Applying Data Augmentation to Handwritten Arabic Numeral Recognition Using Deep Learning Neural Networks

Handwritten character recognition has been the center of research and a benchmark problem in the sector of pattern recognition and artificial intelligence, and it continues to be a challenging research topic. Due to its enormous application many works have been done in this field focusing on different languages. Arabic, being a diversified language has a huge scope of research with potential challenges. A convolutional neural network model for recognizing handwritten numerals in Arabic language is proposed in this paper, where the dataset is subject to various augmentation in order to add robustness needed for deep learning approach. The proposed method is empowered by the presence of dropout regularization to do away with the problem of data overfitting. Moreover, suitable change is introduced in activation function to overcome the problem of vanishing gradient. With these modifications, the proposed system achieves an accuracy of 99.4\% which performs better than every previous work on the dataset.Comment: 5 pages, 6 figures, 3 table

Hierarchical Character-Word Models for Language Identification

Social media messages' brevity and unconventional spelling pose a challenge to language identification. We introduce a hierarchical model that learns character and contextualized word-level representations for language identification. Our method performs well against strong base- lines, and can also reveal code-switching

Landscape Classification using Principal Component Analysis and Fuzzy Classification: Archaeological Sites and their Natural Surroundings in Central Mongolia

The middle and upper Orkhon Valley in Central Mongolia (47.5°N, 102.5°E) hosts a multitude of diverse archaeological features. Most of them – including the well-known ancient cities of Karakorum and Karabalgasun – have only rarely been described in their geographical setups. The aim of this study is to describe, classify and analyse their surrounding landscapes and consequently characterise these sites geographically. This analysis is based on freely available raster datasets that offer information about topography, surface reflectance and derivatives. Principal component analysis is applied as a dimensional reduction technique. Subsequently, a fuzzy-logic approach leads to a classification scheme in which archaeological features are embedded and therefore distinguishable. A distinct difference in preferences regarding to choose a site location can be made and confirmed by semiautomatic analysis, comparing burial and ritual places and settlements. Walled enclosures and settlements are connected to planar steppe regions, whereas burial and ritual places are embedded in mountainous and hilly environments

Give us a little social credit: to design or to discover personal ratings in the era of Big Data

In 2014, the State Council of the Chinese Communist Party announced the institution of a social credit system by 2020, a follow-up to a similar statement on the creation of a social credit system issued by the State Council in 2007. Social credit ratings of the type being developed by the State Council in partnership with Chinese companies go beyond existing financial credit ratings in an attempt to project less-tangible personal characteristics like trustworthiness, criminal tendencies, and group loyalty onto a single scale. The emergence of personal credit ratings is enabled by Big Data, automated decision-making processes, machine learning, and facial recognition technology. It is quite likely that various kinds of personal and social credit ratings shall become reality in the near future. We explore China\u27s version of its social credit system so far, compare the welfare and epistemological qualities of an ecology of personal ratings emanating from polycentric sources versus a social credit rating, and discuss whether a social credit system in an ideologically driven state is less a tool to maximize social welfare through trustworthiness provision and more a method of preventing and punishing deviance from a set of party-held ideological values

Reading sentences of uniform word length: evidence for the adaptation of the preferred saccade length during reading

In the current study we investigated the effect of removing word length variability within sentences on spatial aspects of eye movements during reading. Participants read sentences that were uniform in terms of word length, with each sentence consisting entirely of three, four, or five letter words, or a combination of these word lengths. Several interesting findings emerged. Adaptation of the preferred saccade length occurred for sentences with different uniform word length; participants would be more accurate at making short saccades while reading uniform sentences of three letter words, while they would be more accurate at making long saccades while reading uniform sentences of five letter words. Furthermore, word skipping was affected such that three and four letter words were more likely, and five letter words less likely, to be directly fixated in uniform compared to non-uniform sentences. It is argued that saccadic targeting during reading is highly adaptable and flexible towards the characteristics of the text currently being read, as opposed to the idea implemented in most current models of eye movement control during reading that readers develop a preference for making saccades of a certain length across a lifetime of experience with a given language<br/

MODERN STATUS AND DEVELOPMENT TENDENCIES OF NEOLOGISMS IN THE KAZAKH LANGUAGE

Purpose: The research article is devoted to the structure, semantics, and functions of neologisms in the Kazakh language in the years of Independence. The article covers such issues as the process of emergence of new words in Kazakh language in the period of Independence and gives examples of neologisms and ways of their emergence. Methodology: This was analytical-logical research based on content analysis. Result: Neologisms are found in the most diverse areas of human activity and used to some extent in a wide variety of vocabulary. New names cover almost all spheres of human life. The neological “explosion” of the late 20th and early 21st centuries, peculiar to many post-Soviet states, including Kazakhstan, is determined by political, economic, social and cultural changes in society.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Applications: This research can be used for the universities, teachers, and students. Novelty/Originality: In this research, the model of the modern status and development tendencies of neologisms in the kazakh language is presented in a comprehensive and complete manner