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Articles 631 - 660 of 6718
Full-Text Articles in Physical Sciences and Mathematics
Distance Based Image Classification: A Solution To Generative Classification’S Conundrum?, Wen-Yan Lin, Siying Liu, Bing Tian Dai, Hongdong Li
Distance Based Image Classification: A Solution To Generative Classification’S Conundrum?, Wen-Yan Lin, Siying Liu, Bing Tian Dai, Hongdong Li
Research Collection School Of Computing and Information Systems
Most classifiers rely on discriminative boundaries that separate instances of each class from everything else. We argue that discriminative boundaries are counter-intuitive as they define semantics by what-they-are-not; and should be replaced by generative classifiers which define semantics by what-they-are. Unfortunately, generative classifiers are significantly less accurate. This may be caused by the tendency of generative models to focus on easy to model semantic generative factors and ignore non-semantic factors that are important but difficult to model. We propose a new generative model in which semantic factors are accommodated by shell theory’s [25] hierarchical generative process and non-semantic factors by …
Deep Learning-Based Text Recognition Of Agricultural Regulatory Document, Hua Leong Fwa, Farn Haur Chan
Deep Learning-Based Text Recognition Of Agricultural Regulatory Document, Hua Leong Fwa, Farn Haur Chan
Research Collection School Of Computing and Information Systems
In this study, an OCR system based on deep learning techniques was deployed to digitize scanned agricultural regulatory documents comprising of certificates and labels. Recognition of the certificates and labels is challenging as they are scanned images of the hard copy form and the layout and size of the text as well as the languages vary between the various countries (due to diverse regulatory requirements). We evaluated and compared between various state-of-the-art deep learningbased text detection and recognition model as well as a packaged OCR library – Tesseract. We then adopted a two-stage approach comprising of text detection using Character …
Secure Hierarchical Deterministic Wallet Supporting Stealth Address, Xin Yin, Zhen Liu, Guomin Yang, Guoxing Chen, Haojin Zhu
Secure Hierarchical Deterministic Wallet Supporting Stealth Address, Xin Yin, Zhen Liu, Guomin Yang, Guoxing Chen, Haojin Zhu
Research Collection School Of Computing and Information Systems
Over the past decade, cryptocurrency has been undergoing a rapid development. Digital wallet, as the tool to store and manage the cryptographic keys, is the primary entrance for the public to access cryptocurrency assets. Hierarchical Deterministic Wallet (HDW), proposed in Bitcoin Improvement Proposal 32 (BIP32), has attracted much attention and been widely used in the community, due to its virtues such as easy backup/recovery, convenient cold-address management, and supporting trust-less audits and applications in hierarchical organizations. While HDW allows the wallet owner to generate and manage his keys conveniently, Stealth Address (SA) allows a payer to generate fresh address (i.e., …
Toward Intention Discovery For Early Malice Detection In Bitcoin, Ling Cheng, Feida Zhu, Yong Wang, Huiwen Liu
Toward Intention Discovery For Early Malice Detection In Bitcoin, Ling Cheng, Feida Zhu, Yong Wang, Huiwen Liu
Research Collection School Of Computing and Information Systems
Bitcoin has been subject to illicit activities more often than probably any other financial assets, due to the pseudo-anonymous nature of its transacting entities. An ideal detection model is expected to achieve all the three properties of (I) early detection, (II) good interpretability, and (III) versatility for various illicit activities. However, existing solutions cannot meet all these requirements, as most of them heavily rely on deep learning without satisfying interpretability and are only available for retrospective analysis of a specific illicit type.First, we present asset transfer paths, which aim to describe addresses' early characteristics. Next, with a decision tree based …
Exploiting Reuse For Gpu Subgraph Enumeration, Wentiao Guo, Yuchen Li, Kian-Lee Tan
Exploiting Reuse For Gpu Subgraph Enumeration, Wentiao Guo, Yuchen Li, Kian-Lee Tan
Research Collection School Of Computing and Information Systems
Subgraph enumeration is important for many applications such as network motif discovery, community detection, and frequent subgraph mining. To accelerate the execution, recent works utilize graphics processing units (GPUs) to parallelize subgraph enumeration. The performances of these parallel schemes are dominated by the set intersection operations which account for up to $95\%$ of the total processing time. (Un)surprisingly, a significant portion (as high as $99\%$) of these operations is actually redundant, i.e., the same set of vertices is repeatedly encountered and evaluated. Therefore, in this paper, we seek to salvage and recycle the results of such operations to avoid repeated …
