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Articles 2941 - 2970 of 4524
Full-Text Articles in Computer Sciences
Machine Learning For Prediction Of Trabecular And Cortical Bone Mineral Density, Partha Chudal
Machine Learning For Prediction Of Trabecular And Cortical Bone Mineral Density, Partha Chudal
UNLV Theses, Dissertations, Professional Papers, and Capstones
Osteoporosis becomes very common problem for people after a certain age, which results in fragility fractures without any previous symptoms. One of the primary predictors of osteoporosis is bone mineral density (BMD). BMD is the mineral content of bone, at the optimal levels, that makes the bone strong enough to bear the regular load and elastic enough to handle the irregular twisting load. Two of the major parts of the bone that help to acquire such property are trabecular and cortical bone. This thesis focuses on predicting the BMDs of trabecular and cortical bone for men. For this purpose we …
Improving Energy-Efficiency Through Smart Data Placement In Hadoop Clusters, Ahmed Mostafa
Improving Energy-Efficiency Through Smart Data Placement In Hadoop Clusters, Ahmed Mostafa
Theses and Dissertations
Hadoop, a pioneering open source framework, has revolutionized the big data world because of its ability to process vast amounts of unstructured and semi-structured data. This ability makes Hadoop the ‘go-to’ technology for many industries that generate big data, thus it also aids in being cost effective, unlike other legacy systems. Hadoop MapReduce is used in large scale data parallel applications to process massive amounts of data across a cluster and is used for scheduling, processing, and executing jobs. Basically, MapReduce is the right hand of Hadoop, as its library is needed to process these large data sets. In this …
Toward The Automatic Classification Of Self-Affirmed Refactoring, Mohamed Wiem Mkaouer, Eman Abdullah Alomar, Ali Ouni
Toward The Automatic Classification Of Self-Affirmed Refactoring, Mohamed Wiem Mkaouer, Eman Abdullah Alomar, Ali Ouni
Articles
The concept of Self-Affirmed Refactoring (SAR) was introduced to explore how developers document their refactoring activities in commit messages, i.e., developers explicit documentation of refactoring operations intentionally introduced during a code change. In our previous study, we have manually identified refactoring patterns and defined three main common quality improvement categories including internal quality attributes, external quality attributes, and code smells, by only considering refactoring-related commits. However, this approach heavily depends on the manual inspection of commit messages. In this paper, we propose a two-step approach to first identify whether a commit describes developer-related refactoring events, then to classify it according …
How Do Developers Refactor Code To Improve Code Reusability?, Eman Abdullah Alomar, Philip T. Rodriguez, Jordan Bowman, Tianjia Wang, Benjamin Adepoju, Kevin Lopez, Christian D. Newman, Ali Ouni, Mohamed Wiem Mkaouer
How Do Developers Refactor Code To Improve Code Reusability?, Eman Abdullah Alomar, Philip T. Rodriguez, Jordan Bowman, Tianjia Wang, Benjamin Adepoju, Kevin Lopez, Christian D. Newman, Ali Ouni, Mohamed Wiem Mkaouer
Articles
. Refactoring is the de-facto practice to optimize software health. While there has been several studies proposing refactoring strategies to optimize software design through applying design patterns and removing design defects, little is known about how developers actually refactor their code to improve its reuse. Therefore, we extract, from 1,828 open source projects, a set of refactorings which were intended to improve the software reusability. We analyze the impact of reusability refactorings on state-of-the-art reusability metrics, and we compare the distribution of reusability refactoring types, with the distribution of the remaining mainstream refactorings. Overall, we found that the distribution of …
An Exploratory Study On How Software Reuse Is Discussed In Stack Overflow, Mohamed Wiem Mkaouer, Eman Abdullah Alomar, Jiaqian Liu, Ali Ouni, Christian D. Newman, Diego Barinas
An Exploratory Study On How Software Reuse Is Discussed In Stack Overflow, Mohamed Wiem Mkaouer, Eman Abdullah Alomar, Jiaqian Liu, Ali Ouni, Christian D. Newman, Diego Barinas
Articles
Software reuse is an important and crucial quality attribute in modern software engineering, where almost all software projects, open source or commercial, no matter small or ultra-large, source code reuse in one way or another. Although software reuse has experienced an increased adoption throughout the years with the exponentially growing number of available third-party libraries, frameworks and APIs, little knowledge exists to investigate what aspects of code reuse developers discuss. In this study, we look into bridging this gap by examining Stack Overflow to understand the challenges developers encounter when trying to reuse code. Using the Stack Overflow tags “code-reuse” …
