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2017

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Articles 1501 - 1530 of 2767

Full-Text Articles in Computer Sciences

Security And Privacy In Cloud Computing, Ramakrishnan Krishnan Apr 2017

Security And Privacy In Cloud Computing, Ramakrishnan Krishnan

Masters Theses

Cloud computing (CC) gained a widespread acceptance as a paradigm of computing. The main aim of CC is to reduce the need for customers' investment in new hardware or software by offering flexible cloud services, with a user reaping the benefits of the pay per use approach. CC demands addressing many security and privacy issues: both problems (vulnerabilities, threats, and attacks) and solutions (controls). The thesis discusses all these classes of problems and solutions, categorizing them as either security-related issues, privacy-related issues, or intertwined security and privacy issues. The main contributions of the thesis are twofold: first, using the …

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Deriving A Provisional Tolerable Intake For Intravenous Exposure To Silver Nanoparticles Released From Medical Devices, Laura C. Savery, Rene Vinas, Amber M. Nagy, Prachi Pradeep, Stephen Merrill, Subhas G. Malghan, Peter L. Goering, Ronald P. Brown Apr 2017

Deriving A Provisional Tolerable Intake For Intravenous Exposure To Silver Nanoparticles Released From Medical Devices, Laura C. Savery, Rene Vinas, Amber M. Nagy, Prachi Pradeep, Stephen Merrill, Subhas G. Malghan, Peter L. Goering, Ronald P. Brown

Mathematics, Statistics and Computer Science Faculty Research and Publications

Silver nanoparticles (AgNP) are incorporated into medical devices for their anti-microbial characteristics. The potential exposure and toxicity of AgNPs is unknown due to varying physicochemical particle properties and lack of toxicological data. The aim of this safety assessment is to derive a provisional tolerable intake (pTI) value for AgNPs released from blood-contacting medical devices. A literature review of in vivo studies investigating critical health effects induced from intravenous (i. v.) exposure to AgNPs was evaluated by the Annapolis Accords principles and Toxicological Data Reliability Assessment Tool (ToxRTool). The point of departure (POD) was based on an i. v. 28-day …

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Network-On-Chip Based H.264 Video Decoder On A Field Programmable Gate Array, Ian Barge Apr 2017

Network-On-Chip Based H.264 Video Decoder On A Field Programmable Gate Array, Ian Barge

Master's Theses (2009 -)

This thesis develops the first fully network-on-chip (NoC) based h.264 video decoder implemented in real hardware on a field programmable gate array (FPGA). This thesis starts with an overview of the h.264 video coding standard and an introduction to the NoC communication paradigm. Following this, a series of processing elements (PEs) are developed which implement the component algorithms making up the h.264 video decoder. These PEs, described primarily in VHDL with some Verilog and C, are then mapped to an NoC which is generated using the CONNECT NoC generation tool. To demonstrate the scalability of the proposed NoC based design, …

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Java Server Reliability In The Presence Of Failures, Rich Coe Apr 2017

Java Server Reliability In The Presence Of Failures, Rich Coe

Master's Theses (2009 -)

A design for the separation of a server interface and work processing. Numerous sources, Tanenbaum (Tanenbaum Modern Operating Systems, 493), Goscinski (Goscinski Distributed operating systems, 203), and Birman (Birman Reliable distributed systems, 265), all discuss the concept of Two-Phase Commit, where a coordinator directs one or more processes to perform a transaction. If the transaction or any of the processes fail, the coordinator can decide how to proceed by either retrying or aborting the request. The popular web browser Chrome utilizes a separate process for each tab displayed. Should the rendering and display of a web page cause a crash, …

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An Indoor Navigation System Using A Sensor Fusion Scheme On Android Platform, Jiayi Xin Apr 2017

An Indoor Navigation System Using A Sensor Fusion Scheme On Android Platform, Jiayi Xin

Master's Theses (2009 -)

With the development of wireless communication networks, smart phones have become a necessity for people’s daily lives, and they meet not only the needs of basic functions for users such as sending a message or making a phone call, but also the users’ demands for entertainment, surfing the Internet and socializing. Navigation functions have been commonly utilized, however the navigation function is often based on GPS (Global Positioning System) in outdoor environments, whereas a number of applications need to navigate indoors. This paper presents a system to achieve high accurate indoor navigation based on Android platform. To do this, we …

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A Comprehensive Context-Aware Interruption Management System, April Chunjiao Song Apr 2017

A Comprehensive Context-Aware Interruption Management System, April Chunjiao Song

Master's Theses (2009 -)

The interruption system is an application that prevents the user from noticing phone calls when he/she is busy, by turning off the ringtone. In a previous project, the user can enter his/her class and work schedule on Google Calendar. The intelligent interruption system can detect if the current time matches the range of one of the events in the user's Google Calendar. Other contexts considered were: driving, relationship of the callers, and proximity of Bluetooth devices. This project is a continuation of the interruption system. We consider additional context, social media such as Twitter. Research is done on when is …

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Mobile Big Data Analytics In Healthcare, Alramzana Nujum Navaz Apr 2017

Mobile Big Data Analytics In Healthcare, Alramzana Nujum Navaz

Theses

Mobile and ubiquitous devices are everywhere around us generating considerable amount of data. The concept of mobile computing and analytics is expanding due to the fact that we are using mobile devices day in and out without even realizing it. These mobile devices use Wi-Fi, Bluetooth or mobile data to be intermittently connected to the world, generating, sending and receiving data on the move. Latest mobile applications incorporating graphics, video and audio are main causes of loading the mobile devices by consuming battery, memory and processing power. Mobile Big data analytics includes for instance, big health data, big location data, …

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Improving Energy Efficiency For Iot Communications In 5g Networks, Gary Su Apr 2017

Improving Energy Efficiency For Iot Communications In 5g Networks, Gary Su

Master's Projects

Increase in number of Internet of Things (IoT) devices is quickly changing how mobile networks are being used by shifting more usage to uplink transmissions rather than downlink transmissions. Currently, mobile network uplinks utilize Single Carrier Frequency Division Multiple Access (SC-FDMA) schemes due to the low Peak to Average Power Ratio (PAPR) when compared to Orthogonal Frequency Division Multiple Access (OFDMA). In an IoT perspective, power ratios are highly important in effective battery usage since devices are typically resource-constrained. Fifth Generation (5G) mobile networks are believed to be the future standard network that will handle the influx of IoT device …

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Generic Online Learning For Partial Visible & Dynamic Environment With Delayed Feedback, Behrooz Shahriari Apr 2017

Generic Online Learning For Partial Visible & Dynamic Environment With Delayed Feedback, Behrooz Shahriari

Master's Projects

Reinforcement learning (RL) has been applied to robotics and many other domains which a system must learn in real-time and interact with a dynamic environment. In most studies the state-action space that is the key part of RL is predefined. Integration of RL with deep learning method has however taken a tremendous leap forward to solve novel challenging problems such as mastering a board game of Go. The surrounding environment to the agent may not be fully visible, the environment can change over time, and the feedbacks that agent receives for its actions can have a fluctuating delay. In this …

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Mining Frequency Of Drug Side Effects Over A Large Twitter Dataset Using Apache Spark, Dennis Hsu Apr 2017

Mining Frequency Of Drug Side Effects Over A Large Twitter Dataset Using Apache Spark, Dennis Hsu

Master's Projects

Despite clinical trials by pharmaceutical companies as well as current FDA reporting systems, there are still drug side effects that have not been caught. To find a larger sample of reports, a possible way is to mine online social media. With its current widespread use, social media such as Twitter has given rise to massive amounts of data, which can be used as reports for drug side effects. To process these large datasets, Apache Spark has become popular for fast, distributed batch processing. In this work, we have improved on previous pipelines in sentimental analysis-based mining, processing, and extracting tweets …

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Perception Of Performance Indicators In An Agri-Food Supply Chain, Sweta Chopra, Chad Laux, Edie Schmidt, Prashant Rajan Apr 2017

