Relationships Between Social Network Characteristics, Alcohol Use, And Alcohol-Related Consequences In A Large Network Of First-Year College Students: How Do Peer Drinking Norms Fit In?,
2018
University of Southern California
Relationships Between Social Network Characteristics, Alcohol Use, And Alcohol-Related Consequences In A Large Network Of First-Year College Students: How Do Peer Drinking Norms Fit In?, Graham T. Diguiseppi, Matthew K. Meisel, Sara G. Balestrieri, Miles Q. Ott, Melissa A. Clark, Nancy P. Barnett
Statistical and Data Sciences: Faculty Publications
A burgeoning area of research is using social network analysis to investigate college students' substance use behaviors. However, little research has incorporated students' perceived peer drinking norms into these analyses. The present study investigated the association between social network characteristics, alcohol use, and alcohol-related consequences among first-year college students (N 1,342; 81% of the first-year class) at one university. The moderating role of descriptive norms was also examined. Network characteristics and descriptive norms were derived from participants' nominations of up to 10 other students who were important to them; individual network characteristics included popularity (indegree), network expansiveness (outdegree), relationship reciprocity, …
Non-Manual Articulators In Irish Sign Language Verbs: An Analysis With Data Mining Association Rules,
2018
Technological University Dublin
Non-Manual Articulators In Irish Sign Language Verbs: An Analysis With Data Mining Association Rules, Robert G. Smith, Markus Hofmann
Conference Papers
The Signs of Ireland (SOI) corpus (Leeson et al., 2006) deploys a complex multi-tiered temporal data structure. The process of manually analyzing such data is laborious, cannot eliminate bias and often, important patterns can go completely unnoticed. In addition to this, as a result of the complex nature of grammatical structures contained in the corpus, identifying complex linguistic associations or patterns across tiers is simply too intricate a task for a human to carry out in an acceptable timeframe. This work explores the application of data mining techniques on a set of multi-tiered temporal data from the SOI corpus. Building …
Strategic Players For Identifying Optimal Social Network Intervention Subjects,
2018
Smith College
Strategic Players For Identifying Optimal Social Network Intervention Subjects, Miles Q. Ott, John M. Light, Melissa A. Clark, Nancy P. Barnett
Statistical and Data Sciences: Faculty Publications
We present a method whereby social network ties are used to identify behavioral leaders who are situated in the network such that these individuals are: 1) able to influence other individuals who are in need of and most receptive to intervention, thereby optimizing the impact of the intervention; and 2) not embedded with ties to individuals that are likely to be behaviorally antagonistic to the intervention or that would compromise the optimal impact of intervention. In this study we developed a method that we call Strategic Players, which is a solution for identifying a set of players who are close …
Potential For Participatory Big Data Ethics And Algorithm Design: A Scoping Mapping Review,
2018
Purdue University
Potential For Participatory Big Data Ethics And Algorithm Design: A Scoping Mapping Review, Madisson Whitman, Chien-Yi Hsiang, Kendall Roark
Libraries Faculty and Staff Scholarship and Research
Ubiquitous networked data collection and algorithm-based information systems have the potential to disparately impact lives around the planet and pose a host of emerging ethical challenges. One response has been a call for more transparency and democratic control over the design and implementation of such systems. This scoping mapping review focuses on participatory approaches to the design, governance, and future of these systems across a wide variety of contexts and domains.
Simplicity And Sustainability: Pointers From Ethics And Science,
2018
Carnegie Mellon University
Simplicity And Sustainability: Pointers From Ethics And Science, Mehrdad Massoudi, Ashwin Vaidya
Department of Mathematics Facuty Scholarship and Creative Works
In this paper, we explore the notion of simplicity. We use definitions of simplicity proposed by philosophers, scientists, and economists. In an age when the rapidly growing human population faces an equally rapidly declining energy/material resources, there is an urgent need to consider various notions of simplicity, collective and individual, which we believe to be a sensible path to restore our planet to a reasonable state of health. Following the logic of mathematicians and physicists, we suggest that simplicity can be related to sustainability. Our efforts must therefore not be spent so much in pursuit of growth but in achieving …
Deep Learning For Multisensor Image Resolution Enhancement,
2018
University of Alabama in Huntsville
Deep Learning For Multisensor Image Resolution Enhancement, Charles B. Collins, John M. Beck, Susan M. Bridges, John A. Rushing
Research Horizons Day Posters
No abstract provided.
