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2021

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Articles 2731 - 2760 of 3476

Full-Text Articles in Computer Sciences

5g Sa And Nsa Solutions, Drilon Berisha Jan 2021

5g Sa And Nsa Solutions, Drilon Berisha

Theses and Dissertations

This paper explains in detail the 5G packet core gateway solution. It also gives an overview of the 5G Architecture, the platform and the hardware details of this solution. 5G is the next generation of Third-Generation Partnership Program (3GPP) technology, after 4G/LTE, being defined for wireless mobile data communication. Starting with 3GPP Release 15 onward, this technology defines standards for 5G. As part of 3GPP Release 15, new 5G Radio and Packet Core evolution is being defined to cater to the needs of 5G networks. The two solutions that will be talked about in this paper are 5G Non-Standalone (NSA) …

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Përdorimi I Koncepteve Algjebrike Në Korigjimin E Gabimeve Te Kodet Lineare, Venera Musliu Jan 2021

Përdorimi I Koncepteve Algjebrike Në Korigjimin E Gabimeve Te Kodet Lineare, Venera Musliu

Theses and Dissertations

Ne si shoqëri, në kohën që jetojmë do të ishte e pamundur funksionimi i kësaj shoqërie nëse nuk do ekzistonin metoda të besueshme të cilat sigurojnë integritetin dhe konfidencialitetin e informacionit. Mbrojtja ndaj këtyre gabimeve të cilat ndodhin në mënyrë të pashmangshme në procesin e transmetimit dhe ruajtjes së të dhënave është objekt i teorisë së kodeve të korrigjimit të gabimit. Disa kode korrigjimi të gabimeve, shumë të rëndësishme dhe të dobishme, janë hartuar duke përdorur koncepte algjebrike si: fusha të fundme, polinomiale, klasat e ekuivalencës, hapësirat vektoriale etj. Algjebra abstrakte është njëra nga degët më aktive të matematikës, e …

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The Implementation Of A Novel Graphical Python Editor (Stremecoder) In A Rodent Discrimination Apparatus, Supraja Kalva Jan 2021

The Implementation Of A Novel Graphical Python Editor (Stremecoder) In A Rodent Discrimination Apparatus, Supraja Kalva

Senior Honors Theses and Projects

As the interest in neuroscience and the desire to perform behavioral tasks in a higher level of specificity and accuracy increases, the need to have tools and techniques to conduct experimentations in a low-cost automated manner is essential. Although such methods have been proposed previously by other researchers, they have presented their data and tools in a manner that would have been difficult to comprehend for non-programmers. In labs that do not have the accessibility to individuals who can understand the published procedures, it is very difficult for them to get started and manipulate the published procedures to their interests. …

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Entropy In Music: An Analysis Of Shape Note Music In Terms Of Information Entropy, Kyle Major Jan 2021

Entropy In Music: An Analysis Of Shape Note Music In Terms Of Information Entropy, Kyle Major

Honors Program Theses

This paper will be centered on a case study designed to probe a possible objective method for analyzing music that has already proven itself in the analysis computational systems: information theory. More specifically, this study has been conducted through the collection of data on information entropy in the genre of shape note music. The genre of shape note music has been chosen for its relative simplicity compared to other genres such as the classical symphony, which will render it significantly easier to analyze objectively. Information entropy as proposed by Claude Shannon, makes an excellent method for objective analysis because it …

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A Customizable Speech Practice Application For People Who Stutter, Eric Grimm, Nikola Vuckovic Jan 2021

A Customizable Speech Practice Application For People Who Stutter, Eric Grimm, Nikola Vuckovic

Honors Program Theses

Stuttering is a speech impediment that often requires speech therapy to curb the symptoms. In speech therapy, people who stutter (PWS) learn techniques that they can use to improve their fluency. PWS often practice their techniques extensively in order to maintain fluent speech. Many listen to audio recordings to practice where a single word or sentence is played on the recording and then there is a pause, giving the user a chance to say the word(s) to practice. This style of practice is not customizable and is repetitive since the contents do not change. Thus, we have developed an application …

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Formal Reasoning For Analyzing Goal Models That Evolve Over Time, Alicia M. Grubb, Marsha Chechik Jan 2021

Formal Reasoning For Analyzing Goal Models That Evolve Over Time, Alicia M. Grubb, Marsha Chechik

Computer Science: Faculty Publications

No abstract provided.

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Sequencing Red Fox Y Chromosome Fragments To Develop Phylogenetically Informative Snp Markers And Glimpse Male-Specific Trans-Pacific Phylogeography, Benjamin N. Sacks, Zachary T. Lounsberry, Halie M. Rando, Kristopher Kluepfel, Steven R. Fain, Sarah K. Brown, Anna V. Kukekova Jan 2021

Sequencing Red Fox Y Chromosome Fragments To Develop Phylogenetically Informative Snp Markers And Glimpse Male-Specific Trans-Pacific Phylogeography, Benjamin N. Sacks, Zachary T. Lounsberry, Halie M. Rando, Kristopher Kluepfel, Steven R. Fain, Sarah K. Brown, Anna V. Kukekova

Computer Science: Faculty Publications

The red fox (Vulpes vulpes) has a wide global distribution with many ecotypes and has been bred in captivity for various traits, making it a useful evolutionary model system. The Y chromosome represents one of the most informative markers of phylogeography, yet it has not been well-studied in the red fox due to a lack of the necessary genomic resources. We used a target capture approach to sequence a portion of the red fox Y chromosome in a geographically diverse red fox sample, along with other canid species, to develop single nucleotide polymorphism (SNP) markers, 13 of which we validated …

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Secure Data Sharing In Cloud And Iot By Leveraging Attribute-Based Encryption And Blockchain, Md Azharul Islam Jan 2021

Secure Data Sharing In Cloud And Iot By Leveraging Attribute-Based Encryption And Blockchain, Md Azharul Islam

Doctoral Dissertations

“Data sharing is very important to enable different types of cloud and IoT-based services. For example, organizations migrate their data to the cloud and share it with employees and customers in order to enjoy better fault-tolerance, high-availability, and scalability offered by the cloud. Wearable devices such as smart watch share user’s activity, location, and health data (e.g., heart rate, ECG) with the service provider for smart analytic. However, data can be sensitive, and the cloud and IoT service providers cannot be fully trusted with maintaining the security, privacy, and confidentiality of the data. Hence, new schemes and protocols are required …

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Swill-Tac: Skill-Oriented Dynamic Task Allocation With Willingness For Complex Job In Crowdsourcing, Riya Samanta, Soumya K. Ghosh, Sajal K. Das Jan 2021

Swill-Tac: Skill-Oriented Dynamic Task Allocation With Willingness For Complex Job In Crowdsourcing, Riya Samanta, Soumya K. Ghosh, Sajal K. Das

Computer Science Faculty Research & Creative Works

Allocating tasks to the best-fit candidates is a classical problem in crowdsourcing (CS). Most of the existing approaches assume that the task and candidate knowledge is known in advance and ignore the effect of enrolled candidates' willingness on the CS system's selection decision. For instance, an unwilling candidate assigned to a task may quit without completing it, thus depreciating the utility of the CS platform. In practice, a task or candidate may arrive or leave the CS system dynamically. Moreover, a complex task may be broken into smaller sub-tasks, each requiring a variety of computations and expertise. To overcome these …

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Nodesense2vec: Spatiotemporal Context-Aware Network Embedding For Heterogeneous Urban Mobility Data, Dakshak Keerthi Chandra, Jennifer Leopold, Yanjie Fu Jan 2021

Nodesense2vec: Spatiotemporal Context-Aware Network Embedding For Heterogeneous Urban Mobility Data, Dakshak Keerthi Chandra, Jennifer Leopold, Yanjie Fu

Computer Science Faculty Research & Creative Works

The problem of learning latent representations of heterogeneous networks with spatial and temporal attributes has been gaining traction in recent years, given its myriad of real-world applications. Most systems with applications in the field of transportation, urban economics, medical information, online e-commerce, etc., handle big data that can be structured into Spatiotemporal Heterogeneous Networks (SHNs), thereby making efficient analysis of these networks extremely vital. In this paper, we propose a spatiotemporal context-aware network embedding framework that jointly captures the spatial regularities between objects and the sequential transition patterns of human mobility. First, we model the heterogeneous urban mobility data collected …

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Visualization As A Service For Scientific Data, David Pugmire, James Kress, Jieyang Chen, Hank Childs, Jong Choi, Dmitry Ganyushin, Berk Geveci, Mark Kim, Scott Klasky, Xin Liang, For Full List Of Authors, See Publisher's Website. Jan 2021

Visualization As A Service For Scientific Data, David Pugmire, James Kress, Jieyang Chen, Hank Childs, Jong Choi, Dmitry Ganyushin, Berk Geveci, Mark Kim, Scott Klasky, Xin Liang, For Full List Of Authors, See Publisher's Website.

