Computer Sciences Commons^™

Dynamic Inference Of Change Contracts, Tien-Duy B. Le, Jooyong Yi, David Lo, Ferdian Thung, Abhik Roychoudhury

Research Collection School Of Computing and Information Systems

Software evolves and thus developers frequently make changes to systems that are logged in version control systems. These changes are often poorly documented -- often commit logs are empty or only contain minimal information. Thus, it is often a challenge to understand why certain changes are made especially if they were introduced many months or even years ago. Understanding these changes is important when pertinent questions are raised during future bug fixing or software evolution efforts. Thus, there is a need for an automated approach that can help developers better document changes with little or minimal effort. To address this …

Competition Between Software-As-A-Service Vendors, Dan Ma, Robert John Kauffman

Research Collection School Of Computing and Information Systems

We propose a model of software-as-a-service (SaaS) in a competitive marketplace that brings clarity to the choices that competing vendors must make for pricing and quality strategy. We focus on several features of SaaS competition, including differences in vendor offerings, incomplete information on application functionality, the potential lock-in risk of SaaS clients, and their cost of learning about what it will take to make the vendors’ software work well. Clients can sample the fit costs of adoption, but can switch to another vendor. We obtained several findings through the use of a game-theoretic model. First, a client’s switching cost is …

Time-Series Data Mining In Transportation: A Case Study On Singapore Public Train Commuter Travel Patterns, Roy Ka Wei Lee, Tin Seong Kam

Research Collection School Of Computing and Information Systems

The adoption of smart cards technologies and automated data collection systems (ADCS) in transportation domain had provided public transport planners opportunities to amass a huge and continuously increasing amount of time-series data about the behaviors and travel patterns of commuters. However the explosive growth of temporal related databases has far outpaced the transport planners’ ability to interpret these data using conventional statistical techniques, creating an urgent need for new techniques to support the analyst in transforming the data into actionable information and knowledge. This research study thus explores and discusses the potential use of time-series data mining, a relatively new …

Entity Linking On Microblogs With Spatial And Temporal Signals, Yuan Fang, Ming-Wei Chang

Research Collection School Of Computing and Information Systems

Microblogs present an excellent opportunity for monitoring and analyzing world happenings. Given that words are often ambiguous, entity linking becomes a crucial step towards understanding microblogs. In this paper, we re-examine the problem of entity linking on microblogs. We first observe that spatiotemporal (i.e., spatial and temporal) signals play a key role, but they are not utilized in existing approaches. Thus, we propose a novel entity linking framework that incorporates spatiotemporal signals through a weakly supervised process. Using entity annotations1 on real-world data, our experiments show that the spatiotemporal model improves F1 by more than 10 points over existing systems. …

Analyzing The Dangers Posed By Chrome Extensions, Lujo Bauer, Shaoying Cai, Limin Jia, Timothy Passaro, Yuan Tian

Research Collection School Of Computing and Information Systems

A common characteristic of modern web browsers is that their functionality can be extended via third-party addons. In this paper we focus on Chrome extensions, to which the Chrome browser exports a rich API: extensions can potentially make network requests, access the local file system, get low-level information about running processes, etc. To guard against misuse, Chrome uses a permission system to curtail an extension's privileges. We demonstrate a series of attacks by which extensions can steal data, track user behavior, and collude to elevate their privileges. Although some attacks have previously been reported, we show that subtler versions can …

Action Classification By Exploring Directional Co-Occurrence Of Weighted Stips, Mengyuan Liu, Hong Liu, Qianru Sun

Research Collection School Of Computing and Information Systems

Human action recognition is challenging mainly due to intro-variety, inter-ambiguity and clutter backgrounds in real videos. Bag-of-visual words model utilizes spatio-temporal interest points(STIPs), and represents action by the distribution of points which ignores visual context among points. To add more contextual information, we propose a method by encoding spatio-temporal distribution of weighted pairwise points. First, STIPs are extracted from an action sequence and clustered into visual words. Then, each word is weighted in both temporal and spatial domains to capture the relationships with other words. Finally, the directional relationships between co-occurrence pairwise words are used to encode visual contexts. We …

Strategic Sourcing In The Presence Of Uncertain Supply And Retail Competition, Jianqing Chen, Zhiling Guo

Research Collection School Of Computing and Information Systems

This paper develops an analytical model to evaluate competing retail firms’ sourcing strategies in the presence of supply uncertainty. We consider a common supplier that sells its uncertain supply to two downstream retail firms engaging in price competition in a horizontally differentiated product market. The focal firm has a dual-sourcing option, while the rival firm can only source from the common supplier. We assess the system-wide effects of supply uncertainty on the focal firm's incentive to pursue the dual-sourcing strategy. We find that the focal firm's dual-sourcing strategy can create a win-win situation that leads to increased retail prices and …

Hippi Care Hospital: Towards Proactive Business Processes In Emergency Room Services, Kar Way Tan, Venky Shankaraman

Research Collection School Of Computing and Information Systems

It was 2.35 am on a Saturday morning. Wiki Lim, process specialist from the Process Innovation Centre (PIC) of Hippi Care Hospital (HCH), desperately doodling on her notepad for ideas to improve service delivery at HCH’s Emergency Department (ED). HCH has committed to the public that its ED would meet the service quality criterion of serving 90% of A3 and A4 patients, non-emergency patients with moderate to mild symptoms, within 90 minutes of their arrival at the ED. The ED was not able to meet this performance goal and Dr. Edward Kim, the head of the ED at HCH, had …

A Multi-Dimensional Image Quality Prediction Model For User-Generated Images In Social Networks, You Yang, Xu Wang, Tao Guan, Jialie Shen, Li Yu

Research Collection School Of Computing and Information Systems

User-generated images (UGIs) are currently proliferating within social networks. These images contain multi-dimensional data, including the image itself, text and the social links of the owner. UGIs can be utilized for self-presentation, news dissemination and other purposes, and the quality of the image should be able to reveal these social functionalities. However, it is challenging to predict UGI quality utilizing existing models, such as image quality assessment, recommender systems or others, because these models have difficulties processing multi-dimensional data simultaneously. To address this problem, we propose a multi-dimensional image quality prediction model for UGIs in social networks. In this model, …

Auction With Rolling Horizon For Urban Consolidation Centre, Chen Wang, Stephanus Daniel Handoko, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

A number of cities around the world have adopted urban consolidation centres (UCCs) to address some challenges of their last-mile deliveries. At the UCC, goods are consolidated based on their destinations prior to their deliveries into the city centre. In many examples, the UCC owns a fleet of eco-friendly vehicles to carry out the deliveries. A carrier/shipper who buys the UCC’s service hence no longer needs to enter the city centre in which time-window and vehicle-type restrictions may apply. As a result, it becomes possible to retain the use of large trucks for the economies of scale outside the city …

Optimal Prizes For All-Pay Contests In Heterogeneous Crowdsourcing, T. Luo, S. Kanhere, S. Das, Hwee-Pink Tan

Research Collection School Of Computing and Information Systems

Incentive is key to the success of crowd sourcing which heavily depends on the level of user participation. This paper designs an incentive mechanism to motivate a heterogeneous crowd of users to actively participate in crowd sourcing campaigns. We cast the problem in a new, asymmetric all-pay contest model with incomplete information, where an arbitrary n of users exert irrevocable effort to compete for a prize tuple. The prize tuple is an array of prize functions as opposed to a single constant prize typically used by conventional contests. We design an optimal contest that (a) induces the maximum profit -- …

Designing An Immersive And Entertaining Pervasive Gameplay Experience With Spheros As Game And Interface Elements, Brennan Jones, Kody Dillman, Setareh Aghel Manesh, Ehud Sharlin, Anthony Tang

Research Collection School Of Computing and Information Systems

The Sphero is a robotic remote-controlled ball capable of rolling around on its own in any direction at multiple speeds. Numerous games have been designed for the Sphero for smartphones and tablets. However, most of these games provide an interface for controlling the Sphero that is far from natural. These games also do not put a strong focus on the physical environment around the Sphero. This work discusses a control scheme used to control a Sphero with another Sphero, and a pervasive game leveraging this scheme that emphasizes physical properties of the environment to create an immersive experience.

Lossy Trapdoor Relation And Its Applications To Lossy Encryption And Adaptive Trapdoor Relation, Haiyang Xue, Xianhui Lu, Bao Li, Yamin Liu

Research Collection School Of Computing and Information Systems

Peikert and Waters proposed the notion of lossy trapdoor function in STOC 2008. In this paper, we propose a relaxation of lossy trapdoor function, called lossy trapdoor relation. Unlike the lossy trapdoor function, lossy trapdoor relation does not require completely recovering the input but a public computable injective map of it. Interestingly, the lossy trapdoor relation maintains the application of lossy trapdoor function on the lossy encryption. Moreover, motivated by the construction of adaptive trapdoor relation proposed by Wee (Crypto 2010), we introduce all-but-one verifiable lossy trapdoor relation which is in fact a relaxation of all-but-one lossy trapdoor function. – …

Dcamp: Distributed Common Api For Measuring Performance, Alexander Paul Sideropoulos

Master's Theses

Although the nearing end of Moore’s Law has been predicted numerous times in the past, it will eventually come to pass. In forethought of this, many modern computing systems have become increasingly complex, distributed, and parallel. As software is developed on and for these complex systems, a common API is necessary for gathering vital performance related metrics while remaining transparent to the user, both in terms of system impact and ease of use.

Several distributed performance monitoring and testing systems have been proposed and implemented by both research and commercial institutions. However, most of these systems do not meet several …

Camera Viewpoint Invariant Vehicular Traffic Segmentation And Classification, Jeffrey B. Flora

Electrical & Computer Engineering Theses & Dissertations

The goal of this intelligent transportation systems work is to develop a computer vision method that is view angle independent for segmenting and classifying vehicular traffic on highway systems. In order to achieve this goal, this work implements an algorithm for vehicle segmentation, feature extraction, and classification using the existing Virginia Department of Transportation (VDOT) infrastructure on networked traffic cameras. The VDOT traffic video is analyzed for vehicle detection and segmentation using an adaptive Gaussian mixture model algorithm. Speed estimation is performed using a single camera calibration. Size and shape features from morphological properties and texture features from histogram of …

Machine Learning Nuclear Detonation Features, Daniel T. Schmitt, Gilbert L. Peterson

Faculty Publications

Nuclear explosion yield estimation equations based on a 3D model of the explosion volume will have a lower uncertainty than radius based estimation. To accurately collect data for a volume model of atmospheric explosions requires building a 3D representation from 2D images. The majority of 3D reconstruction algorithms use the SIFT (scale-invariant feature transform) feature detection algorithm which works best on feature-rich objects with continuous angular collections. These assumptions are different from the archive of nuclear explosions that have only 3 points of view. This paper reduces 300 dimensions derived from an image based on Fourier analysis and five edge …

Timing Mark Detection On Nuclear Detonation Video, Daniel T. Schmