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1,793 full-text articles. Page 54 of 83.

Automating Data Analysis For Two-Dimensional Gas Chromatography/Time-Of-Flight Mass Spectrometry Non-Targeted Analysis Of Comparative Samples, Ivan A. Titaley, O. Maduka Ogba, Leah Chibwe, Eunha Hoh, Paul H.-Y. Cheong, Staci L. Massey Simonich 2018 Oregon State University

Automating Data Analysis For Two-Dimensional Gas Chromatography/Time-Of-Flight Mass Spectrometry Non-Targeted Analysis Of Comparative Samples, Ivan A. Titaley, O. Maduka Ogba, Leah Chibwe, Eunha Hoh, Paul H.-Y. Cheong, Staci L. Massey Simonich

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Non-targeted analysis of environmental samples, using comprehensive two‐dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC × GC/ToF-MS), poses significant data analysis challenges due to the large number of possible analytes. Non-targeted data analysis of complex mixtures is prone to human bias and is laborious, particularly for comparative environmental samples such as contaminated soil pre- and post-bioremediation. To address this research bottleneck, we developed OCTpy, a Python™ script that acts as a data reduction filter to automate GC × GC/ToF-MS data analysis from LECO® ChromaTOF® software and facilitates selection of analytes of interest based on peak area …


Internet Of Underground Things: Sensing And Communications On The Field For Precision Agriculture, Mehmet C. Vuran, Abdul Salam, Rigoberto Wong, Suat Irmak 2018 University of Nebraska-Lincoln

Internet Of Underground Things: Sensing And Communications On The Field For Precision Agriculture, Mehmet C. Vuran, Abdul Salam, Rigoberto Wong, Suat Irmak

School of Computing: Conference and Workshop Papers

The projected increases in World population and need for food have recently motivated adoption of information technology solutions in crop fields within precision agriculture approaches. Internet of underground things (IOUT), which consists of sensors and communication devices, partly or completely buried underground for real-time soil sensing and monitoring, emerge from this need. This new paradigm facilitates seamless integration of underground sensors, machinery, and irrigation systems with the complex social network of growers, agronomists, crop consultants, and advisors. In this paper, state-of-the-art communication architectures are reviewed, and underlying sensing technology and communication mechanisms for IOUT are presented. Recent advances in the …


Relating Justification Logic Modality And Type Theory In Curry–Howard Fashion, Konstantinos Pouliasis 2018 CUNY Graduate Center

Relating Justification Logic Modality And Type Theory In Curry–Howard Fashion, Konstantinos Pouliasis

Dissertations, Theses, and Capstone Projects

This dissertation is a work in the intersection of Justification Logic and Curry--Howard Isomorphism. Justification logic is an umbrella of modal logics of knowledge with explicit evidence. Justification logics have been used to tackle traditional problems in proof theory (in relation to Godel's provability) and philosophy (Gettier examples, Russel's barn paradox). The Curry--Howard Isomorphism or proofs-as-programs is an understanding of logic that places logical studies in conjunction with type theory and -- in current developments -- category theory. The point being that understanding a system as a logic, a typed calculus and, a language of a class of categories constitutes …


Lecture Capture / Flipping / Clickers, Darrell Lutey 2018 University of Nevada, Las Vegas

Lecture Capture / Flipping / Clickers, Darrell Lutey

UNLV Best Teaching Practices Expo

Student Success – UNLV needs to improve retention


Natural Language, Mixed-Initiative Personal Assistant Agents, Joshua W. Buck, Saverio Perugini, Tam W. Nguyen 2018 University of Dayton

Natural Language, Mixed-Initiative Personal Assistant Agents, Joshua W. Buck, Saverio Perugini, Tam W. Nguyen

Computer Science Faculty Publications

The increasing popularity and use of personal voice assistant technologies, such as Siri and Google Now, is driving and expanding progress toward the long-term and lofty goal of using artificial intelligence to build human-computer dialog systems capable of understanding natural language. While dialog-based systems such as Siri support utterances communicated through natural language, they are limited in the flexibility they afford to the user in interacting with the system and, thus, support primarily action-requesting and information-seeking tasks. Mixed-initiative interaction, on the other hand, is a flexible interaction technique where the user and the system act as equal participants in an …


