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Full-Text Articles in Physical Sciences and Mathematics

A Mean-Field Markov Decision Process Model For Spatial Temporal Subsidies In Ride-Sourcing Markets, Zheng Zhu, Jintao Ke, Hai Wang Jul 2022

A Mean-Field Markov Decision Process Model For Spatial Temporal Subsidies In Ride-Sourcing Markets, Zheng Zhu, Jintao Ke, Hai Wang

Research Collection School Of Computing and Information Systems

Ride-sourcing services are increasingly popular because of their ability to accommodate on-demand travel needs. A critical issue faced by ride-sourcing platforms is the supply-demand imbalance, as a result of which drivers may spend substantial time on idle cruising and picking up remote passengers. Some platforms attempt to mitigate the imbalance by providing relocation guidance for idle drivers who may have their own self-relocation strategies and decline to follow the suggestions. Platforms then seek to induce drivers to system-desirable locations by offering them subsidies. This paper proposes a mean-field Markov decision process (MF-MDP) model to depict the dynamics in ride-sourcing markets ...


Decomposing Generation Networks With Structure Prediction For Recipe Generation, Hao Wang, Guosheng Lin, Steven C. H. Hoi, Chunyan Miao Jun 2022

Decomposing Generation Networks With Structure Prediction For Recipe Generation, Hao Wang, Guosheng Lin, Steven C. H. Hoi, Chunyan Miao

Research Collection School Of Computing and Information Systems

Recipe generation from food images and ingredients is a challenging task, which requires the interpretation of the information from another modality. Different from the image captioning task, where the captions usually have one sentence, cooking instructions contain multiple sentences and have obvious structures. To help the model capture the recipe structure and avoid missing some cooking details, we propose a novel framework: Decomposing Generation Networks (DGN) with structure prediction, to get more structured and complete recipe generation outputs. Specifically, we split each cooking instruction into several phases, and assign different sub-generators to each phase. Our approach includes two novel ideas ...


Promoting Infrastructure Construction In Advance To Support Sci-Tech Self-Reliance And Self-Strengthening At Higher Level, Yang Wang, Yuanchun Zhou, Yanguang Wang, Jianhui Li, Fazhi Qi, Honglin He, Fangyu Liao May 2022

Promoting Infrastructure Construction In Advance To Support Sci-Tech Self-Reliance And Self-Strengthening At Higher Level, Yang Wang, Yuanchun Zhou, Yanguang Wang, Jianhui Li, Fazhi Qi, Honglin He, Fangyu Liao

Bulletin of Chinese Academy of Sciences (Chinese Version)

The research infrastructure is the basic and strategic platform of scientific and technological innovation. In the last decade, China's research infrastructure has achieved leapfrog development in the level of observation, manufacturing, management, data acquisition, data sharing and utilization, which supports China's scientific and technological innovation activities at a higher level. Looking into the future, the scientific research paradigm is transforming. The network, data, and computing platform will not only support the development of major science and technology infrastructure and field stations in larger, more accurate, and more advanced approach, but also contribute to the transformation of scientific research ...


Information Provenance For Mobile Health Data, Taylor A. Hardin May 2022

Information Provenance For Mobile Health Data, Taylor A. Hardin

Dartmouth College Ph.D Dissertations

Mobile health (mHealth) apps and devices are increasingly popular for health research, clinical treatment and personal wellness, as they offer the ability to continuously monitor aspects of individuals' health as they go about their everyday activities. Many believe that combining the data produced by these mHealth apps and devices may give healthcare-related service providers and researchers a more holistic view of an individual's health, increase the quality of service, and reduce operating costs. For such mHealth data to be considered useful though, data consumers need to be assured that the authenticity and the integrity of the data has remained ...


Prospects For Legal Analytics: Some Approaches To Extracting More Meaning From Legal Texts, Kevin D. Ashley May 2022

Prospects For Legal Analytics: Some Approaches To Extracting More Meaning From Legal Texts, Kevin D. Ashley

University of Cincinnati Law Review

No abstract provided.


