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Articles 23341 - 23370 of 63476

Full-Text Articles in Computer Sciences

Dependency Mapping Software For Jira, Project Management Tool, Bentley Lager May 2020

Dependency Mapping Software For Jira, Project Management Tool, Bentley Lager

Computer Science and Computer Engineering Undergraduate Honors Theses

Efficiently managing a software development project is extremely important in industry and is often overlooked by the software developers on a project. Pieces of development work are identified by developers and are then handed off to project managers, who are left to organize this information. Project managers must organize this to set expectations for the client, and ensure the project stays on track and on budget. The main block in this process are dependency chains between tasks. Dependency chains can cause a project to take much longer than anticipated or result in the under utilization of developers on a project. …

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Understanding Personal Data In The World Of Social Media, Nicholas Scott Rodgers May 2020

Understanding Personal Data In The World Of Social Media, Nicholas Scott Rodgers

Undergraduate Honors Capstone Projects

Personal data is behind many of the online interactions that people have through social media and other online sites and services. This data allows sites to understand their users, which in turn allows them to provide better content for their users. This data is also used to determine user interests, which these online services use to target more relevant advertising to their users, and share the information that they collect about their users with third parties. It is only recently that this personal data is being regulated by lawmakers, the businesses running these sites are held accountable for managing the …

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The Two Types Of Society: Computationally Revealing Recurrent Social Formations And Their Evolutionary Trajectories, Lux Miranda May 2020

The Two Types Of Society: Computationally Revealing Recurrent Social Formations And Their Evolutionary Trajectories, Lux Miranda

Undergraduate Honors Capstone Projects

Comparative social science has a long history of attempts to classify societies and cultures in terms of shared characteristics. However, only recently has it become feasible to conduct quantitative analysis of large historical datasets to mathematically approach the study of social complexity and classify shared societal characteristics. Such methods have the potential to identify recurrent social formations in human societies and contribute to social evolutionary theory. However, in order to achieve this potential, repeated studies are needed to assess the robustness of results to changing methods and data sets. Using an improved derivative of the Seshat: Global History Databank, we …

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High Dimensional Event Exploration Over Multiple Simulations, Steven Deron Scott May 2020

High Dimensional Event Exploration Over Multiple Simulations, Steven Deron Scott

Undergraduate Honors Capstone Projects

In this project, we introduce a visualization technique to analyze event simulation data. In particular, we allow the user to discover families of events based on the topological evolution of discrete events across simulations. Discovering how events behave across runs of a simulation has applications in financial market analysis, military simulations, physical mechanics, and other settings. Our approach is to use established methods to produce a linearized tour through parameter space of arbitrary dimension and visualize events of interest in two dimensions, where the first dimension is the tour ordering and the second dimension is usually time. This paper presents …

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A Machine Learning Method For Predicting Liver Transplant Survival Outcomes, Brandon C. Revels May 2020

A Machine Learning Method For Predicting Liver Transplant Survival Outcomes, Brandon C. Revels

Honors Theses

For years, doctors have utilized the Model for End-stage Liver Disease (MELD) score to aid in the allocation of organs for liver transplants (LT). A major issue with using the MELD score to allocate organs for transplantation is that the MELD score does not accurately predict post-transplant survival. This research project aims to investigate the use of machine learning (ML) methods to predict LT survival using the newer Scientific Registry of Transplant Recipients (SRTR) dataset. For this project, death and nonfatal graft failure were treated equally as both cases result in a loss of a donated organ. The ML algorithms …

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Predicting The Impact Of Weather On Rural Travel Times Using Now-Cast Weather Forecast Data, Manish Meshram May 2020

Predicting The Impact Of Weather On Rural Travel Times Using Now-Cast Weather Forecast Data, Manish Meshram

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

In the states which record extreme weather conditions and high snow in winters, the travel time to drive between cities can get highly affected due to these bad weather conditions. The present solutions to tackle this problem are largely flow or time related and do not take weather conditions into account while making the predictions about travel time. Also these solutions can mostly be used for real time travel and not the future travel. In addition to that, the studies that have been done in this space are mostly for urban travel times but most parts of the interstate highways …

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Teaching Distributed Application Design Using Drones, Cameron Frandsen May 2020

Teaching Distributed Application Design Using Drones, Cameron Frandsen

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

This thesis provides a new platform that instructors can use to create a learning environment for students to learn how to design and implement distributed applications. One possible way to use the platform uses milestones to test the student’s understanding of different concepts. Milestones contain pretests that students can use to test their code. Each milestone focuses on a different concept, including interprocess communication, reliability, and security. A monitor process can be created by the students to provide away for the instructor to see how well the students are learning the concepts by using a monitor process. The platform gives …

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Using Imagery To Improve Program Quality In Computer Programming, Joseph S. Ditton May 2020

Using Imagery To Improve Program Quality In Computer Programming, Joseph S. Ditton

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

A common practice in sports is to review film footage of a game. This is done in the hope that individuals on the team or the a team as a whole might learning something about technique, form, process, or strategy that they either did well on or need to improve on. We believe that the benefits of doing this could extend to computer science, and more specifically, the process of writing a computer program. This has never been done in the past, as such this research is exploratory in nature. A new tool called Phanon can record someone writing a …

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Retention Of Women In Computer Science: Why Women Persist In Their Computer Science Majors, Katarina Pantic May 2020

Retention Of Women In Computer Science: Why Women Persist In Their Computer Science Majors, Katarina Pantic

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Retention of women through graduation in Computer Science (CS) majors is one of the biggest challenges for CS education. Most research in this area focuses on factors influencing attrition rather than why and how women remain committed. The goal of this research study is to understand retention from the perspective of women who persisted in their CS major. Using the theoretical lens of legitimate peripheral participation in communities of practice, I designed and conducted a study that involved focus groups, interviews, journey maps, and experience sampling methods. I found that retention of women in this study was influenced by four …

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Applications Of Digital Remote Sensing To Quantify Glacier Change In Glacier And Mount Rainier National Parks, Brianna Clark May 2020

Applications Of Digital Remote Sensing To Quantify Glacier Change In Glacier And Mount Rainier National Parks, Brianna Clark

Electronic Theses and Dissertations

Digital remote sensing and geographic information systems were employed in performing area and volume calculations on glacial landscapes. Characteristics of glaciers from two geographic regions, the Intermountain Region (between the Rocky Mountain and Cascade Ranges) and the Pacific Northwest, were estimated for the years 1985, 2000, and 2015. Glacier National Park was studied for the Intermountain Region whereas Mount Rainier National Park was representative of the glaciers in the Pacific Northwest. Within the thirty year period of the study, the glaciers in Glacier National Park decreased in area by 27.5 percent while those on Mount Rainier only decreased by 5.7 …

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Visualization Of Musical Instruments Through Midi Interface, John Jaminet May 2020

Visualization Of Musical Instruments Through Midi Interface, John Jaminet

Undergraduate Theses and Capstone Projects

We have created a Music Visualization system that controls an LED strip by parsing MIDI signals that are sent by a musical instrument. This is achieved through a program that parses the MIDI note signals into three-byte RGB signals which are then transferred over WIFI to four Arduino boards that control the LEDs. The system provides a musician the ability to add a dynamic light display that responds to the music in real-time. The system utilizes Windows Presentation Foundation because of its event handling and GUI capabilities. The board we are using is the Arduino MKR 1010 WIFI board as …

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How User-Friendly Operating Systems And Interfaces Make Technology Harder For Everyone, Cameron Short May 2020

How User-Friendly Operating Systems And Interfaces Make Technology Harder For Everyone, Cameron Short

Undergraduate Theses and Capstone Projects

This thesis explores both deprecated and current Operating Systems to understand the changes of user interfaces. By comparing older and more flawed Operating Systems interfaces, I intend to demonstrate how user-friendliness has come to the forefront of OS design. However, by building more user-friendly interfaces, the functionality and power of the older designs, while often misused, has been lost. Systems design restricts user access to such functionality because it might damage the system. It is a sensible precaution for users unaware of the effects of certain actions. However, this thesis will argue that for trained and educated users of the …

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Secure And Efficient Models For Retrieving Data From Encrypted Databases In Cloud, Sultan Ahmed A Almakdi May 2020

Secure And Efficient Models For Retrieving Data From Encrypted Databases In Cloud, Sultan Ahmed A Almakdi

Graduate Theses and Dissertations

Recently, database users have begun to use cloud database services to outsource their databases. The reason for this is the high computation speed and the huge storage capacity that cloud owners provide at low prices. However, despite the attractiveness of the cloud computing environment to database users, privacy issues remain a cause for concern for database owners since data access is out of their control. Encryption is the only way of assuaging users’ fears surrounding data privacy, but executing Structured Query Language (SQL) queries over encrypted data is a challenging task, especially if the data are encrypted by a randomized …

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Memlock: Memory Usage Guided Fuzzing, Cheng Wen, Haijun Wang, Yuekang Li, Shengchao Qin, Yang Liu, Zhiwu Xu, Hongxu Chen, Xiaofei Xie, Geguang Pu, Ting Liu May 2020

Memlock: Memory Usage Guided Fuzzing, Cheng Wen, Haijun Wang, Yuekang Li, Shengchao Qin, Yang Liu, Zhiwu Xu, Hongxu Chen, Xiaofei Xie, Geguang Pu, Ting Liu

Research Collection School Of Computing and Information Systems

Uncontrolled memory consumption is a kind of critical software security weaknesses. It can also become a security-critical vulnerability when attackers can take control of the input to consume a large amount of memory and launch a Denial-of-Service attack. However, detecting such vulnerability is challenging, as the state-of-the-art fuzzing techniques focus on the code coverage but not memory consumption. To this end, we propose a memory usage guided fuzzing technique, named MemLock, to generate the excessive memory consumption inputs and trigger uncontrolled memory consumption bugs. The fuzzing process is guided with memory consumption information so that our approach is general and …

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Rankbooster: Visual Analysis Of Ranking Predictions, Abishek Puri, Bon Kyung Ku, Yong Wang, Huamin Qu May 2020

Rankbooster: Visual Analysis Of Ranking Predictions, Abishek Puri, Bon Kyung Ku, Yong Wang, Huamin Qu

Research Collection School Of Computing and Information Systems

Ranking is a natural and ubiquitous way to facilitate decision-making in various applications. However, different rankings are often used for the same set of entities, with each ranking method placing emphasis on different factors. These factors can also be multi-dimensional in nature, compounding the problem. This complexity can make it challenging for an entity which is being ranked to understand what they can do to improve their rankings, and to analyze the effect of changes in various factors to their overall rank. In this paper, we present RankBooster, a novel visual analytics system to help users conveniently investigate ranking predictions. …

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An Fpga-Based Hardware Accelerator For The Digital Image Correlation Engine, Keaten Stokke May 2020

An Fpga-Based Hardware Accelerator For The Digital Image Correlation Engine, Keaten Stokke

Graduate Theses and Dissertations

The work presented in this thesis was aimed at the development of a hardware accelerator for the Digital Image Correlation engine (DICe) and compare two methods of data access, USB and Ethernet. The original DICe software package was created by Sandia National Laboratories and is written in C++. The software runs on any typical workstation PC and performs image correlation on available frame data produced by a camera. When DICe is introduced to a high volume of frames, the correlation time is on the order of days. The time to process and analyze data with DICe becomes a concern when …

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Dynamic Fraud Detection Via Sequential Modeling, Panpan Zheng May 2020

Dynamic Fraud Detection Via Sequential Modeling, Panpan Zheng

Graduate Theses and Dissertations

The impacts of information revolution are omnipresent from life to work. The web services have signicantly changed our living styles in daily life, such as Facebook for communication and Wikipedia for knowledge acquirement. Besides, varieties of information systems, such as data management system and management information system, make us work more eciently. However, it is usually a double-edged sword. With the popularity of web services, relevant security issues are arising, such as fake news on Facebook and vandalism on Wikipedia, which denitely impose severe security threats to OSNs and their legitimate participants. Likewise, oce automation incurs another challenging security issue, …

