as subsidiary treatment for individuals with intestinal DAO deficiency. If antihistamines are indicated, the treatment should be conscious and time-limited, while 2nd or 3rd generation of H1 antihistamines should take precedence.

scholarly journals Depression-level assessment from multi-lingual conversational speech data using acoustic and text features

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Cenk Demiroglu ◽  
Aslı Beşirli ◽  
Yasin Ozkanca ◽  
Selime Çelik
Keyword(s):  
Text Analysis ◽  
Training Data ◽  
Conversational Speech ◽  
Acoustic Feature ◽  
The World ◽  
Significant Burden ◽  
Depression Assessment ◽  
Depression Level ◽  
Text Features ◽  
Multiple Languages

AbstractDepression is a widespread mental health problem around the world with a significant burden on economies. Its early diagnosis and treatment are critical to reduce the costs and even save lives. One key aspect to achieve that goal is to use technology and monitor depression remotely and relatively inexpensively using automated agents. There has been numerous efforts to automatically assess depression levels using audiovisual features as well as text-analysis of conversational speech transcriptions. However, difficulty in data collection and the limited amounts of data available for research present challenges that are hampering the success of the algorithms. One of the two novel contributions in this paper is to exploit databases from multiple languages for acoustic feature selection. Since a large number of features can be extracted from speech, given the small amounts of training data available, effective data selection is critical for success. Our proposed multi-lingual method was effective at selecting better features than the baseline algorithms, which significantly improved the depression assessment accuracy. The second contribution of the paper is to extract text-based features for depression assessment and use a novel algorithm to fuse the text- and speech-based classifiers which further boosted the performance.

Happiness in Nations

2018 ◽  
Author(s):  
Ruut Veenhoven
Keyword(s):  
Large Collection ◽  
Pursuit Of Happiness ◽  
The World ◽  
Public Happiness ◽  
Research Findings

Today1 there is increasing support for the idea that governments should aim at greater happiness for a greater number of citizens. Is this a mission impossible? The following questions arise in this context: (1) Is greater happiness in a nation feasible? (2) If so, can governments do much about it? (3) If so, what can governments do to raise happiness in their country? (4) How does the pursuit of happiness fit with other political aims? In this paper, I take stock of the available research findings on happiness that bear answers to these questions. To do this, I use a large collection of research findings gathered in the World Database of Happiness. These data show that greater happiness is possible, and indicate some ways to achieve this goal. The pursuit of public happiness fits well with several other policy aims.

scholarly journals A Model of the International Monetary System*

2017 ◽  
Vol 133 (1) ◽  
pp. 295-355 ◽  
Author(s):  
Emmanuel Farhi ◽  
Matteo Maggiori
Keyword(s):  
Simple Model ◽  
Gold Standard ◽  
Supply And Demand ◽  
International Monetary System ◽  
Rate System ◽  
Monetary System ◽  
The World ◽  
The Common ◽  
Triffin Dilemma ◽  
World Supply

AbstractWe propose a simple model of the international monetary system. We study the world supply and demand for reserve assets denominated in different currencies under a variety of scenarios: a hegemon versus a multipolar world; abundant versus scarce reserve assets; and a gold exchange standard versus a floating rate system. We rationalize the Triffin dilemma, which posits the fundamental instability of the system, as well as the common prediction regarding the natural and beneficial emergence of a multipolar world, the Nurkse warning that a multipolar world is more unstable than a hegemon world, and the Keynesian argument that a scarcity of reserve assets under a gold standard or at the zero lower bound is recessionary. Our analysis is both positive and normative.

scholarly journals The UK-US Game and UK's Return to Gold Standard

2020 ◽  
Vol 5 (4) ◽  
pp. 324
Author(s):  
Zheming Zhang
Keyword(s):  
United States ◽  
World War Ii ◽  
World War I ◽  
Economic System ◽  
Gold Standard ◽  
International Economic Order ◽  
The United States ◽  
World War ◽  
The World ◽  
The Uk