Chrono: A System For Normalizing Temporal Expressions, Amy L. Olex, Luke G. Maffey, Nicholas Morton, Bridget T. McInnes 2018 Virginia Commonwealth University

Chrono: A System For Normalizing Temporal Expressions, Amy L. Olex, Luke G. Maffey, Nicholas Morton, Bridget T. Mcinnes

Computer Science Publications

The Chrono System: Chrono is a hybrid rule-based and machine learning system written in Python and built from the ground up to identify temporal expressions in text and normalizes them into the SCATE schema. Input text is preprocessed using Python’s NLTK package, and is run through each of the four primary modules highlighted here. Note that Chrono does not remove stopwords because they add temporal information and context, and Chrono does not tokenize sentences. Output is an Anafora XML file with annotated SCATE entities. After minor parsing logic adjustments, Chrono has emerged as the top performing system for SemEval 2018 …


Support Vector Machines For Image Spam Analysis, Aneri Chavda, Katerina Potika, Fabio Di Troia, Mark Stamp 2018 San Jose State University

Support Vector Machines For Image Spam Analysis, Aneri Chavda, Katerina Potika, Fabio Di Troia, Mark Stamp

Faculty Publications, Computer Science

Email is one of the most common forms of digital communication. Spam is unsolicited bulk email, while image spam consists of spam text embedded inside an image. Image spam is used as a means to evade text-based spam filters, and hence image spam poses a threat to email-based communication. In this research, we analyze image spam detection using support vector machines (SVMs), which we train on a wide variety of image features. We use a linear SVM to quantify the relative importance of the features under consideration. We also develop and analyze a realistic “challenge” dataset that illustrates the limitations …


Expression Of The Microrna-143/145 Cluster Is Decreased In Hepatitis B Virus-Associated Hepatocellular Carcinoma And May Serve As A Biomarker For Tumorigenesis In Patients With Chronic Hepatitis B, Qi Zhao, Xiangfei Sun, Chao Liu, Tao Li, Juan Cui, Chengyong Qin 2018 Shandong University

Expression Of The Microrna-143/145 Cluster Is Decreased In Hepatitis B Virus-Associated Hepatocellular Carcinoma And May Serve As A Biomarker For Tumorigenesis In Patients With Chronic Hepatitis B, Qi Zhao, Xiangfei Sun, Chao Liu, Tao Li, Juan Cui, Chengyong Qin

School of Computing: Faculty Publications

The aims of the present study were to identify the expression profile of microRNA (miR)‑143/145 in hepatitis B virus (HBV)‑associated hepatocellular carcinoma (HCC), explore its association with prognosis and investigate whether the serum miR‑143/145 expression levels may serve as a diagnostic indicator of HBV‑associated HCC. The microRNA (miRNA) chromatin immunoprecipitation dataset was obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus databases, and analyzed using the Wilcoxon signed‑rank test. It was observed that the expression of miR‑143 and miR‑145 was decreased 1.5‑fold in HBV‑associated HCC samples compared with non‑tumor tissue in the TCGA and the GSE22058 datasets …


Deep Learning-Based Framework For Autism Functional Mri Image Classification, Xin Yang, Saman Sarraf, Ning Zhang 2018 Southern Arkansas University

Deep Learning-Based Framework For Autism Functional Mri Image Classification, Xin Yang, Saman Sarraf, Ning Zhang

Journal of the Arkansas Academy of Science

The purpose of this paper is to introduce deep learning-based framework LeNet-5 architecture and implement the experiments for functional MRI image classification of Autism spectrum disorder. We implement our experiments under the NVIDIA deep learning GPU Training Systems (DIGITS). By using the Convolutional Neural Network (CNN) LeNet-5 architecture, we successfully classified functional MRI image of Autism spectrum disorder from normal controls. The results show that we obtained satisfactory results for both sensitivity and specificity.