Computer Science Faculty Research & Creative Works

One of the primary challenges facing scientists is extracting understanding from the large amounts of data produced by simulations, experiments, and observational facilities. The use of data across the entire lifetime ranging from real-time to post-hoc analysis is complex and varied, typically requiring a collaborative effort across multiple teams of scientists. Over time, three sets of tools have emerged: One set for analysis, another for visualization, and a final set for orchestrating the tasks. This trifurcated tool set often results in the manual assembly of analysis and visualization workflows, which are one-off solutions that are often fragile and difficult to …

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Diverse Data! Diverse Schemata?, Krzysztof Janowicz, Cogan Shimizu, Pascal Hitzler, Gengchen Mai, Shirly Stephen, Rui Zhu, Ling Cai, Lu Zhou, Mark Schildhauer, Zilong Liu, Zhangyu Wang, Meilin Shi Jan 2021

Diverse Data! Diverse Schemata?, Krzysztof Janowicz, Cogan Shimizu, Pascal Hitzler, Gengchen Mai, Shirly Stephen, Rui Zhu, Ling Cai, Lu Zhou, Mark Schildhauer, Zilong Liu, Zhangyu Wang, Meilin Shi

Computer Science and Engineering Faculty Publications

One of the key value propositions for knowledge graphs and semantic web technologies is fostering semantic interoperability, i.e., integrating data across different themes and domains. But why do we aim at interoperability in the first place? A common answer to this question is that each individual data source only contains partial information about some phenomenon of interest. Consequently, combining multiple diverse datasets provides a more holistic perspective and enables us to answer more complex questions, e.g., those that span between the physical sciences and the social sciences. Interestingly, while these arguments are well established and go by different names, e.g., …

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Toward Undifferentiated Cognitive Models, Colin Kupitz, Aaron Eberhart, Daniel Schmidt, Christopher Stevens, Cogan Shimizu, Pascal Hitzler, Dario D. Salvucci, Benji Maruyama, Christopher W. Myers Jan 2021

Toward Undifferentiated Cognitive Models, Colin Kupitz, Aaron Eberhart, Daniel Schmidt, Christopher Stevens, Cogan Shimizu, Pascal Hitzler, Dario D. Salvucci, Benji Maruyama, Christopher W. Myers

Computer Science and Engineering Faculty Publications

Autonomous systems are a new frontier for pushing sociotechnical advancement. Such systems will eventually become pervasive, involved in everything from manufacturing, healthcare, defense, and even research itself. However, proliferation is stifled by the high development costs and the resulting inflexibility of the produced systems. The current time needed to create and integrate state of the art autonomous systems that operate as team members in complex situations is a 3-15 year development period, often requiring humans to adapt to limitations in the resulting systems. A new research thrust in interactive task learning (ITL: Laird et al., 2017) has begun, calling for …

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Automatically Generating Human Readable Documentation For Ontology Design Patterns, Cogan Shimizu, Pascal Hitzler Jan 2021

Automatically Generating Human Readable Documentation For Ontology Design Patterns, Cogan Shimizu, Pascal Hitzler

Computer Science and Engineering Faculty Publications

Keeping documentation consistent across deliverables is frequently a hassle. This program is a method for extracting and utilizing the common documentation annotations and those more specific to ontology design patterns from OWL files and rendering via LaTeX to provide a human readable, shareable PDF.

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An Effective And Efficient Graph Representation Learning Approach For Big Graphs, Edoardo Serra, Mikel Joaristi, Alfredo Cuzzocrea, Selim Soufargi, Carson K. Leung Jan 2021

An Effective And Efficient Graph Representation Learning Approach For Big Graphs, Edoardo Serra, Mikel Joaristi, Alfredo Cuzzocrea, Selim Soufargi, Carson K. Leung

Computer Science Faculty Publications and Presentations

In the Big Data era, large graph datasets are becoming increasingly popular due to their capability to integrate and interconnect large sources of data in many fields, e.g., social media, biology, communication networks, etc. Graph representation learning is a flexible tool that automatically extracts features from a graph node. These features can be directly used for machine learning tasks. Graph representation learning approaches producing features preserving the structural information of the graphs are still an open problem, especially in the context of large-scale graphs. In this paper, we propose a new fast and scalable structural representation learning approach called SparseStruct. …