Perception Of Performance Indicators In An Agri-Food Supply Chain, Sweta Chopra, Chad Laux, Edie Schmidt, Prashant Rajan

Faculty Publications

Availability of nutritious, safe food, and guaranteed resources for a household to acquire food at all times results in food security. Availability of food at affordable price remains the greater challenge. Currently, the Indian government runs the Public Distribution System to provide commodity subsidies to households. Various government and private stakeholders are involved in making this procurement, storage, processing and distribution process work. The involvement of a large number of stakeholders, each with different interests, increases the complexity and difficulty to identify performance indicators of the supply chain. Current research evaluates the relationship among the participating stakeholders in the public …

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Probabilistic Roadmaps For Virtual Camera Pathing With Cinematographic Principles, Katherine Davis Apr 2017

Probabilistic Roadmaps For Virtual Camera Pathing With Cinematographic Principles, Katherine Davis

Master's Theses

As technology use increases in the world and inundates everyday life, the visual aspect of technology or computer graphics becomes increasingly important. This thesis presents a system for the automatic generation of virtual camera paths for fly-throughs of a digital scene. The sample scene used in this work is an underwater setting featuring a shipwreck model with other virtual underwater elements such as rocks, bubbles and caustics. The digital shipwreck model was reconstructed from an actual World War II shipwreck, resting off the coast of Malta. Video and sonar scans from an autonomous underwater vehicle were used in a photogrammetry …

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On The Effectiveness Of Virtualization Based Memory Isolation On Multicore Platforms, Siqi Zhao, Xuhua Ding Apr 2017

On The Effectiveness Of Virtualization Based Memory Isolation On Multicore Platforms, Siqi Zhao, Xuhua Ding

Research Collection School Of Computing and Information Systems

Virtualization based memory isolation has beenwidely used as a security primitive in many security systems.This paper firstly provides an in-depth analysis of itseffectiveness in the multicore setting; a first in the literature.Our study reveals that memory isolation by itself is inadequatefor security. Due to the fundamental design choices inhardware, it faces several challenging issues including pagetable maintenance, address mapping validation and threadidentification. As demonstrated by our attacks implementedon XMHF and BitVisor, these issues undermine the security ofmemory isolation. Next, we propose a new isolation approachthat is immune to the aforementioned problems. In our design,the hypervisor constructs a fully isolated micro …

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Empirical Study Of Usage And Performance Of Java Collections, Diego Costa, Artur Andrzejak, Janos Seboek, David Lo Apr 2017

Empirical Study Of Usage And Performance Of Java Collections, Diego Costa, Artur Andrzejak, Janos Seboek, David Lo

Research Collection School Of Computing and Information Systems

Collection data structures have a major impact on the performance of applications, especially in languages such as Java, C#, or C++. This requires a developer to select an appropriate collection from a large set of possibilities, including different abstractions (e.g. list, map, set, queue), and multiple implementations. In Java, the default implementation of collections is provided by the standard Java Collection Framework (JCF). However, there exist a large variety of less known third-party collection libraries which can provide substantial performance benefits with minimal code changes.

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Discovering Anomalous Events From Urban Informatics Data, Kasthuri Jayarajah, Vigneshwaran Subbaraju, Dulanga Kaveesha Weerakoon Mudiyanselage, Archan Misra, La Thanh Tam, Noel Athaide Apr 2017

Discovering Anomalous Events From Urban Informatics Data, Kasthuri Jayarajah, Vigneshwaran Subbaraju, Dulanga Kaveesha Weerakoon Mudiyanselage, Archan Misra, La Thanh Tam, Noel Athaide

Research Collection School Of Computing and Information Systems

Singapore's "smart city" agenda is driving the government to provide public access to a broader variety of urban informatics sources, such as images from traffic cameras and information about buses servicing different bus stops. Such informatics data serves as probes of evolving conditions at different spatiotemporal scales. This paper explores how such multi-modal informatics data can be used to establish the normal operating conditions at different city locations, and then apply appropriate outlier-based analysis techniques to identify anomalous events at these selected locations. We will introduce the overall architecture of sociophysical analytics, where such infrastructural data sources can be combined …