Constrained Multiagent Reinforcement Learning For Large Agent Population, Jiajing Ling, Arambam James Singh, Duc Thien Nguyen, Akshat Kumar
Constrained Multiagent Reinforcement Learning For Large Agent Population, Jiajing Ling, Arambam James Singh, Duc Thien Nguyen, Akshat Kumar
Research Collection School Of Computing and Information Systems
Learning control policies for a large number of agents in a decentralized setting is challenging due to partial observability, uncertainty in the environment, and scalability challenges. While several scalable multiagent RL (MARL) methods have been proposed, relatively few approaches exist for large scale constrained MARL settings. To address this, we first formulate the constrained MARL problem in a collective multiagent setting where interactions among agents are governed by the aggregate count and types of agents, and do not depend on agents’ specific identities. Second, we show that standard Lagrangian relaxation methods, which are popular for single agent RL, do not …
Does Social Media Accelerate Product Recalls? Evidence From The Pharmaceutical Industry, Yang Gao, Wenjing Duan, Huaxia Rui
Does Social Media Accelerate Product Recalls? Evidence From The Pharmaceutical Industry, Yang Gao, Wenjing Duan, Huaxia Rui
Research Collection School Of Computing and Information Systems
Social media has become a vital platform for voicing product-related experiences that may not only reveal product defects but also impose pressure on firms to act more promptly than before. This study scrutinizes the rarely-studied relationship between these voices and the speed of product recalls in the context of the pharmaceutical industry where social media pharmacovigilance is becoming increasingly important for the detection of drug safety signals. Using Federal Drug Administration (FDA) drug enforcement reports and social media data crawled from online forums and Twitter, we investigate whether social media can accelerate the product recall process in the context of …
Towards An Optimal Bus Frequency Scheduling: When The Waiting Time Matters, Songsong Mo, Zhifeng Bao, Baihua Zheng, Zhiyong Peng
Towards An Optimal Bus Frequency Scheduling: When The Waiting Time Matters, Songsong Mo, Zhifeng Bao, Baihua Zheng, Zhiyong Peng
Research Collection School Of Computing and Information Systems
Reorganizing bus frequencies to cater for actual travel demands can significantly save the cost of the public transport system. This paper studies the bus frequency optimization problem considering the user satisfaction. Specifically, for the first time to our best knowledge, we study how to schedule the buses such that the total number of passengers who could receive their bus services within the waiting time threshold can be maximized. We propose two variants of the problem, FAST and FASTCO, to cater for different application needs and prove that both are NP-hard. To solve FAST effectively and efficiently, we first present an …
Performance Evaluation Of Aggregation-Based Group Recommender Systems For Ephemeral Groups, Edgar Ceh-Varela, Huiping Cao, Hady Wirawan Lauw
Performance Evaluation Of Aggregation-Based Group Recommender Systems For Ephemeral Groups, Edgar Ceh-Varela, Huiping Cao, Hady Wirawan Lauw
Research Collection School Of Computing and Information Systems
Recommender Systems (RecSys) provide suggestions in many decision-making processes. Given that groups of people can perform many real-world activities (e.g., a group of people attending a conference looking for a place to dine), the need for recommendations for groups has increased. A wide range of Group Recommender Systems (GRecSys) has been developed to aggregate individual preferences to group preferences. We analyze 175 studies related to GRecSys. Previous works evaluate their systems using different types of groups (sizes and cohesiveness), and most of such works focus on testing their systems using only one type of item, called Experience Goods (EG). As …
Towards A Model On Digital Transformation Within The Higher Education Sector – A South African Perspective, Olusegun A. Ajigini
Towards A Model On Digital Transformation Within The Higher Education Sector – A South African Perspective, Olusegun A. Ajigini
African Conference on Information Systems and Technology
Digital transformation is the application of technology to build new business models, processes, software and systems that result in more profitable revenue, greater competitive advantage and higher efficiency. The factors influencing digital transformation in the higher educational sector were examined in this study. Specifically, data was drawn from 400 respondents and the following variables: organizational IT application portfolio, organizational culture, organizational structure, leadership and ethics predict digital transformation in higher educational sector by using regression analysis. The researcher found that the organizational culture contribution was the highest by predicting 78.9% of digital transformation in the higher education sector.
