Databases and Information Systems Commons^™

Development Of A Personal Logbook Android Application, John Byrnes

Economic Crime Forensics Capstones

Development of a mobile app to keep up with animal information.

Lowering Legal Barriers To Rpki Adoption, Christopher S. Yoo, David A. Wishnick

Faculty Scholarship at Penn Law

Across the Internet, mistaken and malicious routing announcements impose significant costs on users and network operators. To make routing announcements more reliable and secure, Internet coordination bodies have encouraged network operators to adopt the Resource Public Key Infrastructure (“RPKI”) framework. Despite this encouragement, RPKI’s adoption rates are low, especially in North America.

This report presents the results of a year-long investigation into the hypothesis—widespread within the network operator community—that legal issues pose barriers to RPKI adoption and are one cause of the disparities between North America and other regions of the world. On the basis of interviews ...

Automated Trading Systems Statistical And Machine Learning Methods And Hardware Implementation: A Survey, Boming Huang, Yuziang Huan, Li Da Xu, Lirong Zheng, Zhuo Zou

Information Technology & Decision Sciences Faculty Publications

Automated trading, which is also known as algorithmic trading, is a method of using a predesigned computer program to submit a large number of trading orders to an exchange. It is substantially a real-time decision-making system which is under the scope of Enterprise Information System (EIS). With the rapid development of telecommunication and computer technology, the mechanisms underlying automated trading systems have become increasingly diversified. Considerable effort has been exerted by both academia and trading firms towards mining potential factors that may generate significantly higher profits. In this paper, we review studies on trading systems built using various methods and ...

Utilization Of Various Methods And A Landsat Ndvi/Google Earth Engine Product For Classifying Irrigated Land Cover, Andrew Nemecek

Graduate Student Theses, Dissertations, & Professional Papers

Methods for classifying irrigated land cover are often complex and not quickly reproducible. Further, moderate resolution time-series datasets have been consistently utilized to produce irrigated land cover products over the past decade, and the body of irrigation classification literature contains no examples of subclassification of irrigated land cover by irrigation method. Creation of geospatial irrigated land cover products with higher resolution datasets could improve reliability, and subclassification of irrigation by method could provide better information for hydrologists and climatologists attempting to model the role of irrigation in the surface-ground water cycle and the water-energy balance. This study summarizes a simple ...

Predicting Post-Procedural Complications Using Neural Networks On Mimic-Iii Data, Namratha Mohan

LSU Master's Theses

The primary focus of this paper is the creation of a Machine Learning based algorithm for the analysis of large health based data sets. Our input was extracted from MIMIC-III, a large Health Record database of more than 40,000 patients. The main question was to predict if a patient will have complications during certain specified procedures performed in the hospital. These events are denoted by the icd9 code 996 in the individuals' health record. The output of our predictive model is a binary variable which outputs the value 1 if the patient is diagnosed with the specific complication or ...

Gradubique: An Academic Transcript Database Using Blockchain Architecture, Thinh Nguyen

Master's Projects

Blockchain has been widely adopted in the last few years even though it is in its infancy. The first well-known application built on blockchain technology was Bitcoin, which is a decentralized and distributed ledger to record crypto-currency transactions. All of the transactions in Bitcoin are anonymously transferred and validated by participants in the network. Bitcoin protocol and its operations are so reliable that technologists have been inspired to enhance blockchain technologies and deploy it outside of the crypto-currency world. The demand for private and non-crypto-currency solutions have surged among consortiums because of the security and fault tolerant features of blockchain ...

Tcp Server And Client: Bookstore Enquiry, Fawaz Bukhowa

Student Scholar Symposium Abstracts and Posters

An application called "Bookstore Enquiry", and it is implemented in Java using TCP client-server program. It contains two programs; one program is called "Server" and another one is called "Client". In this application, the 'server' maintains information about books and for each book it stores information like 'BookId', 'BookName', 'BookEdition', 'AvailableStock', 'UnitPrice', 'Discount'. This application works in such a way that, the server runs indefinitely and waits for client requests. The Client will accept the BookId & BookName from console and send it to server. If the server finds any books that matches with sent details, then it shows "BOOK FOUND ...