How We Refactor And How We Document It? On The Use Of Supervised Machine Learning Algorithms To Classify Refactoring Documentation, Eman Abdullah Alomar, Anthony Peruma, Mohamed Wiem Mkaouer, Christian D. Newman, Marouane Kessentini, Ali Ouni
How We Refactor And How We Document It? On The Use Of Supervised Machine Learning Algorithms To Classify Refactoring Documentation, Eman Abdullah Alomar, Anthony Peruma, Mohamed Wiem Mkaouer, Christian D. Newman, Marouane Kessentini, Ali Ouni
Articles
Refactoring is the art of improving the structural design of a software system without altering its external behavior. Today, refactoring has become a well-established and disciplined software engineering practice that has attracted a significant amount of research presuming that refactoring is primarily motivated by the need to improve system structures. However, recent studies have shown that developers may incorporate refactoring strategies in other development-related activities that go beyond improving the design especially with the emerging challenges in contemporary software engineering. Unfortunately, these studies are limited to developer interviews and a reduced set of projects. To cope with the above-mentioned limitations, …
Novel Inference Methods For Generalized Linear Models Using Shrinkage Priors And Data Augmentation., Arinjita Bhattacharyya
Novel Inference Methods For Generalized Linear Models Using Shrinkage Priors And Data Augmentation., Arinjita Bhattacharyya
Electronic Theses and Dissertations
Generalized linear models have broad applications in biostatistics and sociology. In a regression setup, the main target is to find a relevant set of predictors out of a large collection of covariates. Sparsity is the assumption that only a few of these covariates in a regression setup have a meaningful correlation with an outcome variate of interest. Sparsity is incorporated by regularizing the irrelevant slopes towards zero without changing the relevant predictors and keeping the resulting inferences intact. Frequentist variable selection and sparsity are addressed by popular techniques like Lasso, Elastic Net. Bayesian penalized regression can tackle the curse of …
A Software Source Code Recommendation System For Code Reuse From Private Repositories, Md Mazharul Islam
A Software Source Code Recommendation System For Code Reuse From Private Repositories, Md Mazharul Islam
Graduate Theses/Dissertations
Motivated by the idea of reusing existing source code from previous projects within a software company, in this thesis, I present a new source code recommendation technique to help programmers find relevant implementations or sample code based on software requirement specifications. My proposed technique assists programmers to search existing code repositories using natural language query. My approach summarizes the uploaded code into sentences or phrases to match them against user queries. This version of my proposed technique extracts and analyzes the content of Python code (such as variables, functions, docstrings, and comments) to generate code summary for each function which …
Iot Tracking System Effectiveness In Enhancing Library Services, Khulud Alawaji
Iot Tracking System Effectiveness In Enhancing Library Services, Khulud Alawaji
Theses and Dissertations
The advantages that the Internet of Things (IoT) provides lead to an increase in the number of IoT solutions that integrate different fields. One of the important IoT contributions is in location-based IoT applications, which leverage the Indoor Positioning System (IPS) technology. IPS uses numerous technologies; one is the Beacon technology, which is based on a small wireless sensor device used to send signals. IPS based Beacon technology used in college libraries to increase the productivity, accuracy, safety, and efficiency of daily processes. This research proposed an IoT Beacon-based tracking system concept to be applied at Evans Library at Florida …
The Equifax Hack Revisited And Repurposed, Hal Berghel
The Equifax Hack Revisited And Repurposed, Hal Berghel
Civil and Environmental Engineering and Construction Faculty Research
Reports on the recent indictments against Chinese hackers regarding Equifax.
Development Of Fully Balanced Ssfp And Computer Vision Applications For Mri-Assisted Radiosurgery (Mars), Jeremiah Sanders
Development Of Fully Balanced Ssfp And Computer Vision Applications For Mri-Assisted Radiosurgery (Mars), Jeremiah Sanders
Dissertations and Theses (Open Access)
Prostate cancer is the second most common cancer in men and the second-leading cause of cancer death in men. Brachytherapy is a highly effective treatment option for prostate cancer, and is the most cost-effective initial treatment among all other therapeutic options for low to intermediate risk patients of prostate cancer. In low-dose-rate (LDR) brachytherapy, verifying the location of the radioactive seeds within the prostate and in relation to critical normal structures after seed implantation is essential to ensuring positive treatment outcomes.
