Processing Pre-Existing Connect-The-Dots Puzzles For Educational Repurposing Applications

Connect-the-Dots puzzles are puzzles which contain labeled dots in a sequence. These puzzles are mostly designed as a way for children to hone in on their counting skills, while having fun. These same puzzles, which are available in abundance online and with modification, can be used to aid students in other areas of education such as spelling. Research shows that the addition of visual imagery provides a significant impact in spelling performance. The objective of this research is to develop an algorithm for processing Connect-the-Dots puzzles to assist in the replacement of the original numbers in the puzzle with characters that will help to facilitate an alternative educational purpose. In particular, the use of Optical Character Recognition (OCR) and image processing algorithms to process pre-existing Connect-the-Dots puzzles is explored. An algorithm was developed to locate and identify the numbers in the puzzles. The system is comprised of five components, namely, an Image Preprocessing component, a Dot Locator component, a Number Locator component, a Number Recognition component, and a Post-Processing component. To test the accuracy of the algorithm an experiment was conducted using 20 hand selected puzzles from an online source. The accuracy of the algorithm was evaluated, component by component, as well as overall, by visually capturing the make-up of the puzzles and comparing them to the results generated by the algorithm. Results show that the algorithm performed at an overall accuracy rate of 66%. However, the Dot Locator component performed at a rate of 100%, the Number Locator at a rate of 86%, and the Number Recognition at a rate of 76%. This research will aid in the development of an application that may provide educational benefits to children who are exposed to using technology for learning, at a young age

Processing Pre-Existing Connect-The-Dots Puzzles For Educational Repurposing Applications

Connect-the-Dots puzzles are puzzles which contain labeled dots in a sequence. These puzzles are mostly designed as a way for children to hone in on their counting skills, while having fun. These same puzzles, which are available in abundance online and with modification, can be used to aid students in other areas of education such as spelling. Research shows that the addition of visual imagery provides a significant impact in spelling performance. The objective of this research is to develop an algorithm for processing Connect-the-Dots puzzles to assist in the replacement of the original numbers in the puzzle with characters that will help to facilitate an alternative educational purpose. In particular, the use of Optical Character Recognition (OCR) and image processing algorithms to process pre-existing Connect-the-Dots puzzles is explored. An algorithm was developed to locate and identify the numbers in the puzzles. The system is comprised of five components, namely, an Image Preprocessing component, a Dot Locator component, a Number Locator component, a Number Recognition component, and a Post Processing component. To test the accuracy of the algorithm an experiment was conducted using 20 hand selected puzzles from an online source. The accuracy of the algorithm was evaluated, component by component, as well as overall, by visually capturing the make-up of the puzzles and comparing them to the results generated by the algorithm. Results show that the algorithm performed at an overall accuracy rate of 66%. However, the Dot Locator component performed at a rate of 100%, the Number Locator at a rate of 86%, and the Number Recognition at a rate of 76%. This research will aid in the development of an application that may provide educational benefits to children who are exposed to using technology for learning, at a young age

An algorithm for two-dimensional density reconstruction in proton computed tomography (PCT)

The purpose of this thesis is to develop an optimized and effective iterative reconstruction algorithm and hardware acceleration methods that work synonymously together through reconstruction in proton computed tomography, which accurately maps the electron density

Оптимизация энергопотребления микроконтроллерных систем

There are two trends in the world of electronics reveal today: an increase of the computing power and minimize of the power consumption. The emergence of devices with high computing power and low power consumption make it possible to use the compact devices with accumulator or battery power instead of bulky devices. The developers used a variety of ways to reduce the energy consumption in order to these devices can work without charge as long as possible while maintaining its compact size. This article discusses the various ways to optimize the energy consumption devices, whose main element is a microcontroller. Reviews the program, architectural and circuit design methods to reduce consumption, consider the advantages and disadvantages, as well as the possibility of using them in combination. Fundamentally new computer architectures are mentioned, which ultimately may prove to be more effective in terms of conventional energy. The brief review of some modern microcontrollers is given finally in terms of low energy consumption.На сегодняшний день в мире электроники прослеживаются две тенденции: увеличение вычислительной мощности и снижение энергопотребления. Появление устройств с большими вычислительными возможностями и низким энергопотреблением дает возможность вместо громоздких устройств применять компактные приборы с аккумуляторным и батарейным питанием. Для того чтобы такие устройства работали без подзарядки как можно дольше и при этом сохраняли свою компактность, разработчики применяют множество способов по снижению энергопотребления. В этой статье рассматриваются различные способы по оптимизации потребления энергии устройствами, основным элементом которых является микроконтроллер. Производится обзор программных, архитектурных и схемотехнических способов снижения потребления, рассмотрены их достоинства и недостатки, а также возможность применения их в комплексе. Упомянуты принципиально новые архитектуры вычислительных систем, которые в перспективе, возможно, окажутся эффективнее традиционных с точки зрения энергосбережения. В завершение дается небольшой обзор некоторых современных микроконтроллеров с точки зрения минимума потребления энергии

Categorization of Learning Analytics Models: Brief Literature Review

Learning analytics is one of the technological tools aiming to investigate educational database collected during the learning delivery process for further purpose of use in decision making or process update. Various types of methods on learning analytics are originated by scholars with their own ambition to contribute the field study. It is emerging study field since 2010s. This paper review literature papers which focused on categorization of learning analytics models with focus of its’ criteria. The papers are chosen from open scholar databases. The selected papers reviewed learning analytics model related studies to bring up their suggested categorization. The category based on the learning analytics models’ main objective as well as used approach. It is observed that prediction of student achievement or success is significant method among learning analytics models

Classification of Repetitive Patterns Using Symmetry Group Prototypes

[EN] We present a novel computational framework for automatic classification method by symmetries, for periodic images applied to content based image retrieval. The existing methods have several drawbacks because of the use of heuristics. These methods have shown low classification values when images exhibit imperfections due to the fabrication or the hand made process. Also, there is no way to give some computation of the classification goodness-of-fit. We propose to obtain an automatic parameter estimation for symmetry analysis. Thus, the image classification is redefined as distances computation to the prototypes of a set of defined classes. Our experimental results improves the state of the art in wallpaper classification methods.This work is supported in part by spanish project VISTAC (DPI2007-66596-C02-01)Agustí-Melchor, M.; Rodas Jordá, Á.; Valiente González, JM. (2011). Classification of Repetitive Patterns Using Symmetry Group Prototypes. Springer-Verlag Berlin Heidelberg. 84-91. http://hdl.handle.net/10251/201675849

HOS Criteria & ICA Algorithms Applied to Radar Detection

International audienc