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Finding Causality And Responsibility For Probabilistic Reverse Skyline Query Non-Answers [Extended Abstract], Yunjun Gao, Qing Liu, Gang Chen, Linlin Zhou, Baihua Zheng Apr 2017

Finding Causality And Responsibility For Probabilistic Reverse Skyline Query Non-Answers [Extended Abstract], Yunjun Gao, Qing Liu, Gang Chen, Linlin Zhou, Baihua Zheng

Research Collection School Of Computing and Information Systems

This paper explores the causality and responsibility problem (CRP) for the non-answers to probabilistic reverse skyline queries (PRSQ). Towards this, we propose an efficient algorithm called CP to compute the causality and responsibility for the non-answers to PRSQ. CP first finds candidate causes, and then, it performs verification to obtain actual causes with their responsibilities, during which several strategies are used to boost efficiency. Extensive experiments using both real and synthetic data sets demonstrate the effectiveness and efficiency of the presented algorithms.

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Capturing Omni-Stereo Panoramas Within Unreal Engine 4, Evan Preslar Apr 2017

Capturing Omni-Stereo Panoramas Within Unreal Engine 4, Evan Preslar

Honors Capstones

No abstract provided.

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Neural Collaborative Filtering, Xiangnan He, Lizi Liao, Hanwang Zhang, Liqiang Nie, Xia Hu, Tat-Seng Chua Apr 2017

Neural Collaborative Filtering, Xiangnan He, Lizi Liao, Hanwang Zhang, Liqiang Nie, Xia Hu, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

In recent years, deep neural networks have yielded immense success on speech recognition, computer vision and natural language processing. However, the exploration of deep neural networks on recommender systems has received relatively less scrutiny. In this work, we strive to develop techniques based on neural networks to tackle the key problem in recommendation --- collaborative filtering --- on the basis of implicit feedback.Although some recent work has employed deep learning for recommendation, they primarily used it to model auxiliary information, such as textual descriptions of items and acoustic features of musics. When it comes to model the key factor in …

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Online Growing Neural Gas For Anomaly Detection In Changing Surveillance Scenes, Qianru Sun, Hong Liu, Tatsuya Harada Apr 2017

Online Growing Neural Gas For Anomaly Detection In Changing Surveillance Scenes, Qianru Sun, Hong Liu, Tatsuya Harada

Research Collection School Of Computing and Information Systems

Anomaly detection is still a challenging task for video surveillance due to complex environments and unpredictable human behaviors. Most existing approaches train offline detectors using manually labeled data and predefined parameters, and are hard to model changing scenes. This paper introduces a neural network based model called online Growing Neural Gas (online GNG) to perform an unsupervised learning. Unlike a parameter-fixed GNG, our model updates learning parameters continuously, for which we propose several online neighbor-related strategies. Specific operations, namely neuron insertion, deletion, learning rate adaptation and stopping criteria selection, get upgraded to online modes. In the anomaly detection stage, the …

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A Survey Of Impact Analysis Tools For Effective Code Evolution, Stephanie Perez Day Galbo Apr 2017

A Survey Of Impact Analysis Tools For Effective Code Evolution, Stephanie Perez Day Galbo

Theses and Dissertations

Background: Software maintenance and evolution are becoming noticeably more im- portant activities in the software development process, with the growing popularity of Agile/SCRUM and continuous integration. Impact analysis, the activity of identifying the consequences of a change before the change is made, can help the developer under- stand the consequences of their potential changes and therefore make informed decisions about incremental changes, with the ultimate goal of minimizing negative impacts on the current baseline. To aid developers with impact analysis, there are a number of tools with a variety of capabilities to facilitate this process. Aim: In order to help …

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Learning Personalized Preference Of Strong And Weak Ties For Social Recommendation, Xin Wang, Steven C. H. Hoi, Martin Ester, Jiajun Bu, Chun Chen Apr 2017