One current gap in knowledge is how to simultaneously image the prostate, surrounding anatomy, and radioactive seeds within the …
Data Breach Consequences And Responses: A Multi-Method Investigation Of Stakeholders, Hamid Reza Nikkhah
Data Breach Consequences And Responses: A Multi-Method Investigation Of Stakeholders, Hamid Reza Nikkhah
Graduate Theses and Dissertations
The role of information in today’s economy is essential as organizations that can effectively store and leverage information about their stakeholders can gain an advantage in their markets. The extensive digitization of business information can make organizations vulnerable to data breaches. A data breach is the unauthorized access to sensitive, protected, or confidential data resulting in the compromise of information security. Data breaches affect not only the breached organization but also various related stakeholders. After a data breach, stakeholders of the breached organizations show negative behaviors, which causes the breached organizations to face financial and non-financial costs. As such, the …
Code Duplication On Stack Overflow, Sebastian Baltes, Christoph Treude
Code Duplication On Stack Overflow, Sebastian Baltes, Christoph Treude
Research Collection School Of Computing and Information Systems
Despite the unarguable importance of Stack Overflow (SO) for the daily work of many software developers and despite existing knowledge about the impact of code duplication on software maintainability, the prevalence and implications of code clones on SO have not yet received the attention they deserve. In this paper, we motivate why studies on code duplication within SO are needed and how existing studies on code reuse differ from this new research direction. We present similarities and differences between code clones in general and code clones on SO and point to open questions that need to be addressed to be …
Assistance For Target Selection In Mobile Augmented Reality, Vinod Asokan, Scott Bateman, Anthony Tang
Assistance For Target Selection In Mobile Augmented Reality, Vinod Asokan, Scott Bateman, Anthony Tang
Research Collection School Of Computing and Information Systems
Mobile augmented reality - where a mobile device is used to view and interact with virtual objects displayed in the real world - is becoming more common. Target selection is the main method of interaction in mobile AR, but is particularly difficult because targets in AR can have challenging characteristics such as being moving or occluded (by digital or real world objects). Because target selection is particularly difficult and error prone in mobile AR, we conduct a comparative study of target assistance techniques. We compared four different cursor-based selection techniques against the standard touch-to-select interaction, finding that a newly adapted …
Towards Characterizing Adversarial Defects Of Deep Learning Software From The Lens Of Uncertainty, Xiyue Zhang, Xiaofei Xie, Lei Ma, Xiaoning Du, Qiang Hu, Yang Liu, Jianjun Zhao, Meng Sun
Towards Characterizing Adversarial Defects Of Deep Learning Software From The Lens Of Uncertainty, Xiyue Zhang, Xiaofei Xie, Lei Ma, Xiaoning Du, Qiang Hu, Yang Liu, Jianjun Zhao, Meng Sun
Research Collection School Of Computing and Information Systems
Over the past decade, deep learning (DL) has been successfully applied to many industrial domain-specific tasks. However, the current state-of-the-art DL software still suffers from quality issues, which raises great concern especially in the context of safety- and security-critical scenarios. Adversarial examples (AEs) represent a typical and important type of defects needed to be urgently addressed, on which a DL software makes incorrect decisions. Such defects occur through either intentional attack or physical-world noise perceived by input sensors, potentially hindering further industry deployment. The intrinsic uncertainty nature of deep learning decisions can be a fundamental reason for its incorrect behavior. …
Use Of Eye-Tracking To Identify Psychological Indicators Of Sleepiness, Debasis Roy, Fiona Fui-Hoon Nah, Matthew Thimgan
Use Of Eye-Tracking To Identify Psychological Indicators Of Sleepiness, Debasis Roy, Fiona Fui-Hoon Nah, Matthew Thimgan
Research Collection School Of Computing and Information Systems
Sleepiness or sleep deprivation creates a serious hazard or obstacle to task execution and performance. Sleep deprivation can be life-threating (e.g., when driving or executing attention-critical tasks). We are interested to examine if eye-tracking technology can be used to assess and detect sleepiness in an online environment. In this research proposal, we will focus on examining the relationships between sleepiness and parameters involving pupil size, blinks, and saccades.
