Decision Support System Determination Of Main Work Unitin Wpp-711 Using Fuzzy Topsis,
2018
Universitas Islam Madura, Indonesia
Decision Support System Determination Of Main Work Unitin Wpp-711 Using Fuzzy Topsis, Hozairi Hozairi, Yaser Krisnafi
Knowledge Engineering and Data Science
Decision-making to determine the working units for being prioritized to be developed in order to improve fishery monitoring in WPP-711 is imperative. The Ministry of Maritime Affairs and Fisheries should make no mismatch decision-making through long-term calculation and analysis. The problem of determining the priority of working units is a complex problem, thus it is required to find an appropriate method to avoid a mismatch decision. Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is a decision-making method capable of solving multi-criteria problems. TOPSIS working principle determines the alternative by considering the shortest distance from the positive …
Capital Letter Pattern Recognition In Text To Speechby Way Of Perceptron Algorithm,
2018
AMIK Multi Data Palembang, Indonesia
Capital Letter Pattern Recognition In Text To Speechby Way Of Perceptron Algorithm, Novan Wijaya
Knowledge Engineering and Data Science
Computer vision is a data transformation retrieved or generated from webcam into another form in means of determining decision. All kinds of transformations are carried through to attain specific aims. One of the supporting techniques in implementing computer vision on a system is digital image processing as the objective of digital image processing is to transform digital-formatted picture so that it can be processed in computer. Computer vision and digital image processing can be implemented in a system of capital letter introduction and real-time handwriting reading on a whiteboard supported by artificial neural network mode “perceptron algorithm” used as a …
Market Basket Analysis To Identify Customer Behaviorsby Way Of Transaction Data,
2018
Maulana Malik Ibrahim State Islamic University, Indonesia
Market Basket Analysis To Identify Customer Behaviorsby Way Of Transaction Data, Fachrul Kurniawan, Binti Umayah, Jihad Hammad, Supeno Mardi Susiki Nugroho, Mochammad Hariadi
Knowledge Engineering and Data Science
Transaction data is a set of recording data result in connections with sales-purchase activities at a particular company. In these recent years, transaction data have been prevalently used as research objects in means of discovering new information. One of the possible attempts is to design an application that can be used to analyze the existing transaction data. That application has the quality of market basket analysis. In addition, the application is designed to be desktop-based whose components are able to process as well as re-log the existing transaction data. The used method in designing this application is by way of …
Earth Satellite Data Analysis,
2018
University of Arkansas Little Rock
Earth Satellite Data Analysis, Venkat Kodali
Theses and Dissertations
The number of satellites has been steadily increasing since the first satellite launched to orbit in 1957. Satellites are launched for various purpose and users of the satellites are now spread across the world. The dependency on satellites has increased greatly over time and they now have a major impact on everyday life. The project I will discuss is focused on data analysis of earth satellites. The datasets used for analysis are from several sources, the data was cleaned and used to find some meaningful insights. The objective is develop data visualization charts and modeling techniques using R, identify trends …
Photovoltaic System Optimization For An Austere Location Using Time Series Data,
2018
Air Force Institute of Technology
Photovoltaic System Optimization For An Austere Location Using Time Series Data, Torrey J. Wagner, Eric Lang, Warren Assink, Douglas S. Dudis
Faculty Publications
In this work we test experimental photovoltaic, storage and generator technologies and investigate their potential to meet austere location energy needs. After defining the energy requirements and insolation of a 1,100-person base, we develop a microgrid model and simulation. Cost optimizations were then performed using hourly time-series data to explore the cost and performance trade-space of a PV-battery-generator system. The work highlights the cost of resiliency and the dependencies of optimum system component sizes on duration and the fully burdened cost of fuel.
An Algorithm For Calculating Top-Dimensional Bounding Chains,
2018
Royal Institute of Technology
An Algorithm For Calculating Top-Dimensional Bounding Chains, J. Frederico Carvalho, Mikael Vejdemo-Johansson, Danica Kragic, Florian T. Pokorny
Publications and Research
We describe the Coefficient-Flow algorithm for calculating the bounding chain of an (n-1)-boundary on an n-manifold-like simplicial complex S. We prove its correctness and show that it has a computational time complexity of O(|S(n−1)|) (where S(n−1) is the set of (n-1)-faces of S). We estimate the big-O coefficient which depends on the dimension of S and the implementation. We present an implementation, experimentally evaluate the complexity of our algorithm, and compare its performance with that of solving the underlying linear system.
