scholarly journals LDA method in psychological assessment of text comprehension

2021 ◽  
Author(s):  
С.А. Свердлов
Keyword(s):  
Psychological Assessment ◽  
Text Comprehension ◽  
Advantages And Disadvantages ◽  
Text Understanding ◽  
Modern Psychology ◽  
Wide Range ◽  
Psychology Pedagogy ◽  
The Moment ◽  
Comparison Of The Results ◽  
Different Content

Проблема понимания текстов и способов его оценки является одной из фундаментальных для современной психологии, педагогики, лингвистики. На настоящий момент имеется большое количество попыток выработки метода оценки понимания текстов, который бы отражал объективную картину интериоризации материала текста читателем, и вместе с тем подходил бы для стандартизации и применения на широком диапазоне текстов различного содержания и структуры, по возможности с минимальными затратами ресурсов оценщика и самого читателя. В настоящей статье раскрываются современные подходы к оценке понимания текстов, их преимущества и недостатки, и формулируется новый перспективный метод оценки понимания текстов, использующий в своём основании модель Латентного размещения Дирихле. Данный метод затем проходит исследование валидности через сравнение результатов его применения и наиболее часто используемых современных методов оценки понимания текстов, делается вывод о его применимости в реальных условиях и перспективах использования в спектре прикладных задач. The problem of understanding texts and methods of assessing it is one of the fundamental for modern psychology, pedagogy, linguistics. At the moment, there are a large number of attempts to develop a method for assessing the understanding of texts, which would reflect an objective picture of the internalization of the material of the text by the reader, and at the same time would be suitable for standardization and application on a wide range of texts of different content and structure, if possible with minimal expenditure of resources of the evaluator and the reader himself. This article reveals modern approaches to assessing text understanding, their advantages and disadvantages, and formulates a new promising method for assessing text understanding, based on the Dirichlet Latent Placement model. This method then goes through a validity study through a comparison of the results of its application and the most commonly used modern methods for assessing text understanding, a conclusion is made about its applicability in real conditions and the prospects for use in a range of applied problems.

scholarly journals Tools Of Causal Inference: Review and Prospects

2020 ◽  
pp. 52-63
Author(s):  
Olha M. Bespala ◽  
Keyword(s):  
Computer Technology ◽  
Software Projects ◽  
Advantages And Disadvantages ◽  
Current State ◽  
Scientific Institutions ◽  
Wide Range ◽  
Human Thinking ◽  
The Moment ◽  
Automated Software ◽  
Further Development

Introduction. The need to establish causality covers a fairly wide range of different industries with different specifics and approaches. Therefore, it becomes necessary to apply various methods to solve the assigned tasks (in the context of causality), which is accompanied by the choice of a wide range of tools, depending on the task at hand. Purpose. The purpose of this work is a brief overview and analysis of modern methods, algorithms and technologies for detecting causation and the range of tasks in which the use of the appropriate tools takes place. Methods. Starting from the gold standards of causal identification and to more accurate, but limited by the range of conditions, algorithms, the current state, advantages and disadvantages of the use of tools are described. Result. The analysis of the current state of existing methods, algorithms and technologies for establishing causality is carried out, the prospects for further development and improvement of tools for causal detection are examined. Conclusions. At the moment there is a large list of known methods, algorithms and technologies, there is a number of problems in which there is a need for more accurate detection of causality. The paper shows that most of the tools for establishing causality give good results for acyclic structures, at the same time, they can give false positive conclusions for cyclic structures. Well-known world scientific institutions and leading corporations of computer technology are fruitfully engaged in the development and implementation of more and more perfect tools for establishing causality in order to develop automated software projects close to human thinking.

Industrial Labour Force of Russia in 20-30s of XX Century in Russian Historiography

2020 ◽  
pp. 431-449
Author(s):  
Oleg V. Shekatunov ◽  
Konstantin G. Malykhin
Keyword(s):  
Labour Force ◽  
Historical Period ◽  
Russian Industry ◽  
Wide Range ◽  
Scientific Papers ◽  
Potential Formation ◽  
The Moment ◽  
Force Potential ◽  
Modern Russian

The article is devoted to the specifics of studying the industrial labour force of Russia in the 1920s - 1930s in Russian historiography. The various stages of study from the 1920s through the 1930s and up to the last years are concerned. The relevance of the study is due to several factors. These include contradictions in the assessments of Bolshevik modernization of the 1920s and 1930s; projected labour force shortages in modern Russia; as well as the existing labour force shortage in industry at the moment. This determines the relevance of studying the historical period, which was characterized by the most acute personnel problems in the country. The novelty of the study is due to the fact that in modern Russian historiography there is no holistic, integrated view of the problems of the labour force potential formation of Russian industry in the 1920s and 1930s. It is noted that there is no research aimed at analyzing the historiography of these problems. The main stages of the study of industrial labour force are highlighted. The analysis of scientific works correlated with each stage of the study of the topic is performed. The problems and methodology of each stage are considered. A review of a wide range of scientific papers both articles and thesis is presented.