Multi-Point Vibration Measurement And Mode Magnification Of Civil Structures Using Video-Based Motion Processing,
2018
University of Nebraska-Lincoln
Multi-Point Vibration Measurement And Mode Magnification Of Civil Structures Using Video-Based Motion Processing, Zhexiong Shang, Zhigang Shen
Department of Construction Engineering and Management: Faculty Publications
Image-based vibration measurement has gained increased attentions in civil and construction communities. A recent video-based motion magnification method was developed to measure and visualize small structure motions. This new approach presents a potential for low-cost vibration measurement and mode shape identification. Pilot studies using this approach on simple rigid body structures were reported. Its validity on complex outdoor structures has not been investigated. In this study, a non-contact video-based approach for multi-point vibration measurement and mode magnification is introduced. The proposed approach can output a full-field vibration map that increases the efficiency of the current structural health monitoring (SHM) practice. …
A Mathematical Analysis Of The Game Of Chess,
2018
Southeastern University - Lakeland
A Mathematical Analysis Of The Game Of Chess, John C. White
Selected Honors Theses
This paper analyzes chess through the lens of mathematics. Chess is a complex yet easy to understand game. Can mathematics be used to perfect a player’s skills? The work of Ernst Zermelo shows that one player should be able to force a win or force a draw. The work of Shannon and Hardy demonstrates the complexities of the game. Combinatorics, probability, and some chess puzzles are used to better understand the game. A computer program is used to test a hypothesis regarding chess strategy. Through the use of this program, we see that it is detrimental to be the first …
Summary Of The Special Issue “Neutrosophic Information Theory And Applications” At “Information” Journal,
2018
University of New Mexico
Summary Of The Special Issue “Neutrosophic Information Theory And Applications” At “Information” Journal, Florentin Smarandache, Jun Ye
Branch Mathematics and Statistics Faculty and Staff Publications
Over a period of seven months (August 2017–February 2018), the Special Issue dedicated to “Neutrosophic Information Theory and Applications” by the “Information” journal (ISSN 2078-2489), located in Basel, Switzerland, was a success. The Guest Editors, Prof. Dr. Florentin Smarandache from the University of New Mexico (USA) and Prof. Dr. Jun Ye from the Shaoxing University (China), were happy to select—helped by a team of neutrosophic reviewers from around the world, and by the “Information” journal editors themselves—and publish twelve important neutrosophic papers, authored by 27 authors and coauthors. There were a variety of neutrosophic topics studied and used by the …
Compression And Relaxation Of Fishing Effort In Response To Changes In Length Of Fishing Season For Red Snapper (Lutjanus Campechanus) In The Northern Gulf Of Mexico,
2018
University of South Alabama
Compression And Relaxation Of Fishing Effort In Response To Changes In Length Of Fishing Season For Red Snapper (Lutjanus Campechanus) In The Northern Gulf Of Mexico, Sean P. Powers, Kevin Anson
University Faculty and Staff Publications
A standard method used by fisheries managers to decrease catch and effort is to shorten the length of a fishery; however, data on recreational angler response to this simple approach are surprisingly lacking. We assessed the effect of variable season length on daily fishing effort, measured by using numbers of boat launches per day, anglers per boat, and anglers per day from video observations, in the recreational sector of the federal fishery for red snapper (Lutjanus campechanus) in coastal Alabama. From 2012 through 2017, season length fluctuated from 3 to 40 d. Daily effort, measured by using mean number of …
Non-Linear Machine Learning With Active Sampling For Mox Drift Compensation,
2018
Technological University Dublin
Non-Linear Machine Learning With Active Sampling For Mox Drift Compensation, Tamara Matthews, Muhammad Iqbal, Horacio Gonzalez-Velez
Conference papers
Abstract—Metal oxide (MOX) gas detectors based on SnO2 provide low-cost solutions for real-time sensing of complex gas mixtures for indoor ambient monitoring. With high sensitivity under ideal conditions, MOX detectors may have poor longterm response accuracy due to environmental factors (humidity and temperature) along with sensor aging, leading to calibration drifts. Finding a simple and efficient solution to correct such calibration drifts has been the subject of numerous studies but remains an open problem. In this work, we present an efficient approach to MOX calibration using active and transfer sampling techniques coupled with non-linear machine learning algorithms, namely neural networks, …