An Investigation Into, And The Construction Of, An Operable Windows Notifier, Grey Hixson May 2022

An Investigation Into, And The Construction Of, An Operable Windows Notifier, Grey Hixson

Computer Science and Computer Engineering Undergraduate Honors Theses

The Office of Sustainability at the University of Arkansas identified that building occupants that have control over operable windows may open them at inappropriate times. Windows opened in a building with a temperature and air differential leads to increased HVAC operating costs and building occupant discomfort. This led the Associate Vice Chancellor of Facilities at the University of Arkansas to propose the construction of a mobile application that a building occupant can use to make an informed decision before opening their window. I have formulated a series of research objectives in conjunction with the Director of the Office of Sustainability ...


Using A Bert-Based Ensemble Network For Abusive Language Detection, Noah Ballinger May 2022

Using A Bert-Based Ensemble Network For Abusive Language Detection, Noah Ballinger

Computer Science and Computer Engineering Undergraduate Honors Theses

Over the past two decades, online discussion has skyrocketed in scope and scale. However, so has the amount of toxicity and offensive posts on social media and other discussion sites. Despite this rise in prevalence, the ability to automatically moderate online discussion platforms has seen minimal development. Recently, though, as the capabilities of artificial intelligence (AI) continue to improve, the potential of AI-based detection of harmful internet content has become a real possibility. In the past couple years, there has been a surge in performance on tasks in the field of natural language processing, mainly due to the development of ...


Implementing The Cms+ Sports Rankings Algorithm In A Javafx Environment, Luke Welch May 2022

Implementing The Cms+ Sports Rankings Algorithm In A Javafx Environment, Luke Welch

Industrial Engineering Undergraduate Honors Theses

Every year, sports teams and athletes get cut from championship opportunities because of their rank. While this reality is easier to swallow if a team or athlete is distant from the cut, it is much harder when they are right on the edge. Many times, it leaves fans and athletes wondering, “Why wasn’t I ranked higher? What factors when into the ranking? Are the rankings based on opinion alone?” These are fair questions that deserve an answer. Many times, sports rankings are derived from opinion polls. Other times, they are derived from a combination of opinion polls and measured ...


College Of Education Filemaker Extraction And End-User Database Development, Andrew Tran May 2022

College Of Education Filemaker Extraction And End-User Database Development, Andrew Tran

Electronic Theses, Projects, and Dissertations

The College of Education (CoE) at the California State University San Bernardino (CSUSB) developed a system to keep track of both state and national accreditation requirements using FileMaker 5, a database system. This accreditation data is crucial for reporting and record-keeping for the CSU Chancellor’s Office as well as the State of California. However, the database system was developed several decades ago, and software support has long since been dropped, causing the CoE’s legacy accreditation data to be at risk of being lost should the software or hardware suffer permanent failure. The purpose of this project was to ...


Performance Comparison Of The Filesystem And Embedded Key-Value Databases, Jesse Hines, Nicholas Cunningham Apr 2022

Performance Comparison Of The Filesystem And Embedded Key-Value Databases, Jesse Hines, Nicholas Cunningham

Campus Research Day

A common scenario when developing local applications is storing many records and then retrieving them by ID. A developer can simply save the records as files or use an embedded database. Large numbers of files can slow down filesystems, but developers may want to avoid a dependency on an embedded database if it offers little benefit for their use case. We will compare the performance for the insert, update, get and delete operations and the space efficiency of storing records as files vs. using key-value embedded databases including RocksDB, LevelDB, Berkley DB, and SQLite.


Database Query Execution Through Virtual Reality, Logan Bateman, Marc Butler Apr 2022

Database Query Execution Through Virtual Reality, Logan Bateman, Marc Butler

Campus Research Day

Building database queries often requires technical knowledge of a query language. However, company employees, such as executives, managers, and others (outside of software research and development, generally) may not have the pre-required knowledge to accurately construct and execute database queries. This paper proposes an approach to constructing database queries using virtual reality. This approach utilizes natural hand or controller gestures which map to various components of building and visualizing database queries.