The Management of Post-Tonsillectomy Morbidity in Patients With Sleep Apnoea

2019 ◽  
Vol 70 (10) ◽  
pp. 3738-3740
Keyword(s):  
Day Surgery ◽  
Sleep Apnoea ◽  
Integrative Approach ◽  
Multicenter Studies ◽  
Therapeutic Modalities ◽  
Advantages And Disadvantages ◽  
Obstructive Sleep ◽  
Wide Range ◽  
The Impact ◽  
Surgery Center

The Tonsillectomy in children or adults is an intervention commonly encountered in the ENT (Ear Nose and Throat) and Head and Neck surgeon practice. The current tendency is to perform this type of surgery in major ambulatory surgery centers. Two objectives are thus pursued: first of all, the increase of the patient quality of life through the reintegration into the family as quickly as possible and secondly, the expenses associated with continuous hospitalization are reduced. Any tertiary (multidisciplinary) sleep center must ensure the complete diagnosis and treatment (including surgery) of sleep respiratory disorders. Under these conditions the selection of patients and especially the implementation of the specific protocols in order to control the postoperative complications it becomes essential. The present paper describes our experience of tonsillectomy as treatment for selected patients with chronic rhonchopathy (snoring) and mild to moderate obstructive sleep apnoea. It was presented the impact of antibiotics protocols in reducing the main morbid outcomes following tonsillectomy, in our day surgery center. The obtained results can also be a prerequisite for the integrative approach of the patients with sleep apnoea who were recommended surgical treatment. Considering the wide range of therapeutic modalities used in sleep apnoea, each with its specific advantages and disadvantages, more extensive and multicenter studies are needed. Keywords: post-tonsillectomy morbidity, day surgery center, sleep disorders

Potential Triazole-based Molecules for the Treatment of Neglected Diseases

2019 ◽  
Vol 26 (23) ◽  
pp. 4403-4434 ◽  
Author(s):  
Susimaire Pedersoli Mantoani ◽  
Peterson de Andrade ◽  
Talita Perez Cantuaria Chierrito ◽  
Andreza Silva Figueredo ◽  
Ivone Carvalho
Keyword(s):  
Effective Treatment ◽  
Chagas Disease ◽  
Medicinal Chemistry ◽  
Biological Activities ◽  
Neglected Diseases ◽  
Triazole Derivatives ◽  
Wide Range ◽  
The World ◽  
Great Relevance ◽  
The Moment

Neglected Diseases (NDs) affect million of people, especially the poorest population around the world. Several efforts to an effective treatment have proved insufficient at the moment. In this context, triazole derivatives have shown great relevance in medicinal chemistry due to a wide range of biological activities. This review aims to describe some of the most relevant and recent research focused on 1,2,3- and 1,2,4-triazolebased molecules targeting four expressive NDs: Chagas disease, Malaria, Tuberculosis and Leishmaniasis.

scholarly journals Advancements in Assessments of Bio-Tissue Engineering and Viable Cell Delivery Matrices Using Bile Acid-Based Pharmacological Biotechnologies

Nanomaterials ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1861
Author(s):  
Armin Mooranian ◽  
Melissa Jones ◽  
Corina Mihaela Ionescu ◽  
Daniel Walker ◽  
Susbin Raj Wagle ◽  
...  
Keyword(s):  
Tissue Engineering ◽  
Viable Cell ◽  
Cell Delivery ◽  
Artificial Organ ◽  
Bioartificial Pancreas ◽  
Advantages And Disadvantages ◽  
Wide Range ◽  
Bioartificial Organs ◽  
Significant Interest ◽  
Modern Technologies

The utilisation of bioartificial organs is of significant interest to many due to their versatility in treating a wide range of disorders. Microencapsulation has a potentially significant role in such organs. In order to utilise microcapsules, accurate characterisation and analysis is required to assess their properties and suitability. Bioartificial organs or transplantable microdevices must also account for immunogenic considerations, which will be discussed in detail. One of the most characterized cases is the investigation into a bioartificial pancreas, including using microencapsulation of islets or other cells, and will be the focus subject of this review. Overall, this review will discuss the traditional and modern technologies which are necessary for the characterisation of properties for transplantable microdevices or organs, summarizing analysis of the microcapsule itself, cells and finally a working organ. Furthermore, immunogenic considerations of such organs are another important aspect which is addressed within this review. The various techniques, methodologies, advantages, and disadvantages will all be discussed. Hence, the purpose of this review is providing an updated examination of all processes for the analysis of a working, biocompatible artificial organ.

scholarly journals EXPRESS: Overcoming the Cold Start Problem of CRM using a Probabilistic Machine Learning Approach

2021 ◽  
pp. 002224372110329
Author(s):  
Nicolas Padilla ◽  
Eva Ascarza
Keyword(s):  
Machine Learning ◽  
Cold Start ◽  
Customer Relationship ◽  
Exponential Families ◽  
Modeling Framework ◽  
Wide Range ◽  
The Moment ◽  
Probabilistic Machine Learning ◽  
Marketing Actions ◽  
Cold Start Problem

The success of Customer Relationship Management (CRM) programs ultimately depends on the firm's ability to identify and leverage differences across customers — a very diffcult task when firms attempt to manage new customers, for whom only the first purchase has been observed. For those customers, the lack of repeated observations poses a structural challenge to inferring unobserved differences across them. This is what we call the “cold start” problem of CRM, whereby companies have difficulties leveraging existing data when they attempt to make inferences about customers at the beginning of their relationship. We propose a solution to the cold start problem by developing a probabilistic machine learning modeling framework that leverages the information collected at the moment of acquisition. The main aspect of the model is that it exibly captures latent dimensions that govern the behaviors observed at acquisition as well as future propensities to buy and to respond to marketing actions using deep exponential families. The model can be integrated with a variety of demand specifications and is exible enough to capture a wide range of heterogeneity structures. We validate our approach in a retail context and empirically demonstrate the model's ability at identifying high-value customers as well as those most sensitive to marketing actions, right after their first purchase.

scholarly journals Ureido Functionalization through Amine-Urea Transamidation under Mild Reaction Conditions

Polymers ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 1583
Author(s):  
Natalia Guerrero-Alburquerque ◽  
Shanyu Zhao ◽  
Daniel Rentsch ◽  
Matthias M. Koebel ◽  
Marco Lattuada ◽  
...  
Keyword(s):  
Aqueous Media ◽  
Reaction Times ◽  
Reaction Rates ◽  
Secondary Amines ◽  
Isocyanic Acid ◽  
Advantages And Disadvantages ◽  
Major Disadvantage ◽  
Wide Range ◽  
Potential Alternative ◽  
Full Conversion

Ureido-functionalized compounds play an indispensable role in important biochemical processes, as well as chemical synthesis and production. Isocyanates, and KOCN in particular, are the preferred reagents for the ureido functionalization of amine-bearing compounds. In this study, we evaluate the potential of urea as a reagent to graft ureido groups onto amines at relatively low temperatures (<100 °C) in aqueous media. Urea is an inexpensive, non-toxic and biocompatible potential alternative to KOCN for ureido functionalization. From as early as 1864, urea was the go-to reagent for polyurea polycondensation, before falling into disuse after the advent of isocyanate chemistry. We systematically re-investigate the advantages and disadvantages of urea for amine transamidation. High ureido-functionalization conversion was obtained for a wide range of substrates, including primary and secondary amines and amino acids. Reaction times are nearly independent of substrate and pH, but excess urea is required for practically feasible reaction rates. Near full conversion of amines into ureido can be achieved within 10 h at 90 °C and within 24 h at 80 °C, and much slower reaction rates were determined at lower temperatures. The importance of the urea/amine ratio and the temperature dependence of the reaction rates indicate that urea decomposition into an isocyanic acid or a carbamate intermediate is the rate-limiting step. The presence of water leads to a modest increase in reaction rates, but the full conversion of amino groups into ureido groups is also possible in the absence of water in neat alcohol, consistent with a reaction mechanism mediated by an isocyanic acid intermediate (where the water assists in the proton transfer). Hence, the reaction with urea avoids the use of toxic isocyanate reagents by in situ generation of the reactive isocyanate intermediate, but the requirement to separate the excess urea from the reaction product remains a major disadvantage.