Phr: Patient Health Record, Quinn Nelson

Theses/Capstones/Creative Projects

The rapid development of information technology systems has expanded into multiple disciplines and results in systems that are limited by initial design and implementation: the Healthcare Information Technology (HIT) space is no different. The introduction of the Electronic Health Record (EHR) system has changed the way healthcare operates. Initial designs of these systems were focused on serving the needs of insurance companies and healthcare billing departments. Research shows that the design of EHR systems negatively impact provider-patient interactions and the care they receive. This capstone project capitalizes on the collaboration efforts between UNO and UNMC – by joining a research group ...

Using Smart Card Data To Model Commuters’ Response Upon Unexpected Train Delays, Xiancai Tian, Baihua Zheng

Research Collection School Of Information Systems

The mass rapid transit (MRT) network is playingan increasingly important role in Singapore’s transit network,thanks to its advantages of higher capacity and faster speed.Unfortunately, due to aging infrastructure, increasing demand,and other reasons like adverse weather condition, commuters inSingapore recently have been facing increasing unexpected traindelays (UTDs), which has become a source of frustration forboth commuters and operators. Most, if not all, existing workson delay management do not consider commuters’ behavior. Wededicate this paper to the study of commuters’ behavior duringUTDs. We adopt a data-driven approach to analyzing the sixmonth’ real data collected by automated fare collection ...

Eye Pressure Monitior, Andrea Nella Levy

Computer Engineering

The document describes a mobile application that takes information from an attached device which tests eye pressure. The device consists of an IOIO board connected to a custom device that measures the frequency of a given waveform. The device was designed by another student for their senior project, which I am taking over. This device is connected to an IOIO board which is a board designed by a Google employee which works with an android phone in order to create applications that work with embedded systems. The board comes with an API and connects to the phone via a micro-USB ...

Extraction Of Information Related To Adverse Drug Events From Electronic Health Record Notes: Design Of An End-To-End Model Based On Deep Learning, Fei Li, Weisong Liu, Hong Yu

Open Access Articles

BACKGROUND: Pharmacovigilance and drug-safety surveillance are crucial for monitoring adverse drug events (ADEs), but the main ADE-reporting systems such as Food and Drug Administration Adverse Event Reporting System face challenges such as underreporting. Therefore, as complementary surveillance, data on ADEs are extracted from electronic health record (EHR) notes via natural language processing (NLP). As NLP develops, many up-to-date machine-learning techniques are introduced in this field, such as deep learning and multi-task learning (MTL). However, only a few studies have focused on employing such techniques to extract ADEs.

OBJECTIVE: We aimed to design a deep learning model for extracting ADEs and ...

Seasonal Warranty Prediction Based On Recurrent Event Data, Qianqian Shan, Yili Hong, William Q. Meeker Jr.

Statistics Preprints

Warranty return data from repairable systems, such as vehicles, usually result in recurrent event data. The non-homogeneous Poisson process (NHPP) model is used widely to describe such data. Seasonality in the repair frequencies and other variabilities, however, complicate the modeling of recurrent event data. Not much work has been done to address the seasonality, and this paper provides a general approach for the application of NHPP models with dynamic covariates to predict seasonal warranty returns. A hierarchical clustering method is used to stratify the population into groups that are more homogeneous than the than the overall population. The stratification facilitates ...

Performance Indicators Analysis Inside A Call Center Using A Simulation Program, Ditila Ekmekçiu, Markela Muça, Adrian Naço

International Journal of Business and Technology

This paper deals with and shows the results of different performance indicators analyses made utilizing the help of Simulation and concentrated on dimensioning problems of handling calls capacity in a call center. The goal is to measure the reactivity of the call center’s performance to potential changes of critical variables. The literature related to the employment of this kind of instrument in call centers is reviewed, and the method that this problem is treated momentarily is precisely described. The technique used to obtain this paper’s goal implicated a simulation model using Arena Contact Center software that worked as ...

Modelling Business And Management Systems Using Fuzzy Cognitive Maps: A Critical Overview, Peter P. Groumpos

International Journal of Business and Technology

A critical overview of modelling Business and Management (B&M) Systems using Fuzzy Cognitive Maps is presented. A limited but illustrative number of specific applications of Fuzzy Cognitive Maps in diverse B&M systems, such as e business, performance assessment, decision making, human resources management, planning and investment decision making processes is provided and briefly analyzed. The limited survey is given in a table with statics of using FCMs in B&M systems during the last 15 years. The limited survey shows that the applications of Fuzzy Cognitive Maps to today’s Business and Management studies has been steadily increased ...