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Hierarchical Multiagent Reinforcement Learning For Maritime Traffic Management, Arambam James Singh, Akshat Kumar, Hoong Chuin Lau May 2020

Hierarchical Multiagent Reinforcement Learning For Maritime Traffic Management, Arambam James Singh, Akshat Kumar, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Increasing global maritime traffic coupled with rapid digitization and automation in shipping mandate developing next generation maritime traffic management systems to mitigate congestion, increase safety of navigation, and avoid collisions in busy and geographically constrained ports (such as Singapore's). To achieve these objectives, we model the maritime traffic as a large multiagent system with individual vessels as agents, and VTS (Vessel Traffic Service) authority as a regulatory agent. We develop a hierarchical reinforcement learning approach where vessels first select a high level action based on the underlying traffic flow, and then select the low level action that determines their future …

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Symbolic Verification Of Message Passing Interface Programs, Hengbiao Yu, Zhenbang Chen, Xianjin Fu, Ji Wang, Zhendong Su, Jun Sun, Chun Huang, Wei Dong May 2020

Symbolic Verification Of Message Passing Interface Programs, Hengbiao Yu, Zhenbang Chen, Xianjin Fu, Ji Wang, Zhendong Su, Jun Sun, Chun Huang, Wei Dong

Research Collection School Of Computing and Information Systems

Message passing is the standard paradigm of programming in high-performance computing. However, verifying Message Passing Interface (MPI) programs is challenging, due to the complex program features (such as non-determinism and non-blocking operations). In this work, we present MPI symbolic verifier (MPI-SV), the first symbolic execution based tool for automatically verifying MPI programs with non-blocking operations. MPI-SV combines symbolic execution and model checking in a synergistic way to tackle the challenges in MPI program verification. The synergy improves the scalability and enlarges the scope of verifiable properties. We have implemented MPI-SV and evaluated it with 111 real-world MPI verification tasks. The …

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Pmkt: Privacy-Preserving Multi-Party Knowledge Transfer For Financial Market Forecasting, Zhuoran Ma, Jianfeng Ma, Yinbin Miao, Kim-Kwang Raymond Choo, Ximeng Liu, Xiangyu Wang, Tengfei Yang May 2020

Pmkt: Privacy-Preserving Multi-Party Knowledge Transfer For Financial Market Forecasting, Zhuoran Ma, Jianfeng Ma, Yinbin Miao, Kim-Kwang Raymond Choo, Ximeng Liu, Xiangyu Wang, Tengfei Yang

Research Collection School Of Computing and Information Systems

While decision-making task is critical in knowledge transfer, particularly from multi-source domains, existing knowledge transfer approaches are not generally designed to be privacy preserving. This has potential legal and financial implications, particularly in sensitive applications such as financial market forecasting. Therefore, in this paper, we propose a Privacy-preserving Multi-party Knowledge Transfer system (PMKT), based on decision trees, for financial market forecasting. Specifically, in PMKT, we leverage a cryptographic-based model sharing technique to securely outsource knowledge reflected in decision trees of multiple parties, and design a secure computation mechanism to facilitate privacy-preserving knowledge transfer. An encrypted user-submitted request from the target …

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Who And When To Screen: Multi-Round Active Screening For Network Recurrent Infectious Diseases Under Uncertainty, Han-Ching Ou, Arunesh Sinha, Sze-Chuan Suen, Andrew Perrault, Alpan Raval, Milind Tambe May 2020

Who And When To Screen: Multi-Round Active Screening For Network Recurrent Infectious Diseases Under Uncertainty, Han-Ching Ou, Arunesh Sinha, Sze-Chuan Suen, Andrew Perrault, Alpan Raval, Milind Tambe

Research Collection School Of Computing and Information Systems

Controlling recurrent infectious diseases is a vital yet complicated problem in global health. During the long period of time from patients becoming infected to finally seeking treatment, their close contacts are exposed and vulnerable to the disease they carry. Active screening (or case finding) methods seek to actively discover undiagnosed cases by screening contacts of known infected people to reduce the spread of the disease. Existing practice of active screening methods often screen all contacts of an infected person, requiring a large budget. In cooperation with a research institute in India, we develop a model of the active screening problem …

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A Fully Distributed Hierarchical Attribute-Based Encryption Scheme, Ali Mohammad, Javad Mohajeri, Ximeng Liu, Ximeng Liu May 2020

A Fully Distributed Hierarchical Attribute-Based Encryption Scheme, Ali Mohammad, Javad Mohajeri, Ximeng Liu, Ximeng Liu

Research Collection School Of Computing and Information Systems

With the development of cloud computing, many enterprises have been interested in outsourcing their data to cloud servers to decrease IT costs and rise capabilities of provided services. To afford confidentiality and fine-grained data access control, attribute-based encryption (ABE) was proposed and used in several cloud storage systems. However, scalability and flexibility in key delegation and user revocation mechanisms are primary issues in ABE systems. In this paper, we introduce the concept of a fully distributed revocable ciphertext-policy hierarchical ABE (FDR-CP-HABE) and design the first FDR-CP-HABE scheme. Our scheme offers a high level of flexibility and scalability in the key …

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Jplink: On Linking Jobs To Vocational Interest Types, Amila Silva, Pei Chi Lo, Ee-Peng Lim May 2020

Jplink: On Linking Jobs To Vocational Interest Types, Amila Silva, Pei Chi Lo, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Linking job seekers with relevant jobs requires matching based on not only skills, but also personality types. Although the Holland Code also known as RIASEC has frequently been used to group people by their suitability for six different categories of occupations, the RIASEC category labels of individual jobs are often not found in job posts. This is attributed to significant manual efforts required for assigning job posts with RIASEC labels. To cope with assigning massive number of jobs with RIASEC labels, we propose JPLink, a machine learning approach using the text content in job titles and job descriptions. JPLink exploits …

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Values Of Artificial Intelligence In Marketing, Yingrui Xi, Keng Siau May 2020

Values Of Artificial Intelligence In Marketing, Yingrui Xi, Keng Siau

Research Collection School Of Computing and Information Systems

Artificial Intelligence (AI) is causing radical changes in marketing and emerging as a competent assistant supporting all areas of the marketing field. The influences and impacts AI has created in various marketing segments have aroused much interest among marketing professionals and academic scholars. Comprehensive and systematic studies on the values of AI in marketing, however, are still lacking and the existing literature fragmented. This research provides a comprehensive review of the existing literature in the relevant fields as well as a series of systematic interviews using the Value-Focused Thinking approach to understand the values of AI in marketing. This research …

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A Data-Analytics Approach For Risk Evaluation In Peer-To-Peer Lending Platforms, Feng He, Yuelei Li, Tiecheng Xu, Libo Yin, Wei Zhang, Xiaotao Zhang May 2020

A Data-Analytics Approach For Risk Evaluation In Peer-To-Peer Lending Platforms, Feng He, Yuelei Li, Tiecheng Xu, Libo Yin, Wei Zhang, Xiaotao Zhang

Research Collection School Of Accountancy

The goal of this article is to investigate the roles of individual behavior characteristics and Internet finance industry risk in the light of bank run theory for P2P. We know that risk evaluation is clearly important for peer-to-peer (P2P) lending platforms in China, as during the last two years, the industry has experienced thousands of platform crashes. Traditional approaches to evaluate enterprise risk are increasingly ineffective in this industry, due to the difficulty of assessing the real information. In addition, the Internet business model makes it possible to record new kinds of information. By applying a data-driven analytics method, we …

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Partial Discharge Classification For Xlpe Cable Joints Using K Nearest Neighbors Algorithm, Mohd Salleh Muhammad Shairazi May 2020

Partial Discharge Classification For Xlpe Cable Joints Using K Nearest Neighbors Algorithm, Mohd Salleh Muhammad Shairazi