DEVELOPMENT OF AN ALGORITHM FOR FINDING ANOMALIES IN WEATHER REPORTS TO IMPROVE THE QUALITY OF FORECASTS

2021 ◽  
pp. 45-52
Author(s):  
K. G. Yashchenkov ◽  
K. S. Dymko ◽  
N. O. Ukhanov ◽  
A. V. Khnykin
Keyword(s):  
Optimal Method ◽  
Implementation Processes ◽  
Advantages And Disadvantages ◽  
Message Exchange ◽  
Text Information ◽  
Preliminary Preparation ◽  
Using Data ◽  
The Moment

The issues of using data analysis methods to find and correct errors in the reports issued by meteorologists are considered. The features of processing various types of meteorological messages are studied. The advantages and disadvantages of existing methods of classification of text information are considered. The classification methods are compared in order to identify the optimal method that will be used in the developed algorithm for analyzing meteorological messages. The prospects of using each of the methods in the developed algorithm are described. An algorithm for processing the source data is proposed, which consists in using syntactic and logical analysis to preclean the data from various kinds of noise and determine format errors for each type of message. After preliminary preparation the classification method correlates the received set of message characteristics with the previously trained model to determine the error of the current weather report and output the corresponding message to the operator in real time. The software tools used in the algorithm development and implementation processes are described. A complete description of the process of processing a meteorological message is presented from the moment when the message is entered in a text editor until the message is sent to the international weather message exchange service. The developed software is demonstrated, in which the proposed algorithm is implemented, which allows to improve the quality of messages and, as a result, the quality of meteorological forecasts. The results of the implementation of the new algorithm are described by comparing the number of messages containing various types of errors before the implementation of the algorithm and after the implementation.

Influence of Longitudinal Roughness on Friction in EHL Contacts

2004 ◽  
Vol 126 (3) ◽  
pp. 473-481 ◽  
Author(s):  
B. Jacod ◽  
C. H. Venner ◽  
P. M. Lugt
Keyword(s):  
Numerical Simulations ◽  
Operating Conditions ◽  
Simplified Approach ◽  
Curve Fit ◽  
Longitudinal Roughness ◽  
Wide Range ◽  
Equivalent Wave ◽  
Harmonic Components ◽  
Comparison Of The Results ◽  
Relative Friction

The effect of longitudinal roughness on the friction in EHL contacts is investigated by means of numerical simulations. In the theoretical model the Eyring equation is used to describe the rheological behavior of the lubricant. First the relative friction variation caused by a single harmonic roughness component is computed as a function of the amplitude and wavelength for a wide range of operating conditions. From the results a curve fit formula is derived for the relative friction variation as a function of the out-of-contact geometry of the waviness and a newly derived parameter characterizing the response of the lubricant to pressure variations. Subsequently, the case of a superposition of two harmonic components is considered. It is shown that for the effect on friction such a combined pattern can be represented by a single equivalent wave. The amplitude and the wavelength of the equivalent wave can be determined from a nonlinear relation in terms of the amplitudes and wavelengths of the individual harmonic components. Finally the approach is applied to the prediction of the effect of a real roughness profile (many components) on the friction. From a comparison of the results with full numerical simulations it appears that the simplified approach is quite accurate.

Application of neural networks in membrane separation

2020 ◽  
Vol 36 (2) ◽  
pp. 265-310 ◽  
Author(s):  
Morteza Asghari ◽  
Amir Dashti ◽  
Mashallah Rezakazemi ◽  
Ebrahim Jokar ◽  
Hadi Halakoei
Keyword(s):  
Neural Networks ◽  
Chemical Engineering ◽  
Membrane Separation ◽  
Mechanistic Model ◽  
Computing Time ◽  
Permeate Flux ◽  
Practical Applications ◽  
Advantages And Disadvantages ◽  
Wide Range ◽  
Physical And Chemical

AbstractArtificial neural networks (ANNs) as a powerful technique for solving complicated problems in membrane separation processes have been employed in a wide range of chemical engineering applications. ANNs can be used in the modeling of different processes more easily than other modeling methods. Besides that, the computing time in the design of a membrane separation plant is shorter compared to many mass transfer models. The membrane separation field requires an alternative model that can work alone or in parallel with theoretical or numerical types, which can be quicker and, many a time, much more reliable. They are helpful in cases when scientists do not thoroughly know the physical and chemical rules that govern systems. In ANN modeling, there is no requirement for a deep knowledge of the processes and mathematical equations that govern them. Neural networks are commonly used for the estimation of membrane performance characteristics such as the permeate flux and rejection over the entire range of the process variables, such as pressure, solute concentration, temperature, superficial flow velocity, etc. This review investigates the important aspects of ANNs such as methods of development and training, and modeling strategies in correlation with different types of applications [microfiltration (MF), ultrafiltration (UF), nanofiltration (NF), reverse osmosis (RO), electrodialysis (ED), etc.]. It also deals with particular types of ANNs that have been confirmed to be effective in practical applications and points out the advantages and disadvantages of using them. The combination of ANN with accurate model predictions and a mechanistic model with less accurate predictions that render physical and chemical laws can provide a thorough understanding of a process.

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