Field Study In Deploying Restless Multi-Armed Bandits: Assisting Non-Profits In Improving Maternal And Child Health,
2022
Google Research Harvard University
Field Study In Deploying Restless Multi-Armed Bandits: Assisting Non-Profits In Improving Maternal And Child Health, Aditya Mate, Lovish Madan, Aparna Taneja, Neha Madhiwalla, Shresth Verma, Gargi Singh, Aparna Hegde, Pradeep Varakantham, Milind Tambe
Research Collection School Of Computing and Information Systems
The widespread availability of cell phones has enabled non-profits to deliver critical health information to their beneficiaries in a timely manner. This paper describes our work to assist non-profits that employ automated messaging programs to deliver timely preventive care information to beneficiaries (new and expecting mothers) during pregnancy and after delivery. Unfortunately, a key challenge in such information delivery programs is that a significant fraction of beneficiaries drop out of the program. Yet, non-profits often have limited health-worker resources (time) to place crucial service calls for live interaction with beneficiaries to prevent such engagement drops. To assist non-profits in optimizing …
New-Media Advertising And Retail Platform Openness,
2022
Singapore Management University
New-Media Advertising And Retail Platform Openness, Jianqing Chen, Zhiling Guo
Research Collection School Of Computing and Information Systems
We recently have witnessed two important trends in online retailing: the advent of new media (e.g., social media and search engines) makes advertising affordable for small sellers, and large online retailers (e.g., Amazon and JD.com) opening their platforms to allow even direct competitors to sell on their platforms. We examine how new-media advertising affects retail platform openness. We develop a game-theoretic model in which a leading retailer, who has both valuation and awareness advantages, and a third-party seller, who sells an identical product, engage in price competition. We find that the availability of relatively low-cost advertising through new media plays …
Collaborative Curating For Discovery And Expansion Of Visual Clusters,
2022
Singapore Management University
Collaborative Curating For Discovery And Expansion Of Visual Clusters, Duy Dung Le, Hady W. Lauw
Research Collection School Of Computing and Information Systems
In many visually-oriented applications, users can select and group images that they find interesting into coherent clusters. For instance, we encounter these in the form of hashtags on Instagram, galleries on Flickr, or boards on Pinterest. The selection and coherence of such user-curated visual clusters arise from a user’s preference for a certain type of content as well as her own perception of which images are similar and thus belong to a cluster. We seek to model such curation behaviors towards supporting users in their future activities such as expanding existing clusters or discovering new clusters altogether. This paper proposes …
Understanding In-App Advertising Issues Based On Large Scale App Review Analysis,
2022
Harbin Institute of Technology
Understanding In-App Advertising Issues Based On Large Scale App Review Analysis, Cuiyun Gao, Jichuan Zeng, David Lo, Xin Xia, Irwin King, Michael R. Lyu
Research Collection School Of Computing and Information Systems
Context: In-app advertising closely relates to app revenue. Reckless ad integration could adversely impact app quality and user experience, leading to loss of income. It is very challenging to balance the ad revenue and user experience for app developers. Objective: Towards tackling the challenge, we conduct a study on analyzing user concerns about in-app advertisement. Method: Specifically, we present a large-scale analysis on ad-related user feedback. The large user feedback data from App Store and Google Play allow us to summarize ad-related app issues comprehensively and thus provide practical ad integration strategies for developers. We first define common ad issues …
Simultaneous Material Identification And Target Imaging With Commodity Rfid Devices,
2022
Singapore Management University
Simultaneous Material Identification And Target Imaging With Commodity Rfid Devices, Ju Wang, Jie Xiong, Xiaojiang Chen, Hongbo Jiang, Rajesh Krishna Balan, Dingyi Fang
Research Collection School Of Computing and Information Systems
Material identification and target imaging play an important role in many applications. This paper introduces TagScan, a system that can identify the material type and image the horizontal cut of a target simultaneously with cheap commodity Radio-Frequency IDentification (RFID) devices. The key intuition is that different materials and/or target sizes cause different amounts of phase and RSS (Received Signal Strength) changes, when radio frequency (RF) signal penetrates through the target. Multiple challenges need to be addressed before we can turn the idea into a functional system, including (i) indoor environments exhibit rich multipath which breaks the linear relationship between the …
Scriptchecker: To Tame Third-Party Script Execution With Task Capabilities,
2022
Singapore Management University
Scriptchecker: To Tame Third-Party Script Execution With Task Capabilities, Wu Luo, Xuhua Ding, Pengfei Wu, Xiaolei Zhang, Qingni Shen, Zhonghai Wu
Research Collection School Of Computing and Information Systems
We present ScriptChecker, a novel browser-based framework to effectively and efficiently restrict third-party script execution according to the host web page’s directives. Different from all existing schemes functioning at the JavaScript layer, ScriptChecker holistically harnesses context separation and the browser’s security monitors to enforce on-demand access controls upon tasks executing untrusted code. The host page can flexibly assign resource-access capabilities to tasks upon their creation. Reaping the benefits of the task capability approach, ScriptChecker outperforms existing techniques in security, usability and performance. We have implemented a prototype of ScriptChecker on Chrome and rigorously evaluated its security against 1373 malicious scripts …