Estimating Exploitation Rates In The Alabama Red Snapper Fishery Using A High-Reward Tag–Recapture Approach,
2018
Auburn University
Estimating Exploitation Rates In The Alabama Red Snapper Fishery Using A High-Reward Tag–Recapture Approach, Dana K. Sackett, Mattgew Catalano, J. Marcus Drymon, Sean P. Powers, Mark Albins
University Faculty and Staff Publications
Accurate estimates of exploitation are essential to managing an exploited fishery. However, these estimates are often dependent on the area and vulnerable sizes of fish considered in a study. High-reward tagging studies offer a simple and direct approach to estimating exploitation rates at these various scales and in examining how model parameters impact exploitation rate estimates. These methods can ultimately provide a better understanding of the spatial dynamics of exploitation at smaller local and regional scales within a fishery—a measure often needed for more site-attached species, such as the Red Snapper Lutjanus campechanus. We used this approach to tag 724 …
Penerapan Data Mining Menggunakan Perbandingan Algoritma Greedy Dengan Algoritma Genetika Pada Prediksi Rentet Waktu Harga Crude Palm Oil,
2017
Universitas Islam MAB Banjarmasin, Indonesia
Penerapan Data Mining Menggunakan Perbandingan Algoritma Greedy Dengan Algoritma Genetika Pada Prediksi Rentet Waktu Harga Crude Palm Oil, Desy Ika Puspitasari
Elinvo (Electronics, Informatics, and Vocational Education)
Penelitian ini menerapkan data mining pada prediksi harga CPO (Crude Palm Oil) dengan membandingkan pemodelan optimasi seleksi fitur algoritma genetika dan algoritma greedy pada metode neural network (NN). Prediksi harga CPO dilakukan untuk memenuhi kebutuhan investor kelapa sawit, melalui analisa masalah fluktuasi harga CPO time series yang tidak pasti. Guna mempermudah dalam melakukan perhitungan, langkah-langkah dari algoritma Genetika dan algoritma Greedy diimplementasikan dengan program komputer Rapid Miner Studio. Adapun tujuan penelitian ini yaitu mengetahui perbandingan akurasi dengan parameter evaluasi RMSE yang dihasilkan dan waktu eksekusi program yang dibutuhkan oleh algoritma Genetika dan algoritma Greedy dalam menyelesaikan masalah prediksi harga CPO. …
Pembagian Tingkat Kecanduan Game Online Menggunakan K-Means Clustering Serta Korelasinya Terhadap Prestasi Akademik,
2017
Universitas Negeri Yogyakarta
Pembagian Tingkat Kecanduan Game Online Menggunakan K-Means Clustering Serta Korelasinya Terhadap Prestasi Akademik, Yudi Prastyo
Elinvo (Electronics, Informatics, and Vocational Education)
Game online tidak hanya memberikan hiburan tetapi juga memberikan tantangan yang menarik untuk diselesaikan sehingga individu bermain game online tanpa memperhitungkan waktu demi mencapai kepuasan. Salah satu metode yang dapat digunakan untuk mengelompokkan tingkat kecanduan game online adalah metode K-Means Clustering. K-Means Clustering merupakan salah satu metode data clustering non hirarki yang berusaha mempartisi data yang ada ke dalam bentuk satu atau lebih cluster/kelompok.Penelitian ini mengambil data sample kuesioner dari mahasiswa di Universitas Ibn Khaldun Bogor dimana isian kuesioner akan diolah sebagai acuan pengelompokkan tingkat kecanduan game online.Hasil clusteringdigunakan untuk mengetahui hubungannya antara tingkat kecanduan game …
Analisis Data Time Series Dan Vcr Kepadatan Lalu Lintas (Studi Kasus: Jalan Adisucipto Depan Ambarukmo Plaza),
2017
Universitas Gadjah Mada, Indonesia
Analisis Data Time Series Dan Vcr Kepadatan Lalu Lintas (Studi Kasus: Jalan Adisucipto Depan Ambarukmo Plaza), Arief Rachma Wibowo
Elinvo (Electronics, Informatics, and Vocational Education)
Kepadatan lalu lintas atau biasa dikenal dengan istilah kemacetan merupakan kondisi dimana terjadinya penumpukan kendaraan disuatu ruas jalan tertentu, hal ini bisa saja disebabkan oleh beberapa faktor, antara lain jumlah kendaraan yang berada dalam ruas jalan tersebut. Sumber data dari riset ini langsung diperoleh dari Dinas Perhubungan DIY. Analisis data time series digunakan untuk meramalkan jumlah kendaraan pada siang hari dan analisis VCR disini untuk klasifikasi kondisi jalan tersebut. Berdasarkan analisis data time series menggunakan metode trend, data jumlah motor yang melalui Jalan Adisucipto pada pukul 12.30-14.40 cenderung mengalami penurunan. Berdasarkan analisis VCR, jumlah kendaraan mencapai puncaknya pada pukul 15.30-17.00 …
Interactive Visual Analytics Application For Spatiotemporal Movement Data Vast Challenge 2017 Mini-Challenge 1: Award For Actionable And Detailed Analysis,
2017
Singapore Management University