Towards A Conceptual Model For Developing A Career Prediction System For Students’ Subject Selection At Secondary School Level, Moses Kamondo Tuhame, Gilbert Maiga, Annabella Habinka, Barbara Kayondo
Towards A Conceptual Model For Developing A Career Prediction System For Students’ Subject Selection At Secondary School Level, Moses Kamondo Tuhame, Gilbert Maiga, Annabella Habinka, Barbara Kayondo
African Conference on Information Systems and Technology
Career choice prediction has been a complex phenomenon both in developed and developing countries. Though various theories that describe career prediction have emerged, their practical implementation in the form of a system has been hampered by the shortfalls that come along with each of them. However, there is no existing theoretically based holistic model that merges various theories that can inform the development of such a system in the developing world context. This paper, therefore, aims at proposing a holistic conceptual model that integrates a number of variables to inform the development of a career prediction system in the developing …
Improving Deep Entity Resolution By Constraints, Soudeh Nilforoushan
Improving Deep Entity Resolution By Constraints, Soudeh Nilforoushan
Electronic Thesis and Dissertation Repository
Entity resolutions the problem of finding duplicate data in a dataset and resolving possible differences and inconsistencies. ER is a long-standing data management and information retrieval problem and a core data integration and cleaning task. There are diverse solutions for ER that apply rule-based techniques, pairwise binary classification, clustering, and probabilistic inference, among other techniques. Deep learning (DL) has been extensively used for ER and has shown competitive performance compared to conventional ER solutions. The state-of-the-art (SOTA) ER solutions using DL are based on pairwise comparison and binary classification. They transform pairs of records into a latent space that can …
“I Think I Discovered A Military Base In The Middle Of The Ocean”—Null Island, The Most Real Of Fictional Places, Levente Juhasz, Peter Mooney
“I Think I Discovered A Military Base In The Middle Of The Ocean”—Null Island, The Most Real Of Fictional Places, Levente Juhasz, Peter Mooney
GIS Center
This paper explores Null Island, a fictional place located at 0° latitude and 0° longitude in the WGS84 (World Geodetic System 1984) geographic coordinate system. Null Island is erroneously associated with large amounts of geographic data in a wide variety of location-based services, place databases, social media and web-based maps. Whereas it was originally considered a joke within the geospatial community, this article will demonstrate implications of its existence, both technological and social in nature, promoting Null Island as a fundamental issue of geographic information that requires more widespread awareness. The article summarizes error sources that lead to data being …
Automated Identification Of Astronauts On Board The International Space Station: A Case Study In Space Archaeology, Rao Hamza Ali, Amir Kanan Kashefi, Alice C. Gorman, Justin St. P. Walsh, Erik J. Linstead
Automated Identification Of Astronauts On Board The International Space Station: A Case Study In Space Archaeology, Rao Hamza Ali, Amir Kanan Kashefi, Alice C. Gorman, Justin St. P. Walsh, Erik J. Linstead
Art Faculty Articles and Research
We develop and apply a deep learning-based computer vision pipeline to automatically identify crew members in archival photographic imagery taken on-board the International Space Station. Our approach is able to quickly tag thousands of images from public and private photo repositories without human supervision with high degrees of accuracy, including photographs where crew faces are partially obscured. Using the results of our pipeline, we carry out a large-scale network analysis of the crew, using the imagery data to provide novel insights into the social interactions among crew during their missions.