Student Works (2020-2029)

Due to excellent mechanical and electrical properties, cross-linked polyethylene (XLPE) cables are commonly used in the power industry. However, cable joints are the weakest part of XLPE cables and are susceptible to insulation failures. Cable joint insulation breakup can cause large losses for power companies. It is therefore necessary to evaluate the consistency of the insulation for early detection of insulation failure. It is known that there is a link between the partial discharge (PD) and the quality of the insulation. PD analysis is an important tool for assessing the quality of insulation in cable joints. In this study, XLPE …

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Classification Of Dividend News Based On The Movement Of The Share Market Prices Of Public Listed Companies In Bursa Malaysia, Vijaya Kumar Shubana May 2020

Classification Of Dividend News Based On The Movement Of The Share Market Prices Of Public Listed Companies In Bursa Malaysia, Vijaya Kumar Shubana

Student Works (2020-2029)

Stock market is naturally complex and plays a major role in towards the nation’s growth. However, the performance of a company in stock market varies due to many influences but not limited to economics, political and financial related news. This study attempts to classify the share market dividend news announcement in Bursa Malaysia based on the pattern of share market price. Samples including five hundred (500) observations of dividend news from forty-seven (47) listed companies in Bursa Malaysia during the period of 2000 to 2018 are used in this study. There are three (3) main objectives in this study which …

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Non-Autoregressive Dialog State Tracking, Hung Le, Richard Socher, Steven C. H. Hoi May 2020

Non-Autoregressive Dialog State Tracking, Hung Le, Richard Socher, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Recent efforts in Dialogue State Tracking (DST) for task-oriented dialogues have progressed toward open-vocabulary or generation-based approaches where the models can generate slot value candidates from the dialogue history itself. These approaches have shown good performance gain, especially in complicated dialogue domains with dynamic slot values. However, they fall short in two aspects: (1) they do not allow models to explicitly learn signals across domains and slots to detect potential dependencies among (domain, slot) pairs; and (2) existing models follow auto-regressive approaches which incur high time cost when the dialogue evolves over multiple domains and multiple turns. In this paper, …

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A Lightweight Privacy-Preserving Cnn Feature Extraction Framework For Mobile Sensing, Kai Huang, Ximeng Liu, Shaojing Fu, Deke Guo, Ming Xu May 2020

A Lightweight Privacy-Preserving Cnn Feature Extraction Framework For Mobile Sensing, Kai Huang, Ximeng Liu, Shaojing Fu, Deke Guo, Ming Xu

Research Collection School Of Computing and Information Systems

The proliferation of various mobile devices equipped with cameras results in an exponential growth of the amount of images. Recent advances in the deep learning with convolutional neural networks (CNN) have made CNN feature extraction become an effective way to process these images. However, it is still a challenging task to deploy the CNN model on the mobile sensors, which are typically resource-constrained in terms of the storage space, the computing capacity, and the battery life. Although cloud computing has become a popular solution, data security and response latency are always the key issues. Therefore, in this paper, we propose …

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“Trust Me, I Have A Ph.D.”: A Propensity Score Analysis On The Halo Effect Of Disclosing One's Offline Social Status In Online Communities, Kunwoo Park, Haewoon Kwak, Hyunho Song, Meeyoung. Cha May 2020

“Trust Me, I Have A Ph.D.”: A Propensity Score Analysis On The Halo Effect Of Disclosing One's Offline Social Status In Online Communities, Kunwoo Park, Haewoon Kwak, Hyunho Song, Meeyoung. Cha

Research Collection School Of Computing and Information Systems

Online communities adopt various reputation schemes to measure content quality. This study analyzes the effect of a new reputation scheme that exposes one's offline social status, such as an education degree, within an online community. We study two Reddit communities that adopted this scheme, whereby posts include tags identifying education status referred to as flairs, and we examine how the “transferred” social status affects the interactions among the users. We computed propensity scores to test whether flairs give ad-hoc authority to the adopters while minimizing the effects of confounding variables such as topics of content. The results show that exposing …

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