Realtime Visualization Of Kafka Architectures, Matthew Jensen, Miro Manestar Apr 2022

Realtime Visualization Of Kafka Architectures, Matthew Jensen, Miro Manestar

Campus Research Day

Apache Kafka specializes in the transfer of incredibly large amounts of data in real-time between devices. However, it can be difficult to comprehend the inner workings of Kafka. Often, to get real-time data, a user must run complicated commands from within the Kafka CLI. Our contribution is a tool that monitors Kafka consumers, producers, and topics, and displays the flow of events between them in a web-based dashboard. This dashboard serves to reduce the complexity of Kafka and enables users unfamiliar with the platform and protocol to better understand how their architecture is configured.


Novel 360-Degree Camera, Ian Gauger, Andrew Kurtz, Zakariya Niazi Apr 2022

Novel 360-Degree Camera, Ian Gauger, Andrew Kurtz, Zakariya Niazi

Frameless

Circle Optics is developing novel technology for low-parallax, real time, panoramic image capture using an integrated array of multiple adjacent polygonal-edged cameras. This technology can be optimized and deployed for a variety of markets, including cinematic VR. Circle Optics’ existing prototype, Hydra Alpha, will be demonstrated.


Iot Clusters Platform For Data Collection, Analysis, And Visualization Use Case, Soin Abdoul Kassif Baba M Traore Apr 2022

Iot Clusters Platform For Data Collection, Analysis, And Visualization Use Case, Soin Abdoul Kassif Baba M Traore

Symposium of Student Scholars

Climate change is happening, and many countries are already facing devastating consequences. Populations worldwide are adapting to the season's unpredictability they relay to lands for agriculture. Our first research was to develop an IoT Clusters Platform for Data Collection, analysis, and visualization. The platform comprises hardware parts with Raspberry Pi and Arduino's clusters connected to multiple sensors. The clusters transmit data collected in real-time to microservices-based servers where the data can be accessed and processed. Our objectives in developing this platform were to create an efficient data collection system, relatively cheap to implement and easy to deploy in ...


Students Certification Management (Scm): Hyperledger Fabric-Based Digital Repository, Md Jobair Hossain Faruk, Hossain Shahriar, Maria Valero Apr 2022

Students Certification Management (Scm): Hyperledger Fabric-Based Digital Repository, Md Jobair Hossain Faruk, Hossain Shahriar, Maria Valero

Symposium of Student Scholars

The higher education sector has been heavily impacted financially by the economic downturn caused by the pandemic that has resulted a decline in student enrollments. Finding cost-effective novel technology for storing and sharing student's credentials among academic institutions and potential employers is a demand. Within the current conventional approach, ensuring authentication of a candidate’s credentials is costly and time-consuming which gives burdens to thousands of prospective students and potential employees. As a result, candidates fail to secure opportunities for either delay or non-submission of credentials all over the world. Blockchain technology has the potential for students' control over ...


A False Sense Of Security - Organizations Need A Paradigm Shift On Protecting Themselves Against Apts, Srinivasulu R. Vuggumudi Apr 2022

A False Sense Of Security - Organizations Need A Paradigm Shift On Protecting Themselves Against Apts, Srinivasulu R. Vuggumudi

Masters Theses & Doctoral Dissertations

Organizations Advanced persistent threats (APTs) are the most complex cyberattacks and are generally executed by cyber attackers linked to nation-states. The motivation behind APT attacks is political intelligence and cyber espionage. Despite all the awareness, technological advancements, and massive investment, the fight against APTs is a losing battle for organizations. An organization may implement a security strategy to prevent APTs. However, the benefits to the security posture might be negligible if the measurement of the strategy’s effectiveness is not part of the plan. A false sense of security exists when the focus is on implementing a security strategy but ...