(2022 Revision) Chapter 1: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana
(2022 Revision) Chapter 1: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana
Open Educational Resources
No abstract provided.
(2022 Revision) Chapter 4: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana
(2022 Revision) Chapter 4: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana
Open Educational Resources
No abstract provided.
(2022 Revision) Appendix: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana
(2022 Revision) Appendix: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana
Open Educational Resources
No abstract provided.
(2022 Revision) Chapter 2: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana
(2022 Revision) Chapter 2: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana
Open Educational Resources
No abstract provided.
(2022 Revision) Chapter 3: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana
(2022 Revision) Chapter 3: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana
Open Educational Resources
No abstract provided.
(2022 Revision) Chapter 6: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana
(2022 Revision) Chapter 6: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana
Open Educational Resources
No abstract provided.
(2022 Revision) Chapter 5: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana
(2022 Revision) Chapter 5: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana
Open Educational Resources
No abstract provided.
(2022 Revision) Chapter 7: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana
(2022 Revision) Chapter 7: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana
Open Educational Resources
No abstract provided.
React E-Commerce Application & Google Cloud Devops, Hemanth Panditi
React E-Commerce Application & Google Cloud Devops, Hemanth Panditi
Culminating Experience Projects
The “CIS 693” project consists of an electronic commerce React application and a developmental operations pipeline that was built in Google Cloud. Over the duration of the applied computer science program and popular trends in technology, there has been an emphasis on cloud computing, serverless technology/microservice architecture, containerization, and distributed computing in general. The cloud is an important and necessary platform to work from because it provides a central location with access to these tools, useful documentation, and informative demonstrations. The projects for previous classes revolved around similar topics as it is relevant in today’s context. The courses offered a …
Convivial Making: Power In Public Library Creative Places, Shannon Crawford Barniskis
Convivial Making: Power In Public Library Creative Places, Shannon Crawford Barniskis
Theses and Dissertations
In 2011, public libraries began to provide access to collaborative creative places, frequently called “makerspaces.” The professional literature portrays these as beneficial for communities and individuals through their support of creativity, innovation, learning, and access to high-tech tools such as 3D printers. As in longstanding “library faith” narratives, which pin the library’s existence to widely held values, makerspace rhetoric describes access to tools and skills as instrumental for a stronger economy or democracy, social justice, and/or individual happiness. The rhetoric generally frames these places as empowering. Yet the concept of power has been neither well-theorized within the library makerspace literature …
Understanding Learners' Motivation Through Machine Learning Analysis On Reflection Writing, Elizabeth Pluskwik, Yuezhou Wang, Lauren Singelmann
Understanding Learners' Motivation Through Machine Learning Analysis On Reflection Writing, Elizabeth Pluskwik, Yuezhou Wang, Lauren Singelmann
Integrated Engineering Department Publications
Educational data mining (EDM) is an emerging interdisciplinary field that utilizes a machine learning (ML) algorithm to collect and analyze educational data, aiming to better predict students' performance and retention. In this WIP paper, we report our methodology and preliminary results from utilizing a ML program to assess students’ motivation through their upper-division years in the XYZ project-based learning (PBL) program. ML, or more specifically, the clustering algorithm, opens the door to processing large amounts of student-written artifacts, such as reflection journals, project reports, and written assignments, and then identifies keywords that signal their levels of motivation (i.e., extrinsic vs. …
Investigating Toxicity Changes Of Cross-Community Redditors From 2 Billion Posts And Comments, Hind Almerekhi, Haewoon Kwak, Bernard J. Jansen
Investigating Toxicity Changes Of Cross-Community Redditors From 2 Billion Posts And Comments, Hind Almerekhi, Haewoon Kwak, Bernard J. Jansen
