Social and Behavioral Sciences Commons^™

Modeling Airport Catchment Areas: Using Spatial Analysis Approach, Sitong Chen

The Journal of Purdue Undergraduate Research

Th e airport catchment area is the geographic area from which an airport can reasonably expect to draw commercial air service passengers. Th e purpose of this interdisciplinary research is to estimate airport catchment areas using a spatial analysis method for informed airport management. In order to ensure the comprehensiveness and reliability of the research, we chose to analyze the catchment areas for five airports of different sizes and in different geographic locations in the United States. The Huff model, which is usually used in marketing, economics, and retail research, was adopted in this study. We applied this model in …

Data-Driven Operational And Safety Analysis Of Emerging Shared Electric Scooter Systems, Qingyu Ma

Computational Modeling & Simulation Engineering Theses & Dissertations

The rapid rise of shared electric scooter (E-Scooter) systems offers many urban areas a new micro-mobility solution. The portable and flexible characteristics have made E-Scooters a competitive mode for short-distance trips. Compared to other modes such as bikes, E-Scooters allow riders to freely ride on different facilities such as streets, sidewalks, and bike lanes. However, sharing lanes with vehicles and other users tends to cause safety issues for riding E-Scooters. Conventional methods are often not applicable for analyzing such safety issues because well-archived historical crash records are not commonly available for emerging E-Scooters.

Perceiving the growth of such a micro-mobility …

Bibliometric Analysis Of Emerging Technologies In The Field Of Computer Science Helping In Ovarian Cancer Research, Sonali Kothari Dr., Anvita Gupta, Muskaan Agrawal Agrawal, Kajal Jaggi, Adhiraj Dev Goswami, Ketan Kotecha, M. Karthikeyan Dr., Vijayshri Khedkar

Library Philosophy and Practice (e-journal)

This study is carried out to provide an analysis of the literature available at the intersection of ovarian cancer and computing. A comprehensive search was conducted using Scopus database for English-language peer-reviewed articles. The study administers chronological, domain clustering and text analysis of the articles under consideration to provide high-level concept map composed of specific words and the connections between them.

A Review Paper: Analysis Of Weka Data Mining Techniques For Heart Disease Prediction System, Basma Jumaa Saleh, Ahmed Yousif Falih Saedi, Ali Talib Qasim Al-Aqbi, Lamees Abdalhasan Salman

Library Philosophy and Practice (e-journal)

Data mining is characterized as searching for useful information through very large data sets. Some of the key and most common techniques for data mining are association rules, classification, clustering, prediction, and sequential models. For a wide range of applications, data mining techniques are used. Data mining plays a significant role in disease detection in the health care industry. The patient should be needed to detect a number of tests for the disease. However, the number of tests should be reduced by using data mining techniques. In time and performance, this reduced test plays an important role. Heart disease is …

Indonesian Library User Behaviour During Covid 19 Pandemic On Digital Library Platform, Irhamni

English Language Institute

COVID-19 pandemic has significantly changed library user behavior, workplaces, and some public areas including in the library. During the COVID 19 pandemics, the digital library with a mobile app like ipusnas has facilitated to accessing library resources. The ipusnas has increased people's accessibility to library materials. This research focuses on the use of the digital library has a significant impact on library users behavior; it can influence how they read, access the library, and their interaction with the library resources.

Bibliometric Study Of Bibliometric Papers About Clustering, Preeti Mulay, Rahul Raghvendra Joshi, Archana Chaudhari

Library Philosophy and Practice (e-journal)

Bibliometric survey or bibliometric review papers generally analyses the work done previously by eminent personalities, authors, countries and various institutions which was published in giant databases like Scopus, Web of Science, Google Scholar, Research Gate and others. Bibliometric papers provide amalgamation of wide range of research papers from journals, conferences, reviews and other papers, which are working papers, papers with results, proposals and few of them are survey papers etc. Bibliometric papers are One-Stop-Solution for the readers and upcoming researchers to get acquainted entirely about the specific topic / domain. Bibliometric papers also help in smartly locating research-gaps for the …

Exploring The Relationship Between Online Discourse And Commitment In Twitter Professional Learning Communities, Wanli Xing, Fei Gao

Visual Communications and Technology Education Faculty Publications

Educators show great interest in participating in social-media communities, such as Twitter, to support their professional development and learning. The majority of the research into Twitter-based professional learning communities has investigated why educators choose to use Twitter for professional development and learning and what they actually do in these communities. However, few studies have examined why certain community members remain committed and others gradually drop out. To fill this gap in the research, this study investigated how some key features of online discourse influenced the continued participation of the members of a Twitter-based professional learning community. More than 600,000 tweets …

Data-Driven Optimization Models For Feeder Bus Network Design, Yaojun Wang

Theses and Dissertations

Urbanization is not a modern phenomenon. However, it is worthwhile to note that the world urban population growth curve has up till recently followed a quadratic-hyperbolic pattern (Korotayey and Khaltourina, 2006). As cities become larger and their population expand, large and growing metropolises have to face the enormous traffic demand. To alleviate the increasing traffic congestion, public transit has been considered as the ideal solution to such troubles and problems restricting urban development. The metro is a type of efficient, dependable and high-capacity public transport adapted in metropolises worldwide. At the same time, the residents from crowded cities migrated to …

