(2022 Revision) Chapter 2: Essential Aspects Of Physical Design And Implementation Of Relational Databases,
2022
CUNY New York City College of Technology
(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 4: Essential Aspects Of Physical Design And Implementation Of Relational Databases,
2022
CUNY New York City College of Technology
(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) Chapter 5: Essential Aspects Of Physical Design And Implementation Of Relational Databases,
2022
CUNY New York City College of Technology
(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,
2022
CUNY New York City College of Technology
(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,
2022
Grand Valley State University
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 …
Smart Manufacturing—Theories, Methods, And Applications,
2022
Old Dominion University
Smart Manufacturing—Theories, Methods, And Applications, Zhuming Bi, Lida Xu, Puren Ouyang
Information Technology & Decision Sciences Faculty Publications
(First paragraph) Smart manufacturing (SM) distinguishes itself from other system paradigms by introducing ‘smartness’ as a measure to a manufacturing system; however, researchers in different domains have different expectations of system smartness from their own perspectives. In this Special Issue (SI), SM refers to a system paradigm where digital technologies are deployed to enhance system smartness by (1) empowering physical resources in production, (2) utilizing virtual and dynamic assets over the internet to expand system capabilities, (3) supporting data-driven decision making at all domains and levels of businesses, or (4) reconfiguring systems to adapt changes and uncertainties in dynamic environments. …
Investigating Toxicity Changes Of Cross-Community Redditors From 2 Billion Posts And Comments,
2022
Singapore Management University
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,
2022
Singapore Management University
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 …
Convivial Making: Power In Public Library Creative Places,
2022
University of Wisconsin-Milwaukee
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 …
Multimodal Private Signatures,
2022
Singapore Management University
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 …
Variational Graph Author Topic Modeling,
2022
Singapore Management University
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 …
Extract Human Mobility Patterns Powered By City Semantic Diagram,
2022
Fudan University
Extract Human Mobility Patterns Powered By City Semantic Diagram, Zhangqing Shan, Weiwei Shan, Baihua Zheng
Research Collection School Of Computing and Information Systems
With widespread deployment of GPS devices, massive spatiotemporal trajectories became more accessible. This booming trend paved the solid data ground for researchers to discover the regularities or patterns of human mobility. However, there are still three challenges in semantic pattern extraction including semantic absence, semantic bias and semantic complexity. In this paper, we invent and apply a novel data structure namely City Semantic Diagram to overcome above three challenges. First, our approach resolves semantic absence by exactly identifying semantic behaviours from raw trajectories. Second, the delicate design of semantic purification helps us to detect semantic complexity from human mobility. Third, …
A Low-Power Passive Uhf Tag With High-Precision Temperature Sensor For Human Body Application,
2022
Fuzhou University
A Low-Power Passive Uhf Tag With High-Precision Temperature Sensor For Human Body Application, Liang-Hung Wang, Zheng Pan, Hao Jiang, Hua-Ling Lai, Qi-Peng Ran, Patricia Angela R. Abu
Department of Information Systems & Computer Science Faculty Publications
Radio frequency identification (RFID) tags are widely used in various electronic devices due to their low cost, simple structure, and convenient data reading. This topic aims to study the key technologies of ultra-high frequency (UHF) RFID tags and high-precision temperature sensors, and how to reduce the power consumption of the temperature sensor and the overall circuits while maintaining minimal loss of performance. Combined with the biomedicine, an innovative high-precision human UHF RFID chip for body temperature monitoring is designed. In this study, a ring oscillator whose output frequency is linearly related to temperature is designed and proposed as a temperature-sensing …
A Detailed Review Work On The Existing Animal Detection System,
2022
North Bengal University,West Bengal,India
A Detailed Review Work On The Existing Animal Detection System, Dechen Doma Bhutia Miss, Swarup Das Dr., Rakesh Kumar Mandal Dr.