Applications Of Unsupervised Machine Learning In Autism Spectrum Disorder Research: A Review,
2022
Chapman University
Applications Of Unsupervised Machine Learning In Autism Spectrum Disorder Research: A Review, Chelsea Parlett-Pelleriti, Elizabeth Stevens, Dennis R. Dixon, Erik J. Linstead
Engineering Faculty Articles and Research
Large amounts of autism spectrum disorder (ASD) data is created through hospitals, therapy centers, and mobile applications; however, much of this rich data does not have pre-existing classes or labels. Large amounts of data—both genetic and behavioral—that are collected as part of scientific studies or a part of treatment can provide a deeper, more nuanced insight into both diagnosis and treatment of ASD. This paper reviews 43 papers using unsupervised machine learning in ASD, including k-means clustering, hierarchical clustering, model-based clustering, and self-organizing maps. The aim of this review is to provide a survey of the current uses of …
Clinical Interactions In Electronic Medical Records Towards The Development Of A Token-Economy Model,
2022
Ateneo de Manila University
Clinical Interactions In Electronic Medical Records Towards The Development Of A Token-Economy Model, Nicole Allison S. Co, Jason Limcaco, Hans Calvin L. Tan, Ma. Regina Justina E. Estuar, Christian E. Pulmano, Dennis Andrew Villamor, Quirino Sugon Jr, Maria Cristina G. Bautista, Paulyn Jean Acacio-Claro
Graduate School of Business Publications
The use of electronic medical records (EMRs) plays a crucial role in the successful implementation of the Universal Healthcare Law which promises quality and affordable healthcare to all Filipinos. Consequently, the current adoption of EMRs should be studied from the perspective of the healthcare provider. As most studies look into use of EMRs by doctors or patients, there are very few that extend studies to look at possible interaction of doctor and patient in the same EMR environment. Understanding this interaction paves the way for possible incentives that will increase the use and adoption of the EMR. This study uses …
Did They Really Tweet That?,
2022
Old Dominion University
Did They Really Tweet That?, Caleb Bradford, Michael L. Nelson (Mentor)
Computer & Information Science: Research Experiences for Undergraduates in Disinformation Detection and Analytics
No abstract provided.
Algorithm-Based Fault Tolerance At Scale,
2022
University of Alabama in Huntsville
Algorithm-Based Fault Tolerance At Scale, Joshua Dennis Booth
Summer Community of Scholars (RCEU and HCR) Project Proposals
No abstract provided.
A Predictive Model To Predict Cyberattack Using Self-Normalizing Neural Networks,
2022
Marshall University
A Predictive Model To Predict Cyberattack Using Self-Normalizing Neural Networks, Oluwapelumi Eniodunmo
Theses, Dissertations and Capstones
Cyberattack is a never-ending war that has greatly threatened secured information systems. The development of automated and intelligent systems provides more computing power to hackers to steal information, destroy data or system resources, and has raised global security issues. Statistical and Data mining tools have received continuous research and improvements. These tools have been adopted to create sophisticated intrusion detection systems that help information systems mitigate and defend against cyberattacks. However, the advancement in technology and accessibility of information makes more identifiable elements that can be used to gain unauthorized access to systems and resources. Data mining and classification tools …
Towards More Efficient Collaborative Distributed Data Analysis And Learning,
2022
University of Central Florida
Towards More Efficient Collaborative Distributed Data Analysis And Learning, Zixia Liu
Electronic Theses and Dissertations, 2020-2023
Modern information era gives rise to the persistent generation of large amounts of data with rapid speed and broad geographical distribution. Obtaining knowledge and understanding via analysis and learning from such data have invaluable worth. Features of such data analytical tasks commonly include: data can be large scale and geographically distributed; computing capability demand can be enormous; tasks can be time-critical; some data can be private; participants can have heterogeneous capabilities and non-IID data; and multiple simultaneously submitted data analytical tasks can be possible. These bring challenges to contemporary computing infrastructure and learning models. In view of this, we develop …
Developing An Ios Game Application: Magnet Hockey,
2022
Bridgewater State University
Developing An Ios Game Application: Magnet Hockey, Trevor D. Wysong
The Graduate Review
Mobile application development requires mindful and meticulous planning. Application design should be responsive and intuitive so that navigation feels natural for the user. All targeted devices should be offered a relatively consistent experience. To ensure this, app performance needs to be closely monitored and different screen sizes and aspect ratios need to be considered when scaling. For an app to become attractive to many people, it should either be competitive with similar apps or be unique and interesting enough to entice people to download it. A unique app should couple familiar elements with new components or twists [8]. People are …
The State Of The Art Of Information Integration In Space Applications,
2022
Old Dominion University
The State Of The Art Of Information Integration In Space Applications, Zhuming Bi, K. L. Yung, Andrew W.H. Ip., Yuk Ming Tang, Chris W.J. Zhang, Li Da Xu
Information Technology & Decision Sciences Faculty Publications
