Zernike Moment Based Classification of Cosmic Ray Candidate Hits from CMOS Sensors

Reliable tools for artefact rejection and signal classification are a must for cosmic ray detection experiments based on CMOS technology. In this paper, we analyse the fitness of several feature-based statistical classifiers for the classification of particle candidate hits in four categories: spots, tracks, worms and artefacts. We use Zernike moments of the image function as feature carriers and propose a preprocessing and denoising scheme to make the feature extraction more efficient. As opposed to convolution neural network classifiers, the feature-based classifiers allow for establishing a connection between features and geometrical properties of candidate hits. Apart from basic classifiers we also consider their ensemble extensions and find these extensions generally better performing than basic versions, with an average recognition accuracy of 88%.

Islam and Art: An Overview

Modern terms like “religion” and “art” offer limited access to the ways in which nonverbal human creativity in the Islamic world engages the “way of life” indicated by the Arabic word din, often translated as religion. Islam emerged within existing paradigms of creativity and perception in the late antique world. Part of this inheritance was a Platonic and Judaic concern with the potentially misleading power to make images, often misinterpreted in the modern world as an “image prohibition.” Rather, the image function extended beyond replication of visual reality, including direct recognition of the Divine as manifest in the material and cultural world. Music, geometry, writing, poetry, painting, devotional space, gardens and intermedial practices engage people with the “way of life” imbued with awareness of the Divine. Rather than externally representing religious ideas, creativity fosters the subjective capacity to recognize the Divine. Flexible enough to transcend the conventions of time and place over the millennium and a half since the inception of Islam, these modes of engagement persist in forms that also communicate through the expressive practices of contemporary art. To consider religion and art in Islam means to think about how each of these categories perpetually embodies, resists, and recreates the others.

Simulation model of Heat Transfer through the Wall

This paper deals with describing of mathematical model of heat transfer through the wall and simulations, which were obtained by MATLAB Simulink. Model is a part of complex model of heating system. During our model design research we solve partial differential equation system and problem with inverse Laplace transform occurs, because of function of real argument from image function of complex argument is not define.

The Unified Image of the Soviet Woman in Wartime Newspaper Discourse Markers

The purpose of the article is to study the system of lexical markers, characteristic of female image formation in the Soviet media of the Great Patriotic War period. Critical discourse analysis method is applied to investigating the leading Soviet newspapers publications devoted to the role of women in the Great Patriotic War. In total over 300 publications issued during 1941–1943 were selected for analysis according to keywords and thematic relevance. The system of lexical markers, comprising the unified female image creation ways, is defined and analyzed. Ideology domination and militarization are noted to have been essential for unified image formation in the Soviet newspaper discourse of the Great Patriotic War period. The paper reveals the markers that reflect the dynamics of female image transformation: from a rear toiler replacing the man who had left for the front in the first period, to the soldier, the woman capable of taking the place of the fallen fighter in next war period. Classification and description of the markers are presented. The author points out, that the unified image is viewed as the 'image-function' deprived of characteristic female features, traditionally represented in journalistic texts. A conclusion is drawn upon designing the unified 'image-function': it was worked out only pursuing propaganda goals, with the main one – mobilization of women on fight against the enemy threatening the very existence of the state.

Feast In: A Machine Learning Image Recognition Model of Recipe and Lifestyle Applications

With the increase of individuals having an interest in the culinary world, the demand for recipe and lifestyle applications have increased. As we adapt to the changes around us during these trying times, many have also taken an interest in home-cooking. However, it may be challenging, especially for beginners to brainstorm recipes for cooking as they may not be equipped with the proper ingredients to do so. In this paper, we propose Feast In, a platform for web and mobile devices which aims to meet a user’s needs for home-cooking. The platform focuses on three unique features which make Feast In more than just the average recipe platform. Firstly, an improved search algorithm which goes beyond searching for keywords would help users narrow down recipes which they can use in their kitchen. Next, customization features which would create a personalized experience, specifically towards recipes results. This would provide individuals who may face allergies or dietary restrictions an improved experience as they would not have to browse through recipes which do not meet their needs. Lastly, the search-by-image function which utilizes image recognition and machine learning technologies. Users will be able to upload an image of food that they have come across and Feast In will return a list of results which matches the image uploaded. By conducting this research, we were able to propose a unique lifestyle and recipe application which would aid users in searching for the perfect recipe.

Occluded Image Function: A Novel Measure for Evaluating Machine Learning Classifiers for Biometrics

A novel method is presented for evaluating the efficacy of object recognition algorithms on occluded images, called the occluded image function (OIF). The OIF describes system behavior in occluded environments and thus gives qualitative insight into their mechanisms; derivative metrics from OIF can also be used to quantitatively compare classifiers. To showcase the utility of the OIF, an experiment is performed by obstructing optical gait images from two biped robot models and using four binary machine learning classifiers to distinguish between them. The OIF diagrams are created from each experiment, and the resulting insights about the classifiers are discussed. Using the OIF, it is shown that the primitive classifiers can sometimes perform better under occlusion conditions, possibly due to pre-filtering of gait data by uniform occlusions. This result serves to demonstrate that the OIF is a useful tool for classifier evaluation.

The method of automatic identification of motor vehicle users

This paper presents a method of automatic recognition of fingerprint diffraction images of motor vehicle users. The proposed method is based on the basic physical properties of the Fourier transform. It creates the possibility of reducing the problem of recognition to the Fourier transform of the image function, extraction of characteristic features vector and classification of input images.