International Journal of Computer and Communication Technology
Technology plays a very important part in today’s world, the simplest of tasks demands technology and we as humans crave every day for better technology to make our lives easier, with the help of technology that saves us valuable time and energy which can be utilized to do more productive work, amongst technological advances, expert system plays a very important role in every field and the major field where expert systems can be employed in, is animal detection, for the welfare of animals and the people who need to interact and at times avoid interaction with these animals. The review …
Strategic Signaling For Utility Control In Audit Games,
2022
Purdue University
Strategic Signaling For Utility Control In Audit Games, Jianan Chen, Qin Hu, Honglu Jiang
Informatics and Engineering Systems Faculty Publications and Presentations
As an effective method to protect the daily access to sensitive data against malicious attacks, the audit mechanism has been widely deployed in various practical fields. In order to examine security vulnerabilities and prevent the leakage of sensitive data in a timely manner, the database logging system usually employs an online signaling scheme to issue an alert when suspicious access is detected. Defenders can audit alerts to reduce potential damage. This interaction process between a defender and an attacker can be modeled as an audit game. In previous studies, it was found that sending real-time signals in the audit …
Real-Time Hierarchical Map Segmentation For Coordinating Multi-Robot Exploration,
2022
Singapore Management University
Real-Time Hierarchical Map Segmentation For Coordinating Multi-Robot Exploration, Tianze Luo, Zichen Chen, Budhitama Subagdja, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Coordinating a team of autonomous agents to explore an environment can be done by partitioning the map of the environment into segments and allocating the segments as targets for the individual agents to visit. However, given an unknown environment, map segmentation must be conducted in a continuous and incremental manner. In this paper, we propose a novel real-time hierarchical map segmentation method for supporting multi-agent exploration of indoor environments, wherein clusters of regions of segments are formed hierarchically from randomly sampled points in the environment. Each cluster is then assigned with a cost-utility value based on the minimum cost possible …
Early Rumor Detection Using Neural Hawkes Process With A New Benchmark Dataset,
2022
Singapore Management University
Early Rumor Detection Using Neural Hawkes Process With A New Benchmark Dataset, Fengzhu Zeng, Wei Gao
Research Collection School Of Computing and Information Systems
Little attention has been paid on EArly Rumor Detection (EARD), and EARD performance was evaluated inappropriately on a few datasets where the actual early-stage information is largely missing. To reverse such situation, we construct BEARD, a new Benchmark dataset for EARD, based on claims from fact-checking websites by trying to gather as many early relevant posts as possible. We also propose HEARD, a novel model based on neural Hawkes process for EARD, which can guide a generic rumor detection model to make timely, accurate and stable predictions. Experiments show that HEARD achieves effective EARD performance on two commonly used general …
Structured And Natural Responses Co-Generation For Conversational Search,
2022
Singapore Management University
Structured And Natural Responses Co-Generation For Conversational Search, Chenchen Ye, Lizi Liao, Fuli Feng, Wei Ji, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Generating fluent and informative natural responses while main- taining representative internal states for search optimization is critical for conversational search systems. Existing approaches ei- ther 1) predict structured dialog acts first and then generate natural response; or 2) map conversation context to natural responses di- rectly in an end-to-end manner. Both kinds of approaches have shortcomings. The former suffers from error accumulation while the semantic associations between structured acts and natural re- sponses are confined in single direction. The latter emphasizes generating natural responses but fails to predict structured acts. Therefore, we propose a neural co-generation model that gener- ates …
Automatic Noisy Label Correction For Fine-Grained Entity Typing,
2022
Singapore Management University
Automatic Noisy Label Correction For Fine-Grained Entity Typing, Weiran Pan, Wei Wei, Feida Zhu
Research Collection School Of Computing and Information Systems
Fine-grained entity typing (FET) aims to assign proper semantic types to entity mentions according to their context, which is a fundamental task in various entity-leveraging applications. Current FET systems usually establish on large-scale weaklysupervised/distantly annotation data, which may contain abundant noise and thus severely hinder the performance of the FET task. Although previous studies have made great success in automatically identifying the noisy labels in FET, they usually rely on some auxiliary resources which may be unavailable in real-world applications (e.g., pre-defined hierarchical type structures, humanannotated subsets). In this paper, we propose a novel approach to automatically correct noisy labels …
Multi-Level Cross-View Contrastive Learning For Knowledge-Aware Recommender System,
2022
Singapore Management University
Multi-Level Cross-View Contrastive Learning For Knowledge-Aware Recommender System, Ding Zou, Wei Wei, Xian-Ling Mao, Ziyang Wang, Minghui Qiu, Feida Zhu, Xin Cao
Research Collection School Of Computing and Information Systems
Knowledge graph (KG) plays an increasingly important role in recommender systems. Recently, graph neural networks (GNNs) based model has gradually become the theme of knowledge-aware recommendation (KGR). However, there is a natural deficiency for GNN-based KGR models, that is, the sparse supervised signal problem, which may make their actual performance drop to some extent. Inspired by the recent success of contrastive learning in mining supervised signals from data itself, in this paper, we focus on exploring the contrastive learning in KG-aware recommendation and propose a novel multi-level cross-view contrastive learning mechanism, named MCCLK. Different from traditional contrastive learning methods which …