Leaderboard Design Principles Influencing User Engagement In An Online Discussion, Brian S. Bovee Apr 2022

Leaderboard Design Principles Influencing User Engagement In An Online Discussion, Brian S. Bovee

Masters Theses & Doctoral Dissertations

Along with the popularity of gamification, there has been increased interest in using leaderboards to promote engagement with online learning systems. The existing literature suggests that when leaderboards are designed well they have the potential to improve learning, but qualitative investigations are required in order to reveal design principles that will improve engagement. In order to address this gap, this qualitative study aims to explore students' overall perceptions of popular leaderboard designs in a gamified, online discussion. Using two leaderboards reflecting performance in an online discussion, this study evaluated multiple leaderboard designs from student interviews and other data sources regarding ...


A Survey On Modern Deep Neural Network For Traffic Prediction: Trends, Methods And Challenges, David Alexander Tedjopumomo, Zhifeng Bao, Baihua Zheng, Farhana Murtaza Choudhury, Kai Qin Apr 2022

A Survey On Modern Deep Neural Network For Traffic Prediction: Trends, Methods And Challenges, David Alexander Tedjopumomo, Zhifeng Bao, Baihua Zheng, Farhana Murtaza Choudhury, Kai Qin

Research Collection School Of Computing and Information Systems

In this modern era, traffic congestion has become a major source of negative economic and environmental impact for urban areas worldwide. One of the most efficient ways to mitigate traffic congestion is through future traffic prediction. The field of traffic prediction has evolved greatly ever since its inception in the late 70s. Earlier studies mainly use classical statistical models such as ARIMA and its variants. Then, researchers started to focus on machine learning models due to their power and flexibility. As theoretical and technological advances emerge, we enter the era of deep neural network, which gained popularity due to its ...


Sibnet: Food Instance Counting And Segmentation, Huu-Thanh. Nguyen, Chong-Wah Ngo, Wing-Kwong Chan Apr 2022

Sibnet: Food Instance Counting And Segmentation, Huu-Thanh. Nguyen, Chong-Wah Ngo, Wing-Kwong Chan

Research Collection School Of Computing and Information Systems

Food computing has recently attracted considerable research attention due to its significance for health risk analysis. In the literature, the majority of research efforts are dedicated to food recognition. Relatively few works are conducted for food counting and segmentation, which are essential for portion size estimation. This paper presents a deep neural network, named SibNet, for simultaneous counting and extraction of food instances from an image. The problem is challenging due to varying size and shape of food as well as arbitrary viewing angle of camera, not to mention that food instances often occlude each other. SibNet is novel for ...


Learning For Amalgamation: A Multi-Source Transfer Learning Framework For Sentiment Classification, Cuong V. Nguyen, Khiem H. Le, Hong Quang Pham, Quang H. Pham, Binh T. Nguyen Apr 2022

Learning For Amalgamation: A Multi-Source Transfer Learning Framework For Sentiment Classification, Cuong V. Nguyen, Khiem H. Le, Hong Quang Pham, Quang H. Pham, Binh T. Nguyen

Research Collection School Of Computing and Information Systems

Transfer learning plays an essential role in Deep Learning, which can remarkably improve the performance of the target domain, whose training data is not sufficient. Our work explores beyond the common practice of transfer learning with a single pre-trained model. We focus on the task of Vietnamese sentiment classification and propose LIFA, a framework to learn a unified embedding from several pre-trained models. We further propose two more LIFA variants that encourage the pre-trained models to either cooperate or compete with one another. Studying these variants sheds light on the success of LIFA by showing that sharing knowledge among the ...