This paper aims to present a comprehensive survey on information integration (II) in space informatics. With an ever-increasing scale and dynamics of complex space systems, II has become essential in dealing with the complexity, changes, dynamics, and uncertainties of space systems. The applications of space II (SII) require addressing some distinctive functional requirements (FRs) of heterogeneity, networking, communication, security, latency, and resilience; while limited works are available to examine recent advances of SII thoroughly. This survey helps to gain the understanding of the state of the art of SII in sense that (1) technical drivers for SII are discussed and …
Caption And Image Based Next-Word Auto-Completion,
2022
San Jose State University
Caption And Image Based Next-Word Auto-Completion, Meet Patel
Master's Projects
With the increasing number of options or choices in terms of entities like products, movies, songs, etc. which are now available to users, they try to save time by looking for an application or system that provides automatic recommendations. Recommender systems are automated computing processes that leverage concepts of Machine Learning, Data Mining and Artificial Intelligence towards generating product recommendations based on a user’s preferences. These systems have given a significant boost to businesses across multiple segments as a result of reduced human intervention. One similar aspect of this is content writing. It would save users a lot of time …
Whole File Chunk Based Deduplication Using Reinforcement Learning,
2022
San Jose State University
Whole File Chunk Based Deduplication Using Reinforcement Learning, Xincheng Yuan
Master's Projects
Deduplication is the process of removing replicated data content from storage facilities like online databases, cloud datastore, local file systems, etc., which is commonly performed as part of data preprocessing to eliminate redundant data that requires unnecessary storage spaces and computing power. Deduplication is even more specifically essential for file backup systems since duplicated files will presumably consume more storage space, especially with a short backup period like daily [8]. A common technique in this field involves splitting files into chunks whose hashes can be compared using data structures or techniques like clustering. In this project we explore the possibility …
Benchmarking Newsql Database Voltdb,
2022
San Jose State University
Benchmarking Newsql Database Voltdb, Kevin Schumacher
Master's Projects
NewSQL is a type of relational database that is able to horizontally scale while retaining linearizable consistency. This is an improvement over a traditional SQL relational database because SQL databases cannot effectively scale across multiple machines. This is also an improvement over NoSQL databases because NewSQL databases are designed from the ground up to be consistent and have ACID guarantees. However, it should be noted that NewSQL databases are not a one size fits all type of database, each specific database is designed to perform well on specific workloads. This project will evaluate a NewSQL database, VoltDB, with a focus …
Streaminghub: Interactive Stream Analysis Workflows,
2022
Old Dominion University
Streaminghub: Interactive Stream Analysis Workflows, Yasith Jayawardana, Vikas G. Ashok, Sampath Jayarathna
Computer Science Faculty Publications
Reusable data/code and reproducible analyses are foundational to quality research. This aspect, however, is often overlooked when designing interactive stream analysis workflows for time-series data (e.g., eye-tracking data). A mechanism to transmit informative metadata alongside data may allow such workflows to intelligently consume data, propagate metadata to downstream tasks, and thereby auto-generate reusable, reproducible analytic outputs with zero supervision. Moreover, a visual programming interface to design, develop, and execute such workflows may allow rapid prototyping for interdisciplinary research. Capitalizing on these ideas, we propose StreamingHub, a framework to build metadata propagating, interactive stream analysis workflows using visual programming. We conduct …
Visual Descriptor Extraction From Patent Figure Captions: A Case Study Of Data Efficiency Between Bilstm And Transformer,
2022
Old Dominion University
Visual Descriptor Extraction From Patent Figure Captions: A Case Study Of Data Efficiency Between Bilstm And Transformer, Xin Wei, Jian Wu, Kehinde Ajayi, Diane Oyen
Computer Science Faculty Publications
Technical drawings used for illustrating designs are ubiquitous in patent documents, especially design patents. Different from natural images, these drawings are usually made using black strokes with little color information, making it challenging for models trained on natural images to recognize objects. To facilitate indexing and searching, we propose an effective and efficient visual descriptor model that extracts object names and aspects from patent captions to annotate benchmark patent figure datasets. We compared two state-of-the-art named entity recognition (NER) models and found that with a limited number of annotated samples, the BiLSTM-CRF model outperforms the Transformer model by a significant …
D-Lib Magazine Pioneered Web-Based Scholarly Communication,
2022
Old Dominion University
D-Lib Magazine Pioneered Web-Based Scholarly Communication, Michael L. Nelson, Herbert Van De Sompel
Computer Science Faculty Publications
The web began with a vision of, as stated by Tim Berners-Lee in 1991, “that much academic information should be freely available to anyone”. For many years, the development of the web and the development of digital libraries and other scholarly communications infrastructure proceeded in tandem. A milestone occurred in July, 1995, when the first issue of D-Lib Magazine was published as an online, HTML-only, open access magazine, serving as the focal point for the then emerging digital library research community. In 2017 it ceased publication, in part due to the maturity of the community it served as well as …