Retrofitting Embeddings For Unsupervised User Identity Linkage, Tao Zhou, Ee-Peng Lim, Roy Ka-Wei Lee, Feida Zhu, Jiuxin Cao
Retrofitting Embeddings For Unsupervised User Identity Linkage, Tao Zhou, Ee-Peng Lim, Roy Ka-Wei Lee, Feida Zhu, Jiuxin Cao
Research Collection School Of Computing and Information Systems
User Identity Linkage (UIL) is the problem of matching user identities across multiple online social networks (OSNs) which belong to the same person. The solutions to UIL problem facilitate cross-platform research on OSN users and enable many useful applications such as user profiling and recommendation. As the UIL labeled data are often lacking and costly to obtain, learning user embeddings for matching user identities using an unsupervised approach is therefore highly desired. In this paper, we propose a novel unsupervised UIL framework for enhancing existing user embedding-based UIL methods. Our proposed framework incorporates two key ideas, user-discriminative features and retrofitting …
Semantic Understanding Of Smart Contracts: Executable Operational Semantics Of Solidity, Jiao Jiao, Shuanglong Kan, Shang Wei Lin, David Sanan, Yang Liu, Jun Sun
Semantic Understanding Of Smart Contracts: Executable Operational Semantics Of Solidity, Jiao Jiao, Shuanglong Kan, Shang Wei Lin, David Sanan, Yang Liu, Jun Sun
Research Collection School Of Computing and Information Systems
Bitcoin has been a popular research topic recently. Ethereum (ETH), a second generation of cryptocurrency, extends Bitcoin's design by offering a Turing-complete programming language called Solidity to develop smart contracts. Smart contracts allow creditable execution of contracts on EVM (Ethereum Virtual Machine) without third parties. Developing correct and secure smart contracts is challenging due to the decentralized computation nature of the blockchain. Buggy smart contracts may lead to huge financial loss. Furthermore, smart contracts are very hard, if not impossible, to patch once they are deployed. Thus, there is a recent surge of interest in analyzing and verifying smart contracts. …
Short-Term Repositioning For Empty Vehicles On Ride-Sourcing Platforms, Hai Wang, Zhengli Wang
Short-Term Repositioning For Empty Vehicles On Ride-Sourcing Platforms, Hai Wang, Zhengli Wang
Research Collection School Of Computing and Information Systems
Motivation Ride sourcing companies, such as Uber, Lyft, and Didi, have been able to leverage on internet-based platforms to connect passengers and drivers. These platforms facilitate passengers and drivers’ mobility data on smartphones in real time, which enables a convenient matching between demand and supply. The imbalance of demand (i.e., passenger requests) and supply (i.e., drivers) on the platforms causes many unserved passenger requests and empty vehicles with idle drivers to exist at the same time, which poses a challenging problem for the platform. To address these challenges, some platforms display heat maps of surge-pricing multipliers or real-time demand to …
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
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 …
Rankbooster: Visual Analysis Of Ranking Predictions, Abishek Puri, Bon Kyung Ku, Yong Wang, Huamin Qu
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. …
Jplink: On Linking Jobs To Vocational Interest Types, Amila Silva, Pei Chi Lo, Ee-Peng Lim
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 …
Relationships Between Willingness To Share Information For Benefits And Trust, Gaurav Bansal, Fiona Fui-Hoon Nah
Relationships Between Willingness To Share Information For Benefits And Trust, Gaurav Bansal, Fiona Fui-Hoon Nah
Research Collection School Of Computing and Information Systems
This research examines the role of willingness to share one’s information for three benefits as tradeoffs – monetary gains, personalization, and national security – and their effects on trust in online businesses. Data were gathered from MTurk and the results indicate that willingness to share information for monetary gains and personalization is marginally associated with trust in online businesses, but willingness to share information for national security has no association with trust in online businesses. The paper also discusses implications, limitations, and future research directions.
