Automatic attendance capturing using histogram of oriented gradients on facial images

Abstract: Humans mostly use faces to identify/recognise individuals and the recent improvement in the capability of computing now allow recognition and detection automatically. However, there still exist quite a number of problems in the automatic recognition of facial images. Histogram of Oriented Gradients (HOG) has been recently adopted and seen as a standard for efficient face recognition and object detection generally. In this paper, we investigate and discuss a simple but effective approach to capturing student’s attendance register in a lecture hall by making use of HOG features for detecting and recognising students face at different moods, orientations, and illuminations. Our experiment detection and recognition output show a good performance on our facial image database obtained from the University of Johannesburg, this performance is due to HOG descriptors attributes which are robust to changes in rotation and illuminations. Our system will help to save instructional staff/lecturer time by eliminating manual calling of students name and also help monitor students

A Corpus-driven Approach toward Teaching Vocabulary and Reading to English Language Learners in U.S.-based K-12 Context through a Mobile App

In order to decrease teachers’ decisions of which vocabulary the focus of the instruction should be upon, a recent line of research argues that pedagogically-prepared word lists may offer the most efficient order of learning vocabulary with an optimized context for instruction in each of four K-12 content areas (math, science, social studies, and language arts) through providing English Language Learners (ELLs) with the most frequent words in each area. Educators and school experts have acknowledged the need for developing new materials, including computerized enhanced texts and effective strategies aimed at improving ELLs’ mastery of academic and STEM-related lexicon. Not all words in a language are equal in their role in comprehending the language and expressing ideas or thoughts. For this study, I used a corpus-driven approach which is operationalized by applying a text analysis method. For the purpose of this research study, I made two corpora, Teacher’s U.S. Corpus (TUSC) and Science and Math Academic Corpus for Kids (SMACK) with a focus on word lemma rather than inflectional and derivational variants of word families. To create the corpora, I collected and analyzed a total of 122 textbooks used commonly in the states of Florida and California. Recruiting, scanning and converting of textbooks had been carried out over a period of more than two years from October 2014 to March 2017. In total, this school corpus contains 10,519,639 running words and 16,344 lemmas saved in 16,315 word document pages. From the corpora, I developed six word lists, namely three frequency-based word lists (high-, mid-, and low-frequency), academic and STEM-related word lists, and essential word list (EWL). I then applied the word lists as the database and developed a mobile app, Vocabulary in Reading Study – VIRS, (available on App Store, Android and Google Play) alongside a website (www.myvirs.com). Also, I developed a new K-12 dictionary which targets the vocabulary needs of ELLs in K-12 context. This is a frequency-based dictionary which categorizes words into three groups of high, medium and low frequency words as well as two separate sections for academic and STEM words. The dictionary has 16,500 lemmas with derivational and inflectional forms

Shortest Route at Dynamic Location with Node Combination-Dijkstra Algorithm

Abstract— Online transportation has become a basic requirement of the general public in support of all activities to go to work, school or vacation to the sights. Public transportation services compete to provide the best service so that consumers feel comfortable using the services offered, so that all activities are noticed, one of them is the search for the shortest route in picking the buyer or delivering to the destination. Node Combination method can minimize memory usage and this methode is more optimal when compared to A* and Ant Colony in the shortest route search like Dijkstra algorithm, but can’t store the history node that has been passed. Therefore, using node combination algorithm is very good in searching the shortest distance is not the shortest route. This paper is structured to modify the node combination algorithm to solve the problem of finding the shortest route at the dynamic location obtained from the transport fleet by displaying the nodes that have the shortest distance and will be implemented in the geographic information system in the form of map to facilitate the use of the system. Keywords— Shortest Path, Algorithm Dijkstra, Node Combination, Dynamic Location (key words

2019 GREAT Day Program

SUNY Geneseo’s Thirteenth Annual GREAT Day.https://knightscholar.geneseo.edu/program-2007/1013/thumbnail.jp

On the Detection and Characterization of Exomoons Through Survey and Targeted Observations

Exomoons remain amongst the most elusive targets in observational astronomy. Nevertheless, these worlds stand to provide an unprecedented window into the formation and evolution of planetary systems. If the Solar System is any guide, we can expect exomoons will be geologically active and diverse, with the potential for hosting volatiles, atmospheres, and even life. Moreover, a thorough understanding of the population and occurrence rates of exomoons will help to place our own Solar System in a galactic context, speaking to the commonality of our own history. And though there are a variety of known pathways for moon formation, the discovery of exomoons may yet reveal heretofore unanticipated system architectures and defy easy explanation, thereby enriching our theoretical understanding of system formation. In this Dissertation I present a population study of exomoons in the Kepler data, finding an apparent dearth of Galilean-analog satellites orbiting planets between 0.1 and 1 AU. I then present evidence for a large exomoon orbiting Kepler-1625b -- potentially the first ever discovery of a transiting exomoon -- as suggested by a joint analysis of Kepler and Hubble Space Telescope data. The following chapter further investigates a number of alternative hypotheses relating to the candidate moon, though the conclusion that an exomoon best explains the data in hand remains unchanged. Finally, I present the results of an effort to identify candidate exomoon signals in the Kepler data by developing a convolutional neural network trained on O(10⁵) Kepler light curves injected with simulated planet and moon transit signals. The most promising exomoon candidates identified by the neural network are examined in detail, undergoing a full photodynamical model fit and Bayesian model selection. I conclude by discussing the outlook for the moon search, highlighting strategies for future work and myriad unanswered questions that should be pursued in the coming years

Applied Metaheuristic Computing

For decades, Applied Metaheuristic Computing (AMC) has been a prevailing optimization technique for tackling perplexing engineering and business problems, such as scheduling, routing, ordering, bin packing, assignment, facility layout planning, among others. This is partly because the classic exact methods are constrained with prior assumptions, and partly due to the heuristics being problem-dependent and lacking generalization. AMC, on the contrary, guides the course of low-level heuristics to search beyond the local optimality, which impairs the capability of traditional computation methods. This topic series has collected quality papers proposing cutting-edge methodology and innovative applications which drive the advances of AMC

Social Sciences and Cultural Studies

This is a unique and groundbreaking collection of questions and answers coming from higher education institutions on diverse fields and across a wide spectrum of countries and cultures. It creates routes for further innovation, collaboration amidst the Sciences (both Natural and Social) and the Humanities and the private and the public sectors of society. The chapters speak across socio-cultural concerns, education, welfare and artistic sectors under the common desire for direct responses in more effective ways by means of interaction across societal structures