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Articles 1111 - 1140 of 6720

Full-Text Articles in Physical Sciences and Mathematics

Effective Digital Learning Practices For Is Design Courses During Covid-19, Eng Lieh Ouh, Benjamin Gan Aug 2021

Effective Digital Learning Practices For Is Design Courses During Covid-19, Eng Lieh Ouh, Benjamin Gan

Research Collection School Of Computing and Information Systems

The COVID-19 pandemic has pushed educational institutions to adopt digital learning for an extended period. This research studies the effectiveness of digital learning practices based on student feedback data collected for two Information Systems design courses: human interaction design and solution architecture design. This paper leverages the data to analyze the effectiveness of a set of digital learning practices: ZOOM lectures, polling or Kahoot questions, self-reflection, virtual exercises and virtual mentorship. Our research questions are on the effectiveness of these learning practices to keep the student’s interest and learn the course materials. The research compares each learning practice and the …

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The Is Social Continuance Model: Using Conversational Agents To Support Co-Creation, Naif Alawi Jul 2021

The Is Social Continuance Model: Using Conversational Agents To Support Co-Creation, Naif Alawi

USF Tampa Graduate Theses and Dissertations

With the rise of Agentic IS Artifact and the increasing integration of this technology within organizations, our understanding of the impact of this technology on individuals remains limited. Although IS use literature provides important guidance for organization to increase employees’ willingness to work with new technology implementations, the utilitarian view of prior IS use limits its application in light of the new evolving social interaction between humans and Agentic IS Artifacts. To that end, we contribute to the IS use literature by implementing a social view to understand the impact of Agentic IS Artifacts on an individual’s perception and behavior. …

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Dan Farkas, Dan Farkas Jul 2021

Dan Farkas, Dan Farkas

Oral History

Dan Farkas has taught on the Pleasantville campus of Pace University since 1977.

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Service Quality Monitoring In Confined Spaces Through Mining Twitter Data, Mohammad Masoud Rahimi, Elham Naghizade, Mark Stevenson, Stephan Winter Jul 2021

Service Quality Monitoring In Confined Spaces Through Mining Twitter Data, Mohammad Masoud Rahimi, Elham Naghizade, Mark Stevenson, Stephan Winter

Journal of Spatial Information Science

Promoting public transport depends on adapting effective tools for concurrent monitoring of perceived service quality. Social media feeds, in general, provide an opportunity to ubiquitously look for service quality events, but when applied to confined geographic area such as a transport node, the sparsity of concurrent social media data leads to two major challenges. Both the limited number of social media messages--leading to biased machine-learning--and the capturing of bursty events in the study period considerably reduce the effectiveness of general event detection methods. In contrast to previous work and to face these challenges, this paper presents a hybrid solution based …

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The Impact Of Urban Road Network Morphology On Pedestrian Wayfinding Behaviour, Debjit Bhowmick, Stephan Winter, Mark Stevenson, Peter Vortisch Jul 2021

The Impact Of Urban Road Network Morphology On Pedestrian Wayfinding Behaviour, Debjit Bhowmick, Stephan Winter, Mark Stevenson, Peter Vortisch

Journal of Spatial Information Science

During wayfinding pedestrians do not always choose the shortest available route. Instead, route choices are guided by several well-known wayfinding strategies or heuristics. These heuristics minimize cognitive effort and usually lead to satisfactory route choices. Our previous study evaluated the costs of four well-known pedestrian wayfinding heuristics and their variation across nine network morphologies. It was observed that the variation in the cost of these wayfinding heuristics increased with an increase in the irregularity of the network, indicating that people may opt for more diverse heuristics while walking through relatively regular networks, and may prefer specific heuristics in the relatively …

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How Does Socio-Economic And Demographic Dissimilarity Determine Physical And Virtual Segregation?, Michael Dorman, Tal Svoray, Itai Kloog Jul 2021

How Does Socio-Economic And Demographic Dissimilarity Determine Physical And Virtual Segregation?, Michael Dorman, Tal Svoray, Itai Kloog

Journal of Spatial Information Science

It is established that socio-economic and demographic dissimilarities between populations are determinants of spatial segregation. However, the understanding of how such dissimilarities translate into actual segregation is limited. We propose a novel network-analysis approach to comprehensively study the determinants of communicative and mobility-related spatial segregation, using geo-tagged Twitter data. We constructed weighted spatial networks representing tie strength between geographical areas, then modeled tie formation as a function of socio-economic and demographic dissimilarity between areas. Physical and virtual tie formation were affected by income, age, and race differences, although these effects were smaller by an order of magnitude than the geographical …

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Geocomputation 2019 Special Feature, Antoni Moore, Mark Gahegan Jul 2021

Geocomputation 2019 Special Feature, Antoni Moore, Mark Gahegan

Journal of Spatial Information Science

No abstract provided.

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Modelling Orebody Structures: Block Merging Algorithms And Block Model Spatial Restructuring Strategies Given Mesh Surfaces Of Geological Boundaries, Raymond Leung Jul 2021

Modelling Orebody Structures: Block Merging Algorithms And Block Model Spatial Restructuring Strategies Given Mesh Surfaces Of Geological Boundaries, Raymond Leung

Journal of Spatial Information Science

This paper describes a framework for capturing geological structures in a 3D block model and improving its spatial fidelity, including the correction of stratigraphic, mineralisation and other types of boundaries, given new mesh surfaces. Using surfaces that represent geological boundaries, the objectives are to identify areas where refinement is needed, increase spatial resolution to minimise surface approximation error, reduce redundancy to increase the compactness of the model and identify the geological domain on a block-by-block basis. These objectives are fulfilled by four system components which perform block-surface overlap detection, spatial structure decomposition, sub-blocks consolidation and block tagging, respectively. The main …

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Big Issues For Big Data: Challenges For Critical Spatial Data Analytics, Chris Brunsdon, Alexis Comber Jul 2021

Big Issues For Big Data: Challenges For Critical Spatial Data Analytics, Chris Brunsdon, Alexis Comber

Journal of Spatial Information Science

In this paper we consider some of the issues of working with big data and big spatial data and highlight the need for an open and critical framework. We focus on a set of challenges underlying the collection and analysis of big data. In particular, we consider 1) inference when working with usually biased big data, challenging the assumed inferential superiority of data with observations, n, approaching N, the population n -> N. We also emphasise 2) the need for analyses that answer questions of practical significance or with greater emphasis on the size of the effect, rather than the …

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Route Schematization With Landmarks, Marcelo De Lima Galvao, Jakub Krukar, Martin Noellenburg, Angela Schwering Jul 2021

Route Schematization With Landmarks, Marcelo De Lima Galvao, Jakub Krukar, Martin Noellenburg, Angela Schwering

Journal of Spatial Information Science

Predominant navigation applications make use of a turn-by-turn instructions approach and are mostly supported by small screen devices. This combination does little to improve users' orientation or spatial knowledge acquisition. Considering this limitation, we propose a route schematization method aimed for small screen devices to facilitate the readability of route information and survey knowledge acquisition. Current schematization methods focus on the route path and ignore context information, specially polygonal landmarks (such as lakes, parks, and regions), which is crucial for promoting orientation. Our schematization method, in addition to the route path, takes as input: adjacent streets, point-like landmarks, and polygonal …

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Local Modelling: One Size Does Not Fit All, A. Stewart Fotheringham Jul 2021

Local Modelling: One Size Does Not Fit All, A. Stewart Fotheringham

Journal of Spatial Information Science

This editorial piece considers what happens when we abandon the concept that models of social processes have global application in favor of a local approach in which context or the influence of 'place' has an important role. A brief history of this local approach to statistical modelling is given, followed by a consideration of its ramifications for understanding societal issues. The piece concludes with futures challenges and prospects in this area.

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Indigeneity And Spatial Information Science, Matt Duckham, Serene Ho Jul 2021

Indigeneity And Spatial Information Science, Matt Duckham, Serene Ho

Journal of Spatial Information Science

Spatial information science has given rise to a set of concepts, tools, and techniques for understanding our geographic world. In turn, the technologies built on this body of knowledge embed certain ways of knowing." This vision paper traces the roots and impacts of those embeddings and explores how they can sometimes be inherently at odds with or completely subvert Indigenous Peoples' ways of knowing. However advancements in spatial information science offer opportunities for innovation whilst working towards reconciliation. We highlight as examples four active research topics in the field to support a call to action for greater inclusion of Indigenous …

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Inferring Movement Patterns From Geometric Similarity, Maike Buchin, Carola Wenk Jul 2021

Inferring Movement Patterns From Geometric Similarity, Maike Buchin, Carola Wenk

Journal of Spatial Information Science

Spatial movement data nowadays is becoming ubiquitously available, including data of animals, vehicles and people. This data allows us to analyze the underlying movement. In particular, it allows us to infer movement patterns, such as recurring places and routes. Many methods to do so rely on the notion of similarity of places or routes. Here we briefly survey how research on this has developed in the past 15 years and outline challenges for future work.

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Why Are Events Important And How To Compute Them In Geospatial Research?, May Yuan Jul 2021

Why Are Events Important And How To Compute Them In Geospatial Research?, May Yuan

Journal of Spatial Information Science

Geospatial research has long centered around objects. While attention to events is growing rapidly, events remain objectified in spatial databases. This paper aims to highlight the importance of events in scientific inquiries and overview general event-based approaches to data modeling and computing. As machine learning algorithms and big data become popular in geospatial research, many studies appear to be the products of convenience with readily adaptable data and codes rather than curiosity. By asking why events are important and how to compute events in geospatial research, the author intends to provoke thinking into the rationale and conceptual basis of event-based …

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Integrated Science Of Movement, Urska Demsar, Jed A. Long, Katarzyna Sila-Nowicka Jul 2021

Integrated Science Of Movement, Urska Demsar, Jed A. Long, Katarzyna Sila-Nowicka

Journal of Spatial Information Science

Recent technological advances in movement data acquisition have enabled researchers in many disciplines to study movement at increasingly detailed spatial and temporal scales. Yet there is little overlap in the sharing of methods and models between disciplines, despite similar research objectives and data models. Attempts to bridge this gap are leading towards the establishment of an overarching interdisciplinary science, termed the Integrated Science of Movement. Here we present opportunities and challenges of this process and outline the crucial role that GIScience as a discipline with a focus on space, place, and time can play in the integrated science of movement.

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From Spatial To Platial - The Role And Future Of Immersive Technologies In The Spatial Sciences, Alexander Klippel Jul 2021

From Spatial To Platial - The Role And Future Of Immersive Technologies In The Spatial Sciences, Alexander Klippel

Journal of Spatial Information Science

Immersive technologies such as virtual and augmented reality have been part of the technology mindset in computer and geospatial sciences early on. The promise of delivering realistic experiences to the human senses that are not bound by physical reality has inspired generations of scientists and entrepreneurs alike. However, the vision for immersive experiences has been in stark contrast to the ability to deliver at the technology end; the community has battled nuisances such as cybersickness, tethers, and the uncanny valley for the last decades. With the 'final wave' of immersive technologies, we are now able to fulfill a long-held promise …

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Thinking Spatial, Mohamed F. Mokbel Jul 2021

Thinking Spatial, Mohamed F. Mokbel

Journal of Spatial Information Science

The systems community in both academia and industry has tremendous success in building widely used general purpose systems for various types of data and applications. Examples include database systems, big data systems, data streaming systems, and machine learning systems. The vast majority of these systems are ill equipped in terms of supporting spatial data. The main reason is that system builders mostly think of spatial data as just one more type of data. Any spatial support can be considered as an afterthought problem that can be supported via on-top functions or spatial cartridges that can be added to the already …

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Cartographic Generalization, Monika Sester Jul 2021

Cartographic Generalization, Monika Sester

Journal of Spatial Information Science

This short paper gives a subjective view on cartographic generalization, its achievements in the past, and the challenges it faces in the future.

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Josis' 10th Anniversary Special Feature: Part Two, Benjamin Adams, Somayeh Dodge, Ross Purves Jul 2021

Josis' 10th Anniversary Special Feature: Part Two, Benjamin Adams, Somayeh Dodge, Ross Purves

Journal of Spatial Information Science

No abstract provided.

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Variational Learning From Implicit Bandit Feedback, Quoc Tuan Truong, Hady W. Lauw Jul 2021

Variational Learning From Implicit Bandit Feedback, Quoc Tuan Truong, Hady W. Lauw

Research Collection School Of Computing and Information Systems

Recommendations are prevalent in Web applications (e.g., search ranking, item recommendation, advertisement placement). Learning from bandit feedback is challenging due to the sparsity of feedback limited to system-provided actions. In this work, we focus on batch learning from logs of recommender systems involving both bandit and organic feedbacks. We develop a probabilistic framework with a likelihood function for estimating not only explicit positive observations but also implicit negative observations inferred from the data. Moreover, we introduce a latent variable model for organic-bandit feedbacks to robustly capture user preference distributions. Next, we analyze the behavior of the new likelihood under two …

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An Automated Method To Enrich And Expand Consumer Health Vocabularies Using Glove Word Embeddings, Mohammed Ibrahim Jul 2021

An Automated Method To Enrich And Expand Consumer Health Vocabularies Using Glove Word Embeddings, Mohammed Ibrahim

Graduate Theses and Dissertations

Clear language makes communication easier between any two parties. However, a layman may have difficulty communicating with a professional due to not understanding the specialized terms common to the domain. In healthcare, it is rare to find a layman knowledgeable in medical jargon, which can lead to poor understanding of their condition and/or treatment. To bridge this gap, several professional vocabularies and ontologies have been created to map laymen medical terms to professional medical terms and vice versa. Many of the presented vocabularies are built manually or semi-automatically requiring large investments of time and human effort and consequently the slow …

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A Differentially Private Task Planning Framework For Spatial Crowdsourcing, Qian Tao, Yongxin Tong, Shuyuan Li, Yuxiang Zeng, Zimu Zhou, Ke Xu Jul 2021

A Differentially Private Task Planning Framework For Spatial Crowdsourcing, Qian Tao, Yongxin Tong, Shuyuan Li, Yuxiang Zeng, Zimu Zhou, Ke Xu

Research Collection School Of Computing and Information Systems

Spatial crowdsourcing has stimulated various new applications such as taxi calling and food delivery. A key enabler for these spatial crowdsourcing based applications is to plan routes for crowd workers to execute tasks given diverse requirements of workers and the spatial crowdsourcing platform. Despite extensive studies on task planning in spatial crowdsourcing, few have accounted for the location privacy of tasks, which may be misused by an untrustworthy platform. In this paper, we explore efficient task planning for workers while protecting the locations of tasks. Specifically, we define the Privacy-Preserving Task Planning (PPTP) problem, which aims at both total revenue …

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Dehumor: Visual Analytics For Decomposing Humor, Xingbo Wang, Yao Ming, Tongshuang Wu, Haipeng Zeng, Yong Wang, Huamin Qu Jul 2021

Dehumor: Visual Analytics For Decomposing Humor, Xingbo Wang, Yao Ming, Tongshuang Wu, Haipeng Zeng, Yong Wang, Huamin Qu

Research Collection School Of Computing and Information Systems

Despite being a critical communication skill, grasping humor is challenginga successful use of humor requires a mixture of both engaging content build-up and an appropriate vocal delivery (e.g., pause). Prior studies on computational humor emphasize the textual and audio features immediately next to the punchline, yet overlooking longer-term context setup. Moreover, the theories are usually too abstract for understanding each concrete humor snippet. To fill in the gap, we develop DeHumor, a visual analytical system for analyzing humorous behaviors in public speaking. To intuitively reveal the building blocks of each concrete example, DeHumor decomposes each humorous video into multimodal features …

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Integrated Framework For Developing Instructional Videos For Foundational Computing Courses, Kyong Jin Shim, Gottipati Swapna, Yi Meng Lau Jul 2021

Integrated Framework For Developing Instructional Videos For Foundational Computing Courses, Kyong Jin Shim, Gottipati Swapna, Yi Meng Lau

Research Collection School Of Computing and Information Systems

Instructional videos are widely used in higher education due to their effectiveness and flexibility of personalized learning features. Computing courses usually focuses on programming, user interface design, server connectivity, data storage, and architecture, among others. The design of instructional videos varies in not only the course content but also the style of content creation. We propose an integrated framework, Computing Videos Design Framework (CVDF), for designing and developing instructional videos for computing courses. CVDF combines the cognitive skills from Bloom’s taxonomy, video design principles, and course learning outcomes for designing different types of instructional videos. We apply the framework to …

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Meta-Inductive Node Classification Across Graphs, Zhihao Wen, Yuan Fang, Zemin Liu Jul 2021

Meta-Inductive Node Classification Across Graphs, Zhihao Wen, Yuan Fang, Zemin Liu

Research Collection School Of Computing and Information Systems

Semi-supervised node classification on graphs is an important research problem, with many real-world applications in information retrieval such as content classification on a social network and query intent classification on an e-commerce query graph. While traditional approaches are largely transductive, recent graph neural networks (GNNs) integrate node features with network structures, thus enabling inductive node classification models that can be applied to new nodes or even new graphs in the same feature space. However, inter-graph differences still exist across graphs within the same domain. Thus, training just one global model (e.g., a state-of-the-art GNN) to handle all new graphs, whilst …

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Make It Easy: An Effective End-To-End Entity Alignment Framework, Congcong Ge, Xiaoze Liu, Lu Chen Chen, Baihua Zheng, Yunjun Gao Jul 2021

Make It Easy: An Effective End-To-End Entity Alignment Framework, Congcong Ge, Xiaoze Liu, Lu Chen Chen, Baihua Zheng, Yunjun Gao

Research Collection School Of Computing and Information Systems

Entity alignment (EA) is a prerequisite for enlarging the coverage of a unified knowledge graph. Previous EA approaches either restrain the performance due to inadequate information utilization or need labor-intensive pre-processing to get external or reliable information to perform the EA task. This paper proposes EASY, an effective end-to-end EA framework, which is able to (i) remove the labor-intensive pre-processing by fully discovering the name information provided by the entities themselves; and (ii) jointly fuse the features captured by the names of entities and the structural information of the graph to improve the EA results. Specifically, EASY first introduces NEAP, …

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Marina: Faster Non-Convex Distributed Learning With Compression, Eduard Gorbunov, Konstantin Burlachenko, Zhize Li, Peter Richtarik Jul 2021

Marina: Faster Non-Convex Distributed Learning With Compression, Eduard Gorbunov, Konstantin Burlachenko, Zhize Li, Peter Richtarik

Research Collection School Of Computing and Information Systems

We develop and analyze MARINA: a new communication efficient method for non-convex distributed learning over heterogeneous datasets. MARINA employs a novel communication compression strategy based on the compression of gradient differences that is reminiscent of but different from the strategy employed in the DIANA method of Mishchenko et al. (2019). Unlike virtually all competing distributed first-order methods, including DIANA, ours is based on a carefully designed biased gradient estimator, which is the key to its superior theoretical and practical performance. The communication complexity bounds we prove for MARINA are evidently better than those of all previous first-order methods. Further, we …

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A Machine Learning Approach To Understanding Emerging Markets, Namita Balani Jul 2021

A Machine Learning Approach To Understanding Emerging Markets, Namita Balani

Graduate Theses and Dissertations

Logistic providers have learned to efficiently serve their existing customer bases with optimized routes and transportation resource allocation. The problem arises when there is potential for logistics growth in an emerging market with no previous data. The purpose of this work is to use industry data for previously known and well-documented markets to apply data analytic techniques such as machine learning to investigate the uncertainty in a new market. The thesis looks into machine learning techniques to predict miles per stop given historical data. It mainly focuses on Random Forest Regression Analysis, but concludes that additional techniques, such as Polynomial …

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Signal Processing And Data Analysis For Real-Time Intermodal Freight Classification Through A Multimodal Sensor System., Enrique J. Sanchez Headley Jul 2021

Signal Processing And Data Analysis For Real-Time Intermodal Freight Classification Through A Multimodal Sensor System., Enrique J. Sanchez Headley

Graduate Theses and Dissertations

Identifying freight patterns in transit is a common need among commercial and municipal entities. For example, the allocation of resources among Departments of Transportation is often predicated on an understanding of freight patterns along major highways. There exist multiple sensor systems to detect and count vehicles at areas of interest. Many of these sensors are limited in their ability to detect more specific features of vehicles in traffic or are unable to perform well in adverse weather conditions. Despite this limitation, to date there is little comparative analysis among Laser Imaging and Detection and Ranging (LIDAR) sensors for freight detection …

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Design And Development Of Techniques To Ensure Integrity In Fog Computing Based Databases, Abdulwahab Fahad S. Alazeb Jul 2021

Design And Development Of Techniques To Ensure Integrity In Fog Computing Based Databases, Abdulwahab Fahad S. Alazeb

Graduate Theses and Dissertations

The advancement of information technology in coming years will bring significant changes to the way sensitive data is processed. But the volume of generated data is rapidly growing worldwide. Technologies such as cloud computing, fog computing, and the Internet of things (IoT) will offer business service providers and consumers opportunities to obtain effective and efficient services as well as enhance their experiences and services; increased availability and higher-quality services via real-time data processing augment the potential for technology to add value to everyday experiences. This improves human life quality and easiness. As promising as these technological innovations, they are prone …

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