<p>With the continuous development and evolution of the United States, especially the economic center shift after World War II, the United States become the economic hegemon instead of the UK and thus it seized the economic initiative of the world. After the World War I, the European countries gradually withdraw from the gold standard. In order to stabilize the world economy development and the international economic order, the United States prepared to build the economic system related with its own interests so as to force the UK to return to the gold standard. The game between the United States and the UK shows the significance of economic initiative. Among them, the outcome of the two countries in the fight of the financial system also demonstrates a significant change in the world economic system.</p>

scholarly journals Leptospirosis

2016 ◽  
Vol 8 (3) ◽  
Author(s):  
Novie H. Rampengan
Keyword(s):  
Gold Standard ◽  
Case Fatality Rate ◽  
Severe Disease ◽  
Case Fatality ◽  
Agglutination Test ◽  
Microscopic Agglutination Test ◽  
Moderate Risk ◽  
Rat Urine ◽  
The World ◽  
Different Parts

Abstract: Leptospirosis is a zoonotic disease that usually occurs during the flood and is generally transmitted through rat urine. Indonesia is a country with a moderate risk of transmission of leptospirosis. Leptospirosis has a broad manifestation varying from self-limited to severe disease. The gold standard examination of leptospirosis is microscopic agglutination test. Diagnosis is divided into suspected, probable, and confirmed. Treatment consists of antibiotics and supportive agents. Generally, the prognosis is good, albeit, sequelae can occur. Case-fatality rate in different parts of the world ranging from less than 5% to 30%.Keywords: leptospirosis, diagnosis,Abstrak: Leptospirosis merupakan penyakit zoonosis yang umumnya timbul saat banjir dan umumnya ditularkan melalui kencing tikus. Indonesia merupakan negara dengan risiko sedang penularan leptospirosis. Leptospirosis memiliki manifestasi luas dari self limited hingga sakit berat. Pemeriksaan baku emas leptospirosis ialah dengan microscopic agglutination test. Diagnosis dibagi atas suspek, probable, dan konfirmasi. Terapi diberikan medikamentosa dengan antibiotik dan suportif. Prognosis umumnya baik namun bisa juga terjadi gejala sisa. Tingkat fatalitas kasus di berbagai belahan dunia berkisar <5%-30%.Kata kunci: leptospirosis, diagnosis

scholarly journals Crowdsourcing snake identification with online communities of professional herpetologists and avocational snake enthusiasts

2021 ◽  
Vol 8 (1) ◽  
pp. 201273
Author(s):  
A. M. Durso ◽  
I. Bolon ◽  
A. R. Kleinhesselink ◽  
M. R. Mondardini ◽  
J. L. Fernandez-Marquez ◽  
...  
Keyword(s):  
Citizen Science ◽  
Gold Standard ◽  
Healthcare Workers ◽  
Geographical Origin ◽  
Species Level ◽  
Community Members ◽  
Venomous Snake ◽  
Building Capacity ◽  
The World ◽  
Treatment Data

Species identification can be challenging for biologists, healthcare practitioners and members of the general public. Snakes are no exception, and the potential medical consequences of venomous snake misidentification can be significant. Here, we collected data on identification of 100 snake species by building a week-long online citizen science challenge which attracted more than 1000 participants from around the world. We show that a large community including both professional herpetologists and skilled avocational snake enthusiasts with the potential to quickly (less than 2 min) and accurately (69–90%; see text) identify snakes is active online around the clock, but that only a small fraction of community members are proficient at identifying snakes to the species level, even when provided with the snake's geographical origin. Nevertheless, participants showed great enthusiasm and engagement, and our study provides evidence that innovative citizen science/crowdsourcing approaches can play significant roles in training and building capacity. Although identification by an expert familiar with the local snake fauna will always be the gold standard, we suggest that healthcare workers, clinicians, epidemiologists and other parties interested in snakebite could become more connected to these communities, and that professional herpetologists and skilled avocational snake enthusiasts could organize ways to help connect medical professionals to crowdsourcing platforms. Involving skilled avocational snake enthusiasts in decision making could build the capacity of healthcare workers to identify snakes more quickly, specifically and accurately, and ultimately improve snakebite treatment data and outcomes.

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