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Fine-Grained Geolocation Of Tweets In Temporal Proximity, Wen Haw CHONG, Ee-peng LIM 2019 Singapore Management University

Fine-Grained Geolocation Of Tweets In Temporal Proximity, Wen Haw Chong, Ee-Peng Lim

Research Collection School Of Information Systems

In fine-grained tweet geolocation, tweets are linked to the specific venues (e.g., restaurants, shops) fromwhich they were posted. This explicitly recovers the venue context that is essential for applications such aslocation-based advertising or user profiling. For this geolocation task, we focus on geolocating tweets that arecontained in tweet sequences. In a tweet sequence, tweets are posted from some latent venue(s) by the sameuser and within a short time interval. This scenario arises from two observations: (1) It is quite common thatusers post multiple tweets in a short time and (2) most tweets are not geocoded. To more accurately ...


Analogies And Comparisons For Stm Data Bodies, Phillip M. Cunio, Brien Flewelling 2019 ExoAnalytic Solutions, Inc.

Analogies And Comparisons For Stm Data Bodies, Phillip M. Cunio, Brien Flewelling

Space Traffic Management Conference

Space Traffic Management (STM) has already demonstrated its potential to be extremely data-intensive. The large number of objects on orbit today, if observed constantly throughout their lifetimes, could produce a staggeringly large number of observations that might in turn generate large numbers of orbits. Orbit data with a lengthy time history can be used to produce estimates of maneuver frequency, susceptibility to natural forces such as drag, and (if combined with photometric data) assessments of behavioral patterns of life.

A future of mega-constellations and a growing number of nations and organizations with assets on orbit would make it likely that ...


Chip-Off Success Rate Analysis Comparing Temperature And Chip Type, Choli Ence, Joan Runs Through, Gary D. Cantrell 2019 St George Police Department

Chip-Off Success Rate Analysis Comparing Temperature And Chip Type, Choli Ence, Joan Runs Through, Gary D. Cantrell

Journal of Digital Forensics, Security and Law

Throughout the digital forensic community, chip-off analysis provides examiners with a technique to obtain a physical acquisition from locked or damaged digital device. Thermal based chip-analysis relies upon the application of heat to remove the flash memory chip from the circuit board. Occasionally, a flash memory chip fails to successfully read despite following similar protocols as other flash memory chips. Previous research found the application of high temperatures increased the number of bit errors present in the flash memory chip. The purpose of this study is to analyze data collected from chip-off analyses to determine if a statistical difference exists ...


Adaptive Cost-Sensitive Online Classification, Peilin ZHAO, Yifan ZHANG, Min WU, Steven C. H. HOI, Mingkui TAN, Junzhou HUANG 2019 Singapore Management University

Adaptive Cost-Sensitive Online Classification, Peilin Zhao, Yifan Zhang, Min Wu, Steven C. H. Hoi, Mingkui Tan, Junzhou Huang

Research Collection School Of Information Systems

Cost-Sensitive Online Classification has drawn extensive attention in recent years, where the main approach is to directly online optimize two well-known cost-sensitive metrics: (i) weighted sum of sensitivity and specificity; (ii) weighted misclassification cost. However, previous existing methods only considered first-order information of data stream. It is insufficient in practice, since many recent studies have proved that incorporating second-order information enhances the prediction performance of classification models. Thus, we propose a family of cost-sensitive online classification algorithms with adaptive regularization in this paper. We theoretically analyze the proposed algorithms and empirically validate their effectiveness and properties in extensive experiments. Then ...


Two-Stage Bagging Pruning For Reducing The Ensemble Size And Improving The Classification Performance, Hua Zhang, Yujie Song, Bo Jiang, Bi Chen, Guogen Shan 2019 Zhejiang Gongshang University

Two-Stage Bagging Pruning For Reducing The Ensemble Size And Improving The Classification Performance, Hua Zhang, Yujie Song, Bo Jiang, Bi Chen, Guogen Shan

Environmental & Occupational Health Faculty Publications

Ensemble methods, such as the traditional bagging algorithm, can usually improve the performance of a single classifier. However, they usually require large storage space as well as relatively time-consuming predictions. Many approaches were developed to reduce the ensemble size and improve the classification performance by pruning the traditional bagging algorithms. In this article, we proposed a two-stage strategy to prune the traditional bagging algorithm by combining two simple approaches: accuracy-based pruning (AP) and distance-based pruning (DP). These two methods, as well as their two combinations, “AP+DP” and “DP+AP” as the two-stage pruning strategy, were all examined. Comparing with ...


Improving Vix Futures Forecasts Using Machine Learning Methods, James Hosker, Slobodan Djurdjevic, Hieu Nguyen, Robert Slater 2019 Southern Methodist University

Improving Vix Futures Forecasts Using Machine Learning Methods, James Hosker, Slobodan Djurdjevic, Hieu Nguyen, Robert Slater

SMU Data Science Review

The problem of forecasting market volatility is a difficult task for most fund managers. Volatility forecasts are used for risk management, alpha (risk) trading, and the reduction of trading friction. Improving the forecasts of future market volatility assists fund managers in adding or reducing risk in their portfolios as well as in increasing hedges to protect their portfolios in anticipation of a market sell-off event. Our analysis compares three existing financial models that forecast future market volatility using the Chicago Board Options Exchange Volatility Index (VIX) to six machine/deep learning supervised regression methods. This analysis determines which models provide ...