Fine-Grained Detection Of Academic Emotions With Spatial Temporal Graph Attention Networks Using Facial Landmarks, Hua Leong Fwa Apr 2022

Fine-Grained Detection Of Academic Emotions With Spatial Temporal Graph Attention Networks Using Facial Landmarks, Hua Leong Fwa

Research Collection School Of Computing and Information Systems

With the incidence of the Covid-19 pandemic, institutions have adopted online learning as the main lessondelivery channel. A common criticism of online learning is that sensing of learners’ affective states such asengagement is lacking which degrades the quality of teaching. In this study, we propose automatic sensing of learners’ affective states in an online setting with web cameras capturing their facial landmarks and head poses. We postulate that the sparsely connected facial landmarks can be modelled using a Graph Neural Network. Using the publicly available in the wild DAiSEE dataset, we modelled both the spatial and temporal dimensions of the ...


Osm Science - The Academic Study Of The Openstreetmap Project, Data, Contributors, Community, And Applications, A. Yair Grinberger, Marco Minghini, Levente Juhasz, Godwin Yeboah, Peter Mooney Mar 2022

Osm Science - The Academic Study Of The Openstreetmap Project, Data, Contributors, Community, And Applications, A. Yair Grinberger, Marco Minghini, Levente Juhasz, Godwin Yeboah, Peter Mooney

GIS Center

This paper is an Editorial for the Special Issue titled “OpenStreetMap as a multidisciplinary nexus: perspectives, practices and procedures”. The Special Issue is largely based on the talks presented in the 2019 and 2020 editions of the Academic Track at the State of the Map conferences. As such, it represents the most pressing and relevant issues and topics considered by the academic community in relation to OpenStreetMap (OSM)—a global project and community aimed to create and maintain a free and editable database and map of the world. In this Editorial, we survey the papers included in the Special Issue ...


Building Capacity For Data-Driven Scholarship, Jamie Rogers Mar 2022

Building Capacity For Data-Driven Scholarship, Jamie Rogers

Works of the FIU Libraries

This talk provides an overview of "dLOC as Data: A Thematic Approach to Caribbean Newspapers," an initiative developed to increase access to digitized Caribbean newspaper text for bulk download, facilitating computational analysis. Capacity building for future research in Caribbean Studies being a crucial aspect of this initiative, a thematic toolkit was developed to facilitate use of the project data as well as provide replicable processes. The toolkit includes sample text analysis projects, as well as tutorials and detailed project documentation. While the toolkit focuses on the history of hurricanes and tropical cyclones of the region, the methodologies and tools used ...


Wifitrace: Network-Based Contact Tracing For Infectious Diseases Using Passive Wifi Sensing, Amee Trivedi, Camellia Zakaria, Rajesh Krishna Balan, Ann Becker, George Corey, Prashant Shenoy Mar 2022

Wifitrace: Network-Based Contact Tracing For Infectious Diseases Using Passive Wifi Sensing, Amee Trivedi, Camellia Zakaria, Rajesh Krishna Balan, Ann Becker, George Corey, Prashant Shenoy

Research Collection School Of Computing and Information Systems

Contact tracing is a well-established and effective approach for the containment of the spread of infectious diseases. While Bluetooth-based contact tracing method using phones has become popular recently, these approaches suffer from the need for a critical mass adoption to be effective. In this paper, we present WiFiTrace, a network-centric approach for contact tracing that relies on passive WiFi sensing with no client-side involvement. Our approach exploits WiFi network logs gathered by enterprise networks for performance and security monitoring, and utilizes them for reconstructing device trajectories for contact tracing. Our approach is specifically designed to enhance the efficacy of traditional ...


Mg2vec: Learning Relationship-Preserving Heterogeneous Graph Representations Via Metagraph Embedding, Wentao Zhang, Yuan Fang, Zemin Liu, Min Wu, Xinming Zhang Mar 2022

Mg2vec: Learning Relationship-Preserving Heterogeneous Graph Representations Via Metagraph Embedding, Wentao Zhang, Yuan Fang, Zemin Liu, Min Wu, Xinming Zhang

Research Collection School Of Computing and Information Systems

Given that heterogeneous information networks (HIN) encompass nodes and edges belonging to different semantic types, they can model complex data in real-world scenarios. Thus, HIN embedding has received increasing attention, which aims to learn node representations in a low-dimensional space, in order to preserve the structural and semantic information on the HIN. In this regard, metagraphs, which model common and recurring patterns on HINs, emerge as a powerful tool to capture semantic-rich and often latent relationships on HINs. Although metagraphs have been employed to address several specific data mining tasks, they have not been thoroughly explored for the more general ...