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Semantics Of The Black-Box: Can Knowledge Graphs Help Make Deep Learning Systems More Interpretable And Explainable?, Manas Gaur, Keyur Faldu, Amit Sheth Jan 2021

Semantics Of The Black-Box: Can Knowledge Graphs Help Make Deep Learning Systems More Interpretable And Explainable?, Manas Gaur, Keyur Faldu, Amit Sheth

Publications

The recent series of innovations in deep learning (DL) have shown enormous potential to impact individuals and society, both positively and negatively. The DL models utilizing massive computing power and enormous datasets have significantly outperformed prior historical benchmarks on increasingly difficult, well-defined research tasks across technology domains such as computer vision, natural language processing, signal processing, and human-computer interactions. However, the Black-Box nature of DL models and their over-reliance on massive amounts of data condensed into labels and dense representations poses challenges for interpretability and explainability of the system. Furthermore, DLs have not yet been proven in their ability to …

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A Pattern For Modeling Causal Relations Between Events, Cogan Shimizu, Rui Zhu, Gengchen Mai, Mark Schildhauer, Krzysztof Janowicz, Pascal Hitzler Jan 2021

A Pattern For Modeling Causal Relations Between Events, Cogan Shimizu, Rui Zhu, Gengchen Mai, Mark Schildhauer, Krzysztof Janowicz, Pascal Hitzler

Computer Science and Engineering Faculty Publications

Space and time are useful nexuses for integrating data. For instance, events affect the places in which they occur and the people that participate in them. By capturing the effects that they may have on a place, coupled with authoritative sources on possible causality between types of events, we can model causal relations between events. In this paper we present an ontology design pattern for modeling the causal relations between events, discuss the primary conceptual components, how they may be instantiated, and present overarching examples related to the domain of disaster risk management.

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Analysis Of Classifier Weaknesses Based On Patterns And Corrective Methods, Nicholas Skapura Jan 2021

Analysis Of Classifier Weaknesses Based On Patterns And Corrective Methods, Nicholas Skapura

Browse all Theses and Dissertations

Classification is an important branch of machine learning that impacts many areas of modern life. Many classification algorithms (classifiers for short) have been developed. They have highly different levels of sophistication and classification accuracy. Classification problems often have highly different levels of hardness and complexity. Practitioners of classification modeling need better understanding of those algorithms in order to select the optimal algorithm for given classification problems. Researchers of classification need new insight on how given classifiers are weak and how they can be improved by correcting their classification errors. This dissertation introduces new tools and concepts to analyze classifier weakness …

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An Assessment Of The Impacts Of Social Media Inputs And Court Case Information On Mitigating Insider Threats, Robert Jones Jan 2021

An Assessment Of The Impacts Of Social Media Inputs And Court Case Information On Mitigating Insider Threats, Robert Jones

CCAC Theses and Dissertations

The insider threat is a global problem that impacts organizations and produces a gamut of undesired outcomes. Businesses often experience lost revenue and stolen trade secrets, which can leave a tarnished reputation. Insider threats can also cause harm to individuals and national security. Past efforts have not mitigated the problem in its entirety. Documented instances of insider threats are as recent as March 2020. Many researchers have focused on monitoring technologies and relying on human monitoring in a reactive posture. An ideal solution would scrutinize an individual’s character and ascertain whether unique traits associated with actors of insider threats are …

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Orientation And Social Influences Matter: Revisiting Neutralization Tendencies In Information Systems Security Violation, Frank Curtis King Jan 2021

Orientation And Social Influences Matter: Revisiting Neutralization Tendencies In Information Systems Security Violation, Frank Curtis King

CCAC Theses and Dissertations

It is estimated that over half of all information systems security breaches are due directly or indirectly to the poor security practices of an organization’s employees. Previous research has shown neutralization techniques as having influence on the intent to violate information security policy. In this study, we proposed an expansion of the neutralization model by including the effects of business and ethical orientation of individuals on their tendencies to neutralize and compromise with information security policy. Additionally, constructs from social influences and pressures have been integrated into this model to measure the impact on the intent to violate information security …

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Investigation Of Ant Colony Optimization Implementation Strategies For Low-Memory Operating Environments, Douglas Hale Jan 2021

Investigation Of Ant Colony Optimization Implementation Strategies For Low-Memory Operating Environments, Douglas Hale

CCAC Theses and Dissertations

In search guided by meta-heuristics, a fundamental tradeoff exists between exploitation of good solutions (intensification) and exploration of the solution space for better solutions (diversification). Over-exploitation can limit the search to suboptimal solutions while over-exploration can reduce the efficiency of the overall search. Ant Colony Optimization (ACO) is a well-known meta-heuristic inspired by biological ants for solving NP-hard combinatorial search problems like the Traveling Salesman Problem (TSP). In nature, biological ant colonies navigate to find efficient paths around complex obstacles by depositing and following simple chemicals called pheromones. ACO algorithms model this behavior by implementing sets of artificial ants which …

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A Framework For Artificial Intelligence Applications In The Healthcare Revenue Management Cycle, Leonard J. Pounds Jan 2021

A Framework For Artificial Intelligence Applications In The Healthcare Revenue Management Cycle, Leonard J. Pounds

CCAC Theses and Dissertations

There is a lack of understanding of specific risks and benefits associated with AI/RPA implementations in healthcare revenue cycle settings. Healthcare companies are confronted with stricter regulations and billing requirements, underpayments, and more significant delays in receiving payments. Despite the continued interest of practitioners, revenue cycle management has not received much attention in research. Revenue cycle management is defined as the process of identifying, collecting, and managing the practice’s revenue from payers based on the services provided.This dissertation provided contributions to both areas, as mentioned above. To accomplish this, a semi-structured interview was distributed to healthcare executives. The semi-structured interview …

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Discrete Mathematical Structures, Tugce Ozdemir Jan 2021

Discrete Mathematical Structures, Tugce Ozdemir

Open Educational Resources

No abstract provided.

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Computational Study Of Target Gene Interactions - Enhancers And Micrornas, Amlan Talukder Jan 2021

Computational Study Of Target Gene Interactions - Enhancers And Micrornas, Amlan Talukder

Electronic Theses and Dissertations, 2020-2023

Gene expression is an essential mechanism for physical and mental development of human. Aberrant regulation of gene expression creates abnormality in human body than can lead to complicated diseases. Gene expression can be regulated at any stage from the chromatin unfolding stage to post-translation stage of protein. In this study, we focused on two important factors of gene expression regulation that participate in the gene expression process at the transcription and the post-transcriptional stages; enhancer-promoter interactions and miRNA-mRNA interactions. The enhancer-promoter interactions are difficult to detect due to the large distance between the enhancer and promoter region and cell-specific activity …

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Evaluating Augmented Reality Tools For Physics Education, Corey Pittman Jan 2021

Evaluating Augmented Reality Tools For Physics Education, Corey Pittman

Electronic Theses and Dissertations, 2020-2023

While we are in the midst of a renaissance of interest in augmented reality (AR), there remain a small number of application domains that have seen significant development. One domain that often benefits from additional visualization capabilities is education, specifically physics and other sciences. This paper summarizes interviews with secondary school educators about their experience with AR and their most desired features. Three prototypes were created which were used to collect usability information from students and educators about their preferences for AR applications in their physics courses. Additionally, we introduce the concept of Environmental Integration, a novel method of defining …

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Arnold Transformations As Applied To Data Encryption, Haley N. Anderson Jan 2021

Arnold Transformations As Applied To Data Encryption, Haley N. Anderson

College of Graduate Studies: Theses & Dissertations

As our world becomes increasingly digital, data security becomes key. Data must be encrypted such that it can be easily encrypted only by the intended recipient. Arnold Transformations are a useful tool in this because of its unpredictable periodicity. Our goal is to outline a method for choosing an Arnold Transformation that is both secure and easy to implement. We find the necessary and sufficient condition that a key matrix has periodicity. The chosen key matrix has a random structure, and it has a periodicity that is sufficiently high. We apply this method to several image and data string examples …

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การผสานการวิเคราะห์เชิงเทคนิคและแบบจำลองการเรียนรู้เชิงลึกสำหรับการซื้อขายน้ำมันดิบ, วิศรุต เลิศทวีเดช Jan 2021

การผสานการวิเคราะห์เชิงเทคนิคและแบบจำลองการเรียนรู้เชิงลึกสำหรับการซื้อขายน้ำมันดิบ, วิศรุต เลิศทวีเดช

Chulalongkorn University Theses and Dissertations (Chula ETD)

น้ำมันดิบเป็นสินค้าอุปโภคที่มีความสำคัญในโลก เพราะน้ำมันดิบถือเป็นแหล่งพลังงานหลักของโลก ราคาของน้ำมันดิบนั้นมีส่วนเกี่ยวข้องในหลาย ๆ อุตสาหกรรม เช่น การขนส่ง, การผลิตพลังงานไฟฟ้า และอุตสาหกรรมปิโตรเคมี ดังนั้นการคาดการณ์ราคาน้ำมันดิบจึงมีความสำคัญสำหรับหลายภาคส่วน แต่ก็เป็นเรื่องที่ท้าทายมากเช่นกัน เนื่องจากราคาน้ำมันดิบมีความผันผวนสูง มีหลานงานวิจัยจำนวนมากที่เสนอการใช้การเรียนรู้ของเครื่องเพื่อทำนายราคาน้ำมัน โดยงานวิจัยนี้ได้นำเสนอเทคนิคการใช้โครงข่ายประสาทเทียมแบบผสานกันระหว่างโครงข่ายประสาทเทียมคอนโวลูชัน (Convolutional neural networks - CNN) และ หน่วยความจำระยะสั้นแบบยาว (Long short-term memory - LSTM) เพื่อใช้ทำนายแนวโน้มราคาน้ำมันและส่งสัญญาณการซื้อขายน้ำมันให้ดียิ่งขึ้นเมื่อเทียบกับกลยุทธ์การซื้อขายน้ำมันแบบดั้งเดิม โดยหลักการของแบบจำลองคือ CNN สามารถตรวจจับรูปแบบในตำแหน่งต่าง ๆ ของข้อมูล Time Series ได้ ในขณะที่ LSTM สามารถใช้รักษาความจำทั้งระยะสั้นและระยะยาวสำหรับข้อมูล Time Series ได้ การผสานคุณสมบัติเหล่านี้จึงเพิ่มความสามารถให้แบบจำลองได้ จากการศึกษานี้พบว่าการผสานกันของ CNN และ LSTM สามารถเพิ่มความสามารถในการทำกำไรจากการซื้อขายน้ำมันดิบได้ในระยะยาว

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Spectral And Latent Representation Distortion For Tts Evaluation, Thananchai Kongthaworn Jan 2021

Spectral And Latent Representation Distortion For Tts Evaluation, Thananchai Kongthaworn

Chulalongkorn University Theses and Dissertations (Chula ETD)

One of the main problems in the development of text-to-speech (TTS) systems is its reliance on subjective measures, typically the Mean Opinion Score (MOS). MOS requires a large number of people to reliably rate each utterance, making the development process slow and expensive. Recent research on speech quality assessment tends to focus on training models to estimate MOS, which requires a large number of training data, something that might not be available in low-resource languages. We propose an objective assessment metric based on the DTW distance using the spectrogram and the high-level features from an Automatic Speech Recognition (ASR) model …

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The Role Of Software Engineering In Bioinformatics, Brendan Sean Lawlor Jan 2021

The Role Of Software Engineering In Bioinformatics, Brendan Sean Lawlor

Theses

This thesis proposes that by applying state-of-the-art software engineering tools, techniques and frameworks to currently recognised challenges in bioinformatics, improved outcomes can be attained in that field. It begins by decomposing software engineering into two categories, namely process and architecture, and choosing two key challenges in the practice of bioinformatics: reproducibility and scalability. The body of the thesis is an exploration of the intersection between these two software engineering categories and these two bioinformatics challenges. The question is asked: Can best practices in professional software engineering be applied to address key issues in the bioinformatics domain, creating positive outcomes? And …

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Zone Path Construction (Zac) Based Approaches For Effective Real-Time Ridesharing, Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet Jan 2021

Zone Path Construction (Zac) Based Approaches For Effective Real-Time Ridesharing, Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet

Research Collection School Of Computing and Information Systems

Real-time ridesharing systems such as UberPool, Lyft Line and GrabShare have become hugely popular as they reduce the costs for customers, improve per trip revenue for drivers and reduce traffic on the roads by grouping customers with similar itineraries. The key challenge in these systems is to group the “right” requests to travel together in the “right” available vehicles in real-time, so that the objective (e.g., requests served, revenue or delay) is optimized. This challenge has been addressed in existing work by: (i) generating as many relevant feasible combinations of requests (with respect to the available delay for customers) as …

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