Travel To Extraterrestrial Bodies Over Time: Some Exploratory Analyses Of Mission Data, Venkat Kodali, Rohith Kumar Reddy Duggirala, Richard S. Segall, Hyacinthe Aboudja, Daniel Berleant 2018 Universiy of Arkansas at Little Rock

Travel To Extraterrestrial Bodies Over Time: Some Exploratory Analyses Of Mission Data, Venkat Kodali, Rohith Kumar Reddy Duggirala, Richard S. Segall, Hyacinthe Aboudja, Daniel Berleant

Journal of the Arkansas Academy of Science

This paper discusses data pertaining to space missions to astronomical bodies beyond earth. The analyses provide summarizing facts and graphs obtained by mining data about (1) missions launched by all countries that go to the moon and planets, and (2) Earth satellites obtained from a Union of Concerned Scientists (UCS) dataset and lists of publically available satellite data.


Programming: Predicting Student Success Early In Cs1. A Re-Validation And Replication Study, Keith Quille, Susan Bergin 2018 Technological University Dublin

Programming: Predicting Student Success Early In Cs1. A Re-Validation And Replication Study, Keith Quille, Susan Bergin

Articles

This paper describes a large, multi-institutional revalidation study conducted in the academic year 2015-16. Six hundred and ninetytwo students participated in this study, from 11 institutions (ten institutions in Ireland and one in Denmark). The primary goal was to validate and further develop an existing computational prediction model called Predict Student Success (PreSS). In doing so, this study addressed a call from the 2015 ITiCSE working group (the second "Grand Challenge"), to "systematically analyse and verify previous studies using data from multiple contexts to tease out tacit factors that contribute to previously observed outcomes". PreSS was developed and validated in …


Glyph Based Segmentation Of Chinese Calligraphy Characters In The "Collected Characters" Stele., David A. McInnis 2018 Eastern Washington University

Glyph Based Segmentation Of Chinese Calligraphy Characters In The "Collected Characters" Stele., David A. Mcinnis

EWU Masters Thesis Collection

Text character segmentation is the process of detecting the bounding box position of individual characters within a written text document image. The character segmentation problem remains extremely difficult for ancient Chinese calligraphy documents. This paper examines a glyph-based segmentation technique for segmenting Chinese Calligraphy characters in the "Collected Characters". The glyph-based character segmentation pipeline utilizes a combination of well-understood image processing techniques in a novel pipeline which is able to detect Chinese calligraphy characters from ink-blots with a good reliability.


A Practical And Efficient Algorithm For The K-Mismatch Shortest Unique Substring Finding Problem, Daniel Robert Allen 2018 Eastern Washington University

A Practical And Efficient Algorithm For The K-Mismatch Shortest Unique Substring Finding Problem, Daniel Robert Allen

EWU Masters Thesis Collection

This thesis revisits the k-mismatch shortest unique substring (SUS) finding problem and demonstrates that a technique recently presented in the context of solving the k-mismatch average common substring problem can be adapted and combined with parts of the existing solution, resulting in a new algorithm which has expected time complexity of O(n logk n), while maintaining a practical space complexity at O(kn), where n is the string length. When k > 0, which is the hard case, the new proposal significantly improves the any-case O(n2) time complexity of the prior best method for k-mismatch SUS finding. Experimental study …


Old English Character Recognition Using Neural Networks, Sattajit Sutradhar 2018 Georgia Southern University

Old English Character Recognition Using Neural Networks, Sattajit Sutradhar

College of Graduate Studies: Theses & Dissertations

Character recognition has been capturing the interest of researchers since the beginning of the twentieth century. While the Optical Character Recognition for printed material is very robust and widespread nowadays, the recognition of handwritten materials lags behind. In our digital era more and more historical, handwritten documents are digitized and made available to the general public. However, these digital copies of handwritten materials lack the automatic content recognition feature of their printed materials counterparts. We are proposing a practical, accurate, and computationally efficient method for Old English character recognition from manuscript images. Our method relies on a modern machine learning …