Heterogeneous Embedding Propagation For Large-Scale E-Commerce User Alignment, Vincent W. Zheng, Mo Sha, Yuchen Li, Hongxia Yang, Zhenjie Zhang, Kian-Lee Tan

Research Collection School Of Information Systems

We study the important problem of user alignment in e-commerce: to predict whether two online user identitiesthat access an e-commerce site from different devices belong toone real-world person. As input, we have a set of user activitylogs from Taobao and some labeled user identity linkages. Useractivity logs can be modeled using a heterogeneous interactiongraph (HIG), and subsequently the user alignment task canbe formulated as a semi-supervised HIG embedding problem.HIG embedding is challenging for two reasons: its heterogeneousnature and the presence of edge features. To address thechallenges, we propose a novel Heterogeneous Embedding Prop-agation (HEP) model. The core idea is ...

River: A Real-Time Influence Monitoring System On Social Media Stream, Mo Sha, Yuchen Li, Yanhao Wang, Wentian Guo, Kian-Lee Tan

Research Collection School Of Information Systems

Social networks generate a massive amount of interaction data among users in the form of streams. To facilitate social network users to consume the continuously generated stream and identify preferred viral social contents, we present a real-time monitoring system called River to track a small set of influential social contents from high-speed streams in this demo. River has four novel features which distinguish itself from existing social monitoring systems: (1) River extracts a set of contents which collectively have the most significant influence coverage while reducing the influence overlaps; (2) River is topic-based and monitors the contents which are relevant ...

Vpsearch: Achieving Verifiability For Privacy-Preserving Multi-Keyword Search Over Encrypted Cloud Data, Zhiguo Wan, Robert H. Deng

Research Collection School Of Information Systems

Although cloud computing offers elastic computation and storage resources, it poses challenges on verifiability of computations and data privacy. In this work we investigate verifiability for privacy-preserving multi-keyword search over outsourced documents. As the cloud server may return incorrect results due to system faults or incentive to reduce computation cost, it is critical to offer verifiability of search results and privacy protection for outsourced data at the same time. To fulfill these requirements, we design aVerifiablePrivacy-preserving keywordSearch scheme, called VPSearch, by integrating an adapted homomorphic MAC technique with a privacy-preserving multi-keyword search scheme. The proposed scheme enables the client to ...

Latent Dirichlet Allocation For Textual Student Feedback Analysis, Swapna Gottipati, Venky Shankararaman, Jeff Rongsheng Lin

Research Collection School Of Information Systems

Education institutions collect feedback from students upon course completionand analyse it to improve curriculum design, delivery methodology and students' learningexperience. A large part of feedback comes in the form textual comments, which pose achallenge in quantifying and deriving insights. In this paper, we present a novel approach ofthe Latent Dirichlet Allocation (LDA) model to address this difficulty in handling textualstudent feedback. The analysis of quantitative part of student feedback provides generalratings and helps to identify aspects of the teaching that are successful and those that canimprove. The reasons for the failure or success, however, can only be deduced by analysingthe ...

Heterogeneous Embedding Propagation For Large-Scale E-Commerce User Alignment, Vincent W. Zheng, Mo Sha, Yuchen Li, Hongxia Yang, Yuan Fang, Zhenjie Zhang, Kian-Lee Tan, Kevin Chen-Chuan Chang

Research Collection School Of Information Systems

We study the important problem of user alignment in e-commerce: to predict whether two online user identitiesthat access an e-commerce site from different devices belong toone real-world person. As input, we have a set of user activitylogs from Taobao and some labeled user identity linkages. Useractivity logs can be modeled using a heterogeneous interactiongraph (HIG), and subsequently the user alignment task canbe formulated as a semi-supervised HIG embedding problem.HIG embedding is challenging for two reasons: its heterogeneousnature and the presence of edge features. To address thechallenges, we propose a novel Heterogeneous Embedding Prop-agation (HEP) model. The core idea is ...

Effective Visualization Approaches For Ultra-High Dimensional Datasets, Gurminder Kaur

LSU Doctoral Dissertations

Multivariate informational data, which are abstract as well as complex, are becoming increasingly common in many areas such as scientific, medical, social, business, and so on. Displaying and analyzing large amounts of multivariate data with more than three variables of different types is quite challenging. Visualization of such multivariate data suffers from a high degree of clutter when the numbers of dimensions/variables and data observations become too large. We propose multiple approaches to effectively visualize large datasets of ultrahigh number of dimensions by generalizing two standard multivariate visualization methods, namely star plot and parallel coordinates plot. We refine three ...