Learning User Interface Semantics From Heterogeneous Networks With Multi-Modal And Positional Attributes, Gary Ang, Ee-Peng Lim Mar 2022

Learning User Interface Semantics From Heterogeneous Networks With Multi-Modal And Positional Attributes, Gary Ang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

User interfaces (UI) of desktop, web, and mobile applications involve a hierarchy of objects (e.g. applications, screens, view class, and other types of design objects) with multimodal (e.g. textual, visual) and positional (e.g. spatial location, sequence order and hierarchy level) attributes. We can therefore represent a set of application UIs as a heterogeneous network with multimodal and positional attributes. Such a network not only represents how users understand the visual layout of UIs, but also influences how users would interact with applications through these UIs. To model the UI semantics well for different UI annotation, search, and ...


Deep Learning For Anomaly Detection: A Review, Guansong Pang, Chunhua Shen, Longbing Cao, Anton Van Den Hengel Mar 2022

Deep Learning For Anomaly Detection: A Review, Guansong Pang, Chunhua Shen, Longbing Cao, Anton Van Den Hengel

Research Collection School Of Computing and Information Systems

Anomaly detection, a.k.a. outlier detection or novelty detection, has been a lasting yet active research area in various research communities for several decades. There are still some unique problem complexities and challenges that require advanced approaches. In recent years, deep learning enabled anomaly detection, i.e., deep anomaly detection, has emerged as a critical direction. This article surveys the research of deep anomaly detection with a comprehensive taxonomy, covering advancements in 3 high-level categories and 11 fine-grained categories of the methods. We review their key intuitions, objective functions, underlying assumptions, advantages, and disadvantages and discuss how they address ...


Thoughts On Data-Driven Discursive Logic And Triangulation Of Think Tank, Jianjun Sun, Lei Pei, Yaxue Ma, Yang Li Feb 2022

Thoughts On Data-Driven Discursive Logic And Triangulation Of Think Tank, Jianjun Sun, Lei Pei, Yaxue Ma, Yang Li

Bulletin of Chinese Academy of Sciences (Chinese Version)

The rapid accumulation of data resources and the development of analysis technologies have expanded the scope of think tank research, and prompted think tanks to pay more attention to data intelligence. Meanwhile, higher requirements are put forward on the quality and innovation of the think tank. Facing the development needs of think tanks, i.e., modernization, innovation, and conscientization, this paper demonstrates the change of data-driven think tank researches from the perspective of the information chain. The paper analyzes the urgent need to reshape the discursive logic of the think tank, and discusses the construction scheme of triangulation for data-driven ...


The Effect Of Using The Gamification Strategy On Academic Achievement And Motivation Towards Learning Problem-Solving Skills In Computer And Information Technology Course Among Tenth Grade Female Students, Mazyunah Almutairi, Prof. Ahmad Almassaad Feb 2022

The Effect Of Using The Gamification Strategy On Academic Achievement And Motivation Towards Learning Problem-Solving Skills In Computer And Information Technology Course Among Tenth Grade Female Students, Mazyunah Almutairi, Prof. Ahmad Almassaad

International Journal for Research in Education

Abstract

This study aimed to identify the effect of using the gamification strategy on academic achievement and motivation towards learning problem-solving skills in computer and information technology course. A quasi-experimental method was adopted. The study population included tenth-grade female students in Al-Badi’ah schools in Riyadh. The sample consisted of 54 students divided into two equal groups: control group and experimental group. The study tools comprised an achievement test and the motivation scale. The results showed that there were statistically significant differences between the two groups in the academic achievement test in favor of the experimental group, with a large ...


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 Feb 2022

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 ...