Scenario Development For Unmanned Aircraft System Simulation-Based Immersive Experiential Learning, Nickolas D. Macchiarella, Alexander J. Mirot 2018 Embry-Riddle Aeronautical University

Scenario Development For Unmanned Aircraft System Simulation-Based Immersive Experiential Learning, Nickolas D. Macchiarella, Alexander J. Mirot

Journal of Aviation/Aerospace Education & Research

Application of scenario-based training can serve as practical means of educating remote pilots and sensor operators as they seek professional levels of knowledge. Both education and training can build upon time-tested training and simulation methodologies that apply simulators in settings that mirror real-world operations. Embry-Riddle Aeronautical University’s unmanned aircraft system (UAS) program curriculum is rooted in immersive simulation that offers students an experiential learning experience that is aimed to develop higher-order thinking skills. Skills that are critical to professional levels of performance. The degree program builds from basic application skills to critical thinking skills by using immersive scenario-based training in …


Comparing The Usage Of React Native And Ionic, Sam Borick 2018 The University of Akron

Comparing The Usage Of React Native And Ionic, Sam Borick

Williams Honors College, Honors Research Projects

This project will compare two popular programming frameworks for building mobile applications. These frameworks are called ‘cross-platform frameworks’ as they can develop applications on multiple platforms. The scope of this project is to understand the structural reasons for the differences in these frameworks. While this project does speculate on reasons for choosing either framework, this project does not attempt to make a hard recommendation.

In this project, I built two applications, as similar as possible, in React Native and Ionic. I found that there were differences in the goals of these frameworks, lending each of the two better to different …


Grocery List: An Android Application, Daniel McFadden 2018 The University of Akron

Grocery List: An Android Application, Daniel Mcfadden

Williams Honors College, Honors Research Projects

Grocery List is an android application that allows the user to save a grocery list to their device for reference at a store as opposed to the traditional pen and paper. Grocery List was created in Android developer, and uses Java and XML to run the application and display different layouts.

Grocery Lists' main purpose is to be an easy to use, flexible listing application that can serve multiple different listing uses such as grocery lists, to do tasks, and even just some simple reminders.


Computational Analysis Of Composite Fiber Diameter, Cailin Simpson 2018 University of Alabama in Huntsville

Computational Analysis Of Composite Fiber Diameter, Cailin Simpson

Summer Community of Scholars Posters (RCEU and HCR Combined Programs)

No abstract provided.


A Systematic Approach To Rna-Associated Motif Discovery, Tian Gao, Jiang Shu, Juan Cui 2018 University of Nebraska-Lincoln

A Systematic Approach To Rna-Associated Motif Discovery, Tian Gao, Jiang Shu, Juan Cui

School of Computing: Faculty Publications

Background: Sequencing-based large screening of RNA-protein and RNA-RNA interactions has enabled the mechanistic study of post-transcriptional RNA processing and sorting, including exosome-mediated RNA secretion. The downstream analysis of RNA binding sites has encouraged the investigation of novel sequence motifs, which resulted in exceptional new challenges for identifying motifs from very short sequences (e.g., small non-coding RNAs or truncated messenger RNAs), where conventional methods tend to be ineffective. To address these challenges, we propose a novel motif-finding method and validate it on a wide range of RNA applications.

Results: We first perform motif analysis on microRNAs and longer RNA fragments from …


A Comparison Of Information Technology Mediated Customer Services Between The U.S. And China, Suhong Li, Hal Records, Robert Behling 2018 Bryant University

A Comparison Of Information Technology Mediated Customer Services Between The U.S. And China, Suhong Li, Hal Records, Robert Behling

Information Systems and Analytics Department Faculty Journal Articles

Information technology mediated customer service is a reality of the 21st century. More and more companies have moved their customer services from in store and in person to online through computer or mobile devices. Using 442 responses collected from one USA university (234 responses) and two Chinese universities (208 responses), the study investigates customer preferences over two service delivery models (either in store or online) on five types of purchasing (retail, eating-out, banking, travel and entertainment) and their perception difference in customer service quality between those two delivery models in the U.S. and China. The results show that the majority …


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