A Systematic Review Of Process Modelling Methods And Its Application For Personalised Adaptive Learning Systems, Kingsley Okoye 2019 University of East London

A Systematic Review Of Process Modelling Methods And Its Application For Personalised Adaptive Learning Systems, Kingsley Okoye

Journal of International Technology and Information Management

This systematic review work investigates current literature and methods that are related to the application of process mining and modelling in real-time particularly as it concerns personalisation of learning systems, or yet still, e-content development. The work compares available studies based on the domain area of study, the scope of the study, methods used, and the scientific contribution of the papers and results. Consequently, the findings of the identified papers were systematically evaluated in order to point out potential confounding variables or flaws that might have been overlooked or missing in the current literature. In turn, a critical structured analysis ...


Toward The Personalization Of Copyright Law, Adi Libson, Gideon Parchomovsky 2019 Bar-Ilan University, Israel

Toward The Personalization Of Copyright Law, Adi Libson, Gideon Parchomovsky

Faculty Scholarship at Penn Law

In this Article, we provide a blueprint for personalizing copyright law in order to reduce the deadweight loss that stems from its universal application to all users, including those who would not have paid for it. We demonstrate how big data can help identify inframarginal users, who would not pay for copyrighted content, and we explain how copyright liability and remedies should be modified in such cases.


Exploring Critical Success Factors For Data Integration And Decision-Making In Law Enforcement, Marquay Edmondson, Walter R. McCollum, Mary-Margaret Chantre, Gregory Campbell 2019 Capitol Technology University

Exploring Critical Success Factors For Data Integration And Decision-Making In Law Enforcement, Marquay Edmondson, Walter R. Mccollum, Mary-Margaret Chantre, Gregory Campbell

International Journal of Applied Management and Technology

Agencies from various disciplines supporting law enforcement functions and processes have integrated, shared, and communicated data through ad hoc methods to address crime, terrorism, and many other threats in the United States. Data integration in law enforcement plays a critical role in the technical, business, and intelligence processes created by users to combine data from various sources and domains to transform them into valuable information. The purpose of this qualitative phenomenological study was to explore the current conditions of data integration frameworks through user and system interactions among law enforcement organizational processes. Further exploration of critical success factors used to ...


Behind Emammal’S Success: A Data Curator With A Data Standard, Jennifer Y. Zhao, William J. McShea 2018 Smithsonian Institution

Behind Emammal’S Success: A Data Curator With A Data Standard, Jennifer Y. Zhao, William J. Mcshea

Journal of eScience Librarianship

This paper explores the data challenges of a major collection method in the field of ecology: using infrared-activated cameras to detect wildlife. One such solution, eMammal, is now available to address these struggles. We delineate the key reason behind its success: a data curator who manages an established data standard and communicates with eMammal’s users and stakeholders. We outline the tasks of this data curator, mention how they can work with data librarians, and demonstrate that the data curator position is already applicable in several biological science fields with a few examples. We end by emphasizing the growth of ...


Secured Data Masking Framework And Technique For Preserving Privacy In A Business Intelligence Analytics Platform, Osama Ali 2018 The University of Western Ontario

Secured Data Masking Framework And Technique For Preserving Privacy In A Business Intelligence Analytics Platform, Osama Ali

Electronic Thesis and Dissertation Repository

The main concept behind business intelligence (BI) is how to use integrated data across different business systems within an enterprise to make strategic decisions. It is difficult to map internal and external BI’s users to subsets of the enterprise’s data warehouse (DW), resulting that protecting the privacy of this data while maintaining its utility is a challenging task. Today, such DW systems constitute one of the most serious privacy breach threats that an enterprise might face when many internal users of different security levels have access to BI components. This thesis proposes a data masking framework (iMaskU: Identify ...


Crude Oil Prices Forecasting: Time Series Vs. Svr Models, Xin James He 2018 Fairfield University

Crude Oil Prices Forecasting: Time Series Vs. Svr Models, Xin James He

Journal of International Technology and Information Management

This research explores the weekly crude oil price data from U.S. Energy Information Administration over the time period 2009 - 2017 to test the forecasting accuracy by comparing time series models such as simple exponential smoothing (SES), moving average (MA), and autoregressive integrated moving average (ARIMA) against machine learning support vector regression (SVR) models. The main purpose of this research is to determine which model provides the best forecasting results for crude oil prices in light of the importance of crude oil price forecasting and its implications to the economy. While SVR is often considered the best forecasting model in ...