Classification Of Labour Pain Using Electroencephalogram Signal Based On Wavelet Method, Chong Yeh Sai
Classification Of Labour Pain Using Electroencephalogram Signal Based On Wavelet Method, Chong Yeh Sai
Student Works (2020-2029)
Electroencephalogram (EEG) is the recording of electrical activity of the cerebral cortex through electrodes placed on the scalp. EEG is used to acquire neurophysiological signals for application in clinical diagnosis and brain computer interface (BCI). However, in practical settings the EEG signals are often contaminated by signal artifacts known as the biological and environmental artifacts. These artifacts degrade EEG signals, thereby obstructing clinical diagnosis or BCI applications by distorting the observed power spectrum. Procedures for automated removal of EEG artifacts are frequently sought after in pre-processing and filtering of the EEG signals. In recent years, a combination of independent component …
An Efficient Ddos Attack Detection Framework For Vehicular Communication, Kolandaisamy Raenu
An Efficient Ddos Attack Detection Framework For Vehicular Communication, Kolandaisamy Raenu
Student Works (2020-2029)
Vehicular Ad Hoc Networks (VANETs) are rapidly gaining attention due to the diversity of services that they can potentially offer. VANET is a wireless network that allows vehicles to interconnect and communicate with other nearby vehicles and Road Side Units (RSUs). In VANET, each vehicle is considered as a node which is equipped with an On-Board Unit (OBU) and an Application Unit (AU). The nodes may connect and communicate with each other directly (i.e., Vehicle to Vehicle (V2V)) or through RSUs (i.e., Vehicle to Infrastructure (V2I)). This is primarily for alleviating an Intelligent Transport System (ITS) that aims to provide …
Mitigating Real-Time Relay Phishing Attacks Against Mobile Push Notification Based Two-Factor Authentication Systems, Casey Silver
Mitigating Real-Time Relay Phishing Attacks Against Mobile Push Notification Based Two-Factor Authentication Systems, Casey Silver
Masters Theses, 2020-current
This paper explores how existing push notification based two-factor authentication systems are susceptible to real-time man-in-the-middle relay attacks and proposes a system for mitigating such attacks. A fully functional reference system of the proposed mitigation was built and compared to an existing push notification two-factor authentication system while undergoing a real-time man-in-the-middle relay attack. The reference systems used cloud infrastructure for hosting, an Apple iPhone as the notification receiver, and Apple’s push notification service to send notifications. A publicly available tool for conducting real-time man-in-the-middle relay attacks was used to conduct the attacks. The results of the tests were recorded …
Cornac: A Comparative Framework For Multimodal Recommender Systems, Aghiles Salah, Quoc Tuan Truong, Hady W. Lauw
Cornac: A Comparative Framework For Multimodal Recommender Systems, Aghiles Salah, Quoc Tuan Truong, Hady W. Lauw
Research Collection School Of Computing and Information Systems
Cornac is an open-source Python framework for multimodal recommender systems. In addition to core utilities for accessing, building, evaluating, and comparing recommender models, Cornac is distinctive in putting emphasis on recommendation models that leverage auxiliary information in the form of a social network, item textual descriptions, product images, etc. Such multimodal auxiliary data supplement user-item interactions (e.g., ratings, clicks), which tend to be sparse in practice. To facilitate broad adoption and community contribution, Cornac is publicly available at https://github.com/PreferredAI/cornac, and it can be installed via Anaconda or the Python Package Index (pip). Not only is it well-covered by unit tests …
The Two Types Of Society: Computationally Revealing Recurrent Social Formations And Their Evolutionary Trajectories, Lux Miranda
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 …
Knot Flow Classification And Its Applications In Vehicular Ad-Hoc Networks (Vanet), David Schmidt
Knot Flow Classification And Its Applications In Vehicular Ad-Hoc Networks (Vanet), David Schmidt
Electronic Theses and Dissertations
Intrusion detection systems (IDSs) play a crucial role in the identification and mitigation for attacks on host systems. Of these systems, vehicular ad hoc networks (VANETs) are difficult to protect due to the dynamic nature of their clients and their necessity for constant interaction with their respective cyber-physical systems. Currently, there is a need for a VANET-specific IDS that meets this criterion. To this end, a spline-based intrusion detection system has been pioneered as a solution. By combining clustering with spline-based general linear model classification, this knot flow classification method (KFC) allows for robust intrusion detection to occur. Due its …
Dependency Mapping Software For Jira, Project Management Tool, Bentley Lager
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. …