Learning Personalized Preference Of Strong And Weak Ties For Social Recommendation, Xin Wang, Steven C. H. Hoi, Martin Ester, Jiajun Bu, Chun Chen

Research Collection School Of Computing and Information Systems

Recent years have seen a surge of research on social recommendation techniques for improving recommender systems due to the growing influence of social networks to our daily life. The intuition of social recommendation is that users tend to show affinities with items favored by their social ties due to social influence. Despite the extensive studies, no existing work has attempted to distinguish and learn the personalized preferences between strong and weak ties, two important terms widely used in social sciences, for each individual in social recommendation. In this paper, we first highlight the importance of different types of ties in …

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Predicting The Impact Of Software Engineering Topics: An Empirical Study, Santonu Sarkar, Rumana Lakdawala, Subhajit Datta Apr 2017

Predicting The Impact Of Software Engineering Topics: An Empirical Study, Santonu Sarkar, Rumana Lakdawala, Subhajit Datta

Research Collection School Of Computing and Information Systems

Predicting the future is hard, more so in active research areas. In this paper, we customize an established model for citation prediction of research papers and apply it on research topics. We argue that research topics, rather than individual publications, have wider relevance in the research ecosystem, for individuals as well as organizations. In this study, topics are extracted from a corpus of software engineering publications covering 55,000+ papers written by more than 70,000 authors across 56 publication venues, over a span of 38 years, using natural language processing techniques. We demonstrate how critical aspects of the original paper-based prediction …

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The Crowd Work Accessibility Problem, Saiganesh Swaminathan, Kotaro Hara, Jeffrey P. Bigham Apr 2017

The Crowd Work Accessibility Problem, Saiganesh Swaminathan, Kotaro Hara, Jeffrey P. Bigham

Research Collection School Of Computing and Information Systems

Crowd work is an increasingly prevalent and important kind of work. Because of its flexible nature, crowd work may offer benefits for people with disabilities. Unfortunately, people with disabilities currently lack access to much of this work because the tasks that are posted are often inaccessible. In this paper, we first characterize the accessibility of the tasks posted to a popular crowd marketplace, Amazon Mechanical Turk, by performing manual and automatic checks on 120 tasks from several common types. We then outline research directions that could have positive impact on this problem. Given ongoing and upcoming changes to the world …

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On Analyzing User Topic-Specific Platform Preferences Across Multiple Social Media Sites, Roy Ka Wei Lee, Tuan Anh Hoang, Ee Peng Lim Apr 2017

On Analyzing User Topic-Specific Platform Preferences Across Multiple Social Media Sites, Roy Ka Wei Lee, Tuan Anh Hoang, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Topic modeling has traditionally been studied for single text collections and applied to social media data represented in the form of text documents. With the emergence of many social media platforms, users find themselves using different social media for posting content and for social interaction. While many topics may be shared across social media platforms, users typically show preferences of certain social media platform(s) over others for certain topics. Such platform preferences may even be found at the individual level. To model social media topics as well as platform preferences of users, we propose a new topic model known as …

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Now You See It, Now You Don't! A Study Of Content Modification Behavior In Facebook, Fuxiang Chen, Ee-Peng Lim Apr 2017

Now You See It, Now You Don't! A Study Of Content Modification Behavior In Facebook, Fuxiang Chen, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Social media, as a major platform to disseminate information, has changed the way users and communities contribute content. In this paper, we aim to study content modifications on public Facebook pages operated by news media, community groups, and bloggers. We also study the possible reasons behind them, and their effects on user interaction. We conducted a detailed study of Content Censorship (CC) and Content Edit (CE) in Facebook using a detailed longitudinal dataset consisting of 57 public Facebook pages over 3 weeks covering 145,955 posts and 9,379,200 comments. We detected many CC and CE activities between 28% and 56% of …

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Machine Comprehension Using Match-Lstm And Answer Pointer, Shuohang Wang, Jing Jiang Apr 2017

Machine Comprehension Using Match-Lstm And Answer Pointer, Shuohang Wang, Jing Jiang