The Relationship Between Organizational Resources And Green It/S Adoption: A Rbv Approach, Lutfus Sayeed, Alberto Onetti 2018 San Francisco State University

The Relationship Between Organizational Resources And Green It/S Adoption: A Rbv Approach, Lutfus Sayeed, Alberto Onetti

Journal of International Technology and Information Management

ABSTRACT

The objective of the present study was to empirically explore the impact of the implementation of Green IT/S measures on organizational resources in the US and European firms. The study examined the influence of reconfiguration of resources within a firm while adopting various Green IT/S practices and technologies. Green IT/S implementation requires resource commitment from organizations (Bose and Luo, 2011). What are these resources and how do they affect the extent of Green IT/S measures adopted by businesses? Resource Based View (RBV) of the firm was used as the theoretical framework of the study. The ...


Table Of Contents Jitim Vol 27 Issue 3, 2018, 2018 California State University, San Bernardino

Table Of Contents Jitim Vol 27 Issue 3, 2018

Journal of International Technology and Information Management

Table of Contents


Mobility-Driven Ble Transmit-Power Adaptation For Participatory Data Muling, Chung-Kyun HAN, Archan MISRA, Shih-Fen CHENG 2018 Singapore Management University

Mobility-Driven Ble Transmit-Power Adaptation For Participatory Data Muling, Chung-Kyun Han, Archan Misra, Shih-Fen Cheng

Research Collection School Of Information Systems

This paper analyzes a human-centric framework, called SmartABLE, for easy retrieval of the sensor values from pervasively deployed smart objects in a campus-like environment. In this framework, smartphones carried by campus occupants act as data mules, opportunistically retrieving data from nearby BLE (Bluetooth Low Energy) equipped smart object sensors and relaying them to a backend repository. We focus specifically on dynamically varying the transmission power of the deployed BLE beacons, so as to extend their operational lifetime without sacrificing the frequency of sensor data retrieval. We propose a memetic algorithm-based power adaptation strategy that can handle deployments of thousands of ...


Mobility-Driven Ble Transmit-Power Adaptation For Participatory Data Muling, Chung-Kyun HAN, Archan MISRA, Shih-Fen CHENG 2018 Singapore Management University

Mobility-Driven Ble Transmit-Power Adaptation For Participatory Data Muling, Chung-Kyun Han, Archan Misra, Shih-Fen Cheng

Research Collection School Of Information Systems

This paper analyzes a human-centric framework, called SmartABLE, for easy retrieval of the sensor values from pervasively deployed smart objects in a campus-like environment. In this framework, smartphones carried by campus occupants act as data mules, opportunistically retrieving data from nearby BLE (Bluetooth Low Energy) equipped smart object sensors and relaying them to a backend repository. We focus specifically on dynamically varying the transmission power of the deployed BLE beacons, so as to extend their operational lifetime without sacrificing the frequency of sensor data retrieval. We propose a memetic algorithm-based power adaptation strategy that can handle deployments of thousands of ...


Organize Events Mobile Application, Thakshak Mani Chandra Reddy Gudimetla 2018 California State University, San Bernardino

Organize Events Mobile Application, Thakshak Mani Chandra Reddy Gudimetla

Electronic Theses, Projects, and Dissertations

In a big organization there are many events organized every day. To know about the events, we typically need to check an events page, rely on flyers or on distributed pamphlets or through word of mouth. To register for an event a user now a days typically does this online which involves inputting user details. At the event, the user either signs a sheet of paper or enters credentials in a web page loaded on a tablet or other electronic device. Typically, this is a time-consuming process with many redundancies like entering user details every time the user wants to ...


Seasonal Warranty Prediction Based On Recurrent Event Data, Qianqian Shan, Yili Hong, William Q. Meeker Jr. 2018 Iowa State University

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 ...


Transcribing Braille Code: Learning Equations Across Platforms, Deegan Atha, Courtney Balogh 2018 Purdue University

Transcribing Braille Code: Learning Equations Across Platforms, Deegan Atha, Courtney Balogh

Purdue Journal of Service-Learning and International Engagement

Deegan Atha, a graduating senior in electrical engineering and a future engineer, is interested in human-centered design and developing technology that helps students engage and be successful in STEM.

Courtney Balogh, a junior in mechanical engineering, is interested in human-centered design and the importance it plays in product development. Deegan and Courtney are members of the Purdue EPICS project, Learning Equations Across Platforms (LEAP). They partnered with the Indiana School for the Blind and Visually Impaired (ISBVI) to develop a braille transcription device and web application that converts braille to print in real time.


Web-Based Archaeology And Collaborative Research, Fabrizio Galeazzi, Heather Richards-Rissetto 2018 University of York

Web-Based Archaeology And Collaborative Research, Fabrizio Galeazzi, Heather Richards-Rissetto

Anthropology Faculty Publications

While digital technologies have been part of archaeology for more than fifty years, archaeologists still look for more efficient methodologies to integrate digital practices of fieldwork recording with data management, analysis, and ultimately interpretation.This Special Issue of the Journal of Field Archaeology gathers international scholars affiliated with universities, organizations, and commercial enterprises working in the field of Digital Archaeology. Our goal is to offer a discussion to the international academic community and practitioners. While the approach is interdisciplinary, our primary audience remains readers interested in web technology and collaborative platforms in archaeology


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