Prediction And Recommendations On The It Leaners' Learning Path As A Collective Intelligence Using A Data Mining Technique, Seong-Yong Hong, Juyun Cho, Yonghyun Hwang

Journal of International Technology and Information Management

With the recent advances in computer technology along with pervasive internet accesses, data analytics is getting more attention than ever before. In addition, research areas on data analysis are diverging and integrating lots of different fields such as a business and social sector. Especially, recent researches focus on the data analysis for a better intelligent decision making and prediction system. This paper analyzes data collected from current IT learners who have already studied various IT subjects to find the IT learners’ learning patterns. The most popular learning patterns are identified through an association rule data mining using an arules package …

Evaluation Of Classification And Ensemble Algorithms For Bank Customer Marketing Response Prediction, Olatunji Apampa

Journal of International Technology and Information Management

This article attempts to improve the performance of classification algorithms used in the bank customer marketing response prediction of an unnamed Portuguese bank using the Random Forest ensemble. A thorough exploratory data analysis (EDA) was conducted on the data in order to ascertain the presence of anomalies such as outliers and extreme values. The EDA revealed that the bank data had 45, 211 instances and 17 features, with 11.7% positive responses. This was in addition to the detection of outliers and extreme values. Classification algorithms used for modelling the bank dataset include; Logistic Regression, Decision Tree, Naïve Bayes and the …

A Comparative Study: Utilizing Data Mining Techniques To Classify Traffic Congestion Status, Abbas Mirakhorli

UNLV Theses, Dissertations, Professional Papers, and Capstones

Performance measure is a process of evaluating and quantifying a system. Performance measure provides us with information about how good a system is working and how well the predefined goals are met. In order to analyze the performance of a transportation system, the traffic data such as speed, volume, occupancy and travel time of the system need to be collected. These data will generate valuable historical database that can be used to develop models to improve the quality of service of transportation system. The performance measures in transportation studies can be categorized to following main groups: Congestion, Mobility, Accessibility, Reliability, …

Hot Zone Identification: Analyzing Effects Of Data Sampling On Spam Clustering, Rasib Khan, Mainul Mizan, Ragib Hasan, Alan Sprague

Journal of Digital Forensics, Security and Law

Email is the most common and comparatively the most efficient means of exchanging information in today's world. However, given the widespread use of emails in all sectors, they have been the target of spammers since the beginning. Filtering spam emails has now led to critical actions such as forensic activities based on mining spam email. The data mine for spam emails at the University of Alabama at Birmingham is considered to be one of the most prominent resources for mining and identifying spam sources. It is a widely researched repository used by researchers from different global organizations. The usual process …

Educational Data Mining: An Advance For Intelligent Systems In Education, Ryan Baker

Ryan S.J.d. Baker

Computer-based technologies have transformed the way we live, work, socialize, play, and learn. Today, the use of data collected through these technologies is supporting a second-round of transformation in all of these areas. Over the last decades, the methods of data mining and analytics have transformed field after field. Scientific fields such as physics, biology, and climate science have leveraged these methods to manage and make discoveries in previously unimaginably large datasets. The first journal devoted to data mining and analytics methods in biology, Computers in Biology and Medicine, began publication as long ago as the 1970s. In the mid-1990s …

Data Mining The Harness Track And Predicting Outcomes, Robert P. Schumaker

Journal of International Technology and Information Management

This paper presented the S&C Racing system that uses Support Vector Regression (SVR) to predict harness race finishes and analyzed it on fifteen months of data from Northfield Park. We found that our system outperforms the most common betting strategies of wagering on the favorites and the mathematical arbitrage Dr. Z system in five of the seven wager types tested. This work would suggest that an informational inequality exists within the harness racing market that is not apparent to domain experts.

Using Textual Features To Predict Popular Content On Digg, Paul H. Miller

Paul H Miller

Over the past few years, collaborative rating sites, such as Netflix, Digg and Stumble, have become increasingly prevalent sites for users to find trending content. I used various data mining techniques to study Digg, a social news site, to examine the influence of content on popularity. What influence does content have on popularity, and what influence does content have on users’ decisions? Overwhelmingly, prior studies have consistently shown that predicting popularity based on content is difficult and maybe even inherently impossible. The same submission can have multiple outcomes and content neither determines popularity, nor individual user decisions. My results show …

Using Textual Features To Predict Popular Content On Digg, Paul H. Miller

Department of English: Dissertations, Theses, and Student Research

Over the past few years, collaborative rating sites, such as Netflix, Digg and Stumble, have become increasingly prevalent sites for users to find trending content. I used various data mining techniques to study Digg, a social news site, to examine the influence of content on popularity. What influence does content have on popularity, and what influence does content have on users’ decisions? Overwhelmingly, prior studies have consistently shown that predicting popularity based on content is difficult and maybe even inherently impossible. The same submission can have multiple outcomes and content neither determines popularity, nor individual user decisions. My results show …

Infoextractor – A Tool For Social Media Data Mining, Chirag Shah, Charles File

JITP 2011: The Future of Computational Social Science

We present InfoExtractor, a web-based tool for collecting data and metadata from focused social media content. InfoExtractor then provides this data in various structured and unstructured formats for easy manipulation and analysis. The tool allows social science researchers to easily collect data for quantitative analysis, and is designed to deliver data from popular and influential social media sites in a useful and easy to access way. InfoExtractor was designed to replace traditional means of content aggregation, such as page scraping and brute- force copying.