Research Collection School Of Computing and Information Systems

Machine comprehension of text is an important problem in natural language processing. A recently released dataset, the Stanford Question Answering Dataset (SQuAD), offers a large number of real questions and their answers created by humans through crowdsourcing. SQuAD provides a challenging testbed for evaluating machine comprehension algorithms, partly because compared with previous datasets, in SQuAD the answers do not come from a small set of candidate answers and they have variable lengths. We propose an end-to-end neural architecture for the task. The architecture is based on match-LSTM, a model we proposed previously for textual entailment, and Pointer Net, a sequence-to-sequence …

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Modeling Topics And Behavior Of Microbloggers: An Integrated Approach, Tuan Anh Hoang, Ee-Peng Lim Apr 2017

Modeling Topics And Behavior Of Microbloggers: An Integrated Approach, Tuan Anh Hoang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Microblogging encompasses both user-generated content and behavior. When modeling microblogging data, one has to consider personal and background topics, as well as how these topics generate the observed content and behavior. In this article, we propose the Generalized Behavior-Topic (GBT) model for simultaneously modeling background topics and users' topical interest in microblogging data. GBT considers multiple topical communities (or realms) with different background topical interests while learning the personal topics of each user and the user's dependence on realms to generate both content and behavior. This differentiates GBT from other previous works that consider either one realm only or content …

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Assessing The Language Of Chat For Teamwork Dialogue, Antonette Shibani, Elizabeth Koh, Vivian Lai, Kyong Jin Shim Apr 2017

Assessing The Language Of Chat For Teamwork Dialogue, Antonette Shibani, Elizabeth Koh, Vivian Lai, Kyong Jin Shim

Research Collection School Of Computing and Information Systems

In technology enhanced language learning, many pedagogical activities involve students in online discussion such as synchronous chat, in order to help them practice their language skills. Besides developing the language competency of students, it is also crucial to nurture their teamwork competencies for today's global and complex environment. Language communication is an important glue of teamwork. In order to assess the language of chat for teamwork dimensions, several text mining methods are pos sible. However, difficulties arise such as pre-processing being a black box and classification approaches and algorithms being dependent on the context. To address these issues, the study …

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Aspect Extraction From Product Reviews Using Category Hierarchy Information, Yifeng Yang, Chen Cen, Minghui Qiu, Forrest Sheng Bao Apr 2017

Aspect Extraction From Product Reviews Using Category Hierarchy Information, Yifeng Yang, Chen Cen, Minghui Qiu, Forrest Sheng Bao

Research Collection School Of Computing and Information Systems

Aspect extraction is a task to abstract the common properties of objects from corpora discussing them, such as reviews of products. Recent work on aspect extraction is leveraging the hierarchical relationship between products and their categories. However, such effort focuses on the aspects of child categories but ignores those from parent categories. Hence, we propose an LDA-based generative topic model inducing the two-layer categorical information (CAT-LDA), to balance the aspects of both a parent category and its child categories. Our hypothesis is that child categories inherit aspects from parent categories, controlled by the hierarchy between them. Experimental results on 5 …

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What You See Is Not What You Get: Leakage-Resilient Password Entry Schemes For Smart Glasses, Yan Li, Yao Cheng, Yingjiu Li, Robert H. Deng Apr 2017

What You See Is Not What You Get: Leakage-Resilient Password Entry Schemes For Smart Glasses, Yan Li, Yao Cheng, Yingjiu Li, Robert H. Deng

Research Collection School Of Computing and Information Systems

Smart glasses are becoming popular for users to access various services such as email. To protect these services, password-based user authentication is widely used. Unfortunately, the password based user authentication has inherent vulnerability against password leakage. Many efforts have been put on designing leakage resilient password entry schemes on PCs and mobile phones with traditional input equipment including keyboards and touch screens. However, such traditional input equipment is not available on smart glasses. Existing password entry on smart glasses relies on additional PCs or mobile devices. Such solutions force users to switch between different systems, which causes interrupted experience and …

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