Interactive Visual Analytics Application For Spatiotemporal Movement Data Vast Challenge 2017 Mini-Challenge 1: Award For Actionable And Detailed Analysis, Yifei Guan, Tin Seong Kam
Research Collection School Of Computing and Information Systems
The Visual Analytics Science and Technology (VAST) Challenge 2017 Mini-Challenge 1 dataset mirrored the challenging scenarios in analysing large spatiotemporal movement tracking datasets. The datasets provided contains a 13-month movement data generated by five types of sensors, for six types of vehicles passing through the Boonsong Lekagul Nature Preserve. We present an application developed with the market leading visualisation software Tableau to provide an interactive visual analysis of the multi-dimensional spatiotemporal datasets. Our interactive application allows the user to perform an interactive analysis to observe movement patterns, study vehicle trajectories and identify movement anomalies while allowing them to customise the …
Ancr—An Adaptive Network Coding Routing Scheme For Wsns With Different-Success-Rate Links †,
2017
Northwest University
Ancr—An Adaptive Network Coding Routing Scheme For Wsns With Different-Success-Rate Links †, Xiang Ji, Anwen Wang, Chunyu Li, Chun Ma, Yao Peng, Dajin Wang, Qingyi Hua, Feng Chen, Dingyi Fang
Department of Computer Science Faculty Scholarship and Creative Works
As the underlying infrastructure of the Internet of Things (IoT), wireless sensor networks (WSNs) have been widely used in many applications. Network coding is a technique in WSNs to combine multiple channels of data in one transmission, wherever possible, to save node’s energy as well as increase the network throughput. So far most works on network coding are based on two assumptions to determine coding opportunities: (1) All the links in the network have the same transmission success rate; (2) Each link is bidirectional, and has the same transmission success rate on both ways. However, these assumptions may not be …
Supervised Classification Using Finite Mixture Copula,
2017
Austin Peay State University
Supervised Classification Using Finite Mixture Copula, Sumen Sen, Norou Diawara
Mathematics & Statistics Faculty Publications
Use of copula for statistical classification is recent and gaining popularity. For example, statistical classification using copula has been proposed for automatic character recognition, medical diagnostic and most recently in data mining. Classical discrimination rules assume normality. But in this data age time, this assumption is often questionable. In fact features of data could be a mixture of discrete and continues random variables. In this paper, mixture copula densities are used to model class conditional distributions. Such types of densities are useful when the marginal densities of the vector of features are not normally distributed and are of a mixed …
Content Analysis Of Data Science Graduate Programs In The U.S.,
2017
Shenyang City University
Content Analysis Of Data Science Graduate Programs In The U.S., Duo Li, Elizabeth Milonas, Qiping Zhang
Publications and Research
Data science is an emerging academic field (Paul & Aithal, 2018), which has its origins in “Big Data/Cloud Computing” and complexity science domains. Data Science is about managing large and complex data (Big Data management) and analytics technologies (Paul & Aithal, 2018). Data, technology, and people are the three pillars of data science. In addition, Data Science is composed of three key areas: analytics, infrastructure, and data curation (Tang & Sae-Lim, 2016). Stanton (2012) defined data science as “an emerging area of work concerned with the collection, preparation, analysis, visualization, management, and preservation of large collections of information (Song & …
Constructing Interactive Visual Classification, Clustering And Dimension Reduction Models For N-D Data,
2017
Central Washington University
Constructing Interactive Visual Classification, Clustering And Dimension Reduction Models For N-D Data, Boris Kovalerchuk, Dmytro Dovhalets
Computer Science Faculty Scholarship
The exploration of multidimensional datasets of all possible sizes and dimensions is a long-standing challenge in knowledge discovery, machine learning, and visualization. While multiple efficient visualization methods for n-D data analysis exist, the loss of information, occlusion, and clutter continue to be a challenge. This paper proposes and explores a new interactive method for visual discovery of n-D relations for supervised learning. The method includes automatic, interactive, and combined algorithms for discovering linear relations, dimension reduction, and generalization for non-linear relations. This method is a special category of reversible General Line Coordinates (GLC). It produces graphs in 2-D that represent …