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 …
3rd Analytics Without Borders Conference Program,
2018
Bryant University
3rd Analytics Without Borders Conference Program, Bentley University
Analytics Without Borders
No abstract provided.
Exploring The Potential Of Data Physicalization For Stem Learning,
2018
Human-Data Interaction Group, Cork Institute of Technology Cork, Ireland
Exploring The Potential Of Data Physicalization For Stem Learning, Sarah Hayes
Conference Papers
This paper presents an overview of the research that I have conducted as part of my PhD studies. The aim of this research is to explore the potential of data physicalization to enhance and improve STEM learning. Specifically, this research is focused on exploring the ways in which physical data representations can be used to clarify dense scientific, technological, engineering or mathematical concepts, and support novel interactions to increase user engagement and learning. My aim is to achieve this through the design, deployment and evaluation of a series of data physicalizations representing STEM concepts and data sets.
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 …
Mapping Opioid Mortality Rates Across Treatment Capacity To Identify Need And Access,
2018
VCU School of Medicine
Mapping Opioid Mortality Rates Across Treatment Capacity To Identify Need And Access, Garrett K. Wong, Justin R. Chang, Chase Greco, Yadunandan Pillai, Mohammad A. Shahrezaei, Melissa H. Burton, Rob Lawrence, Alan Dow
Graduate Research Posters
Background: The opioid and heroin overdose epidemic is a public health emergency in the state of Virginia, resulting in the death of more than 1,100 people in 2016. In order to overcome this epidemic, we need to match the places with the greatest need for services related to substance use disorders with the appropriate healthcare workforce.
Aims: As the data about the overdose outbreak and related socioeconomic factors grow in size and complexity, data scientists have attempted to utilize big data techniques to identify communities and risk factors contributing to addiction.
Methods: Using data obtained from the …
Visualizing The Opioid Overdose With A Dynamic Heat Map To Identify And Predict Vulnerable Communities,
2018
VCU School of Medicine
Visualizing The Opioid Overdose With A Dynamic Heat Map To Identify And Predict Vulnerable Communities, Justin R. Chang, Garrett K. Wong, Chase Greco, Yadunandan Pillai, Mohammad A. Shahrezaei, Melissa H. Burton, Rob Lawrence, Alan Dow
Graduate Research Posters
Background: Opioid and heroin overdose epidemic is a public health emergency in the state of Virginia. In order to prevent overdose deaths, we need the target expertise in substance use disorders to areas with high rates of overdose. In particular, an area with an acute spike in overdoses might represent an urgent need for intervention.
Aims: The CDC urges the use of near real-time surveillance to effectively identify overdose incidence, and to coordinate community responses in the states affected by the epidemic, including Virginia. However, current opioid overdose datasets for Virginia lack adequate consistency, granularity, and temporality for …
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 …
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, …
Privacy In Iot Cloud,
2018
City University of New York
Privacy In Iot Cloud, Aftab Ahmad, Ravi Mukkamala, Karthik Navuluri
Computer Science Faculty Publications
We present a framework for privacy preservation in an information cloud of IoT devices. We contend that privacy provisioning should be located in the user device and must protect the user, the information, and the device from breaches in privacy. We elaborate on how the layered privacy model can ensure such privacy provisioning, and justify the device being the provisioning point instead of the cloud alone. We present the point of view that, due to resource limitations of the IoT devices in general, the privacy preserving measures need to be hard-coded in the device technology. We fall short of suggesting …
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 …
A Frame-Based Nlp System For Cancer-Related Information Extraction,
2018
University of Texas Health Science Center at Houston, School of Health Information Sciences, Houston TX, USA
A Frame-Based Nlp System For Cancer-Related Information Extraction, Yuqi Si, Kirk Roberts
Faculty, Staff and Student Publications
We propose a frame-based natural language processing (NLP) method that extracts cancer-related information from clinical narratives. We focus on three frames: cancer diagnosis, cancer therapeutic procedure, and tumor description. We utilize a deep learning-based approach, bidirectional Long Short-term Memory (LSTM) Conditional Random Field (CRF), which uses both character and word embeddings. The system consists of two constituent sequence classifiers: a frame identification (lexical unit) classifier and a frame element classifier. The classifier achieves an F
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 …