Research Collection School Of Computing and Information Systems
This research investigates changes in online behavior of users who publish in multiple communities on Reddit by measuring their toxicity at two levels. With the aid of crowdsourcing, we built a labeled dataset of 10,083 Reddit comments, then used the dataset to train and fine-tune a Bidirectional Encoder Representations from Transformers (BERT) neural network model. The model predicted the toxicity levels of 87,376,912 posts from 577,835 users and 2,205,581,786 comments from 890,913 users on Reddit over 16 years, from 2005 to 2020. This study utilized the toxicity levels of user content to identify toxicity changes by the user within the …
Trajectory Optimization For Safe Navigation In Maritime Traffic Using Historical Data, Chaithanya Basrur, Arambam James Singh, Arunesh Sinha, Akshat Kumar, T. K. Satish Kumar
Trajectory Optimization For Safe Navigation In Maritime Traffic Using Historical Data, Chaithanya Basrur, Arambam James Singh, Arunesh Sinha, Akshat Kumar, T. K. Satish Kumar
Research Collection School Of Computing and Information Systems
Increasing maritime trade often results in congestion in busy ports, thereby necessitating planning methods to avoid close quarter risky situations among vessels. Rapid digitization and automation of port operations and vessel navigation provide unique opportunities for significantly improving navigation safety. Our key contributions are as follows. First, given a set of future candidate trajectories for vessels in a traffic hotspot zone, we develop a multiagent trajectory optimization method to choose trajectories that result in the best overall close quarter risk reduction. Our novel MILP-based optimization method is more than an order-of-magnitude faster than a standard MILP for this problem, and …
Interpreting Trajectories From Multiple Views: A Hierarchical Self-Attention Network For Estimating The Time Of Arrival, Zebin Chen, Xiaolin Xiao, Yue-Jiao Gong, Jun Fang, Nan Ma, Hua Chai, Zhiguang Cao
Interpreting Trajectories From Multiple Views: A Hierarchical Self-Attention Network For Estimating The Time Of Arrival, Zebin Chen, Xiaolin Xiao, Yue-Jiao Gong, Jun Fang, Nan Ma, Hua Chai, Zhiguang Cao
Research Collection School Of Computing and Information Systems
Estimating the time of arrival is a crucial task in intelligent transportation systems. Although considerable efforts have been made to solve this problem, most of them decompose a trajectory into several segments and then compute the travel time by integrating the attributes from all segments. The segment view, though being able to depict the local traffic conditions straightforwardly, is insufficient to embody the intrinsic structure of trajectories on the road network. To overcome the limitation, this study proposes multi-view trajectory representation that comprehensively interprets a trajectory from the segment-, link-, and intersection-views. To fulfill the purpose, we design a hierarchical …
Variational Graph Author Topic Modeling, Ce Zhang, Hady Wirawan Lauw
Variational Graph Author Topic Modeling, Ce Zhang, Hady Wirawan Lauw
Research Collection School Of Computing and Information Systems
While Variational Graph Auto-Encoder (VGAE) has presented promising ability to learn representations for documents, most existing VGAE methods do not model a latent topic structure and therefore lack semantic interpretability. Exploring hidden topics within documents and discovering key words associated with each topic allow us to develop a semantic interpretation of the corpus. Moreover, documents are usually associated with authors. For example, news reports have journalists specializing in writing certain type of events, academic papers have authors with expertise in certain research topics, etc. Modeling authorship information could benefit topic modeling, since documents by the same authors tend to reveal …
Multimodal Private Signatures, Khoa Nguyen, Fuchun Guo, Willy Susilo, Guomin Yang
Multimodal Private Signatures, Khoa Nguyen, Fuchun Guo, Willy Susilo, Guomin Yang
Research Collection School Of Computing and Information Systems
We introduce Multimodal Private Signature (MPS) - an anonymous signature system that offers a novel accountability feature: it allows a designated opening authority to learn some partial information op about the signer’s identity id, and nothing beyond. Such partial information can flexibly be defined as op = id (as in group signatures), or as op = 0 (like in ring signatures), or more generally, as op = Gj (id), where Gj (·) is a certain disclosing function. Importantly, the value of op is known in advance by the signer, and hence, the latter can decide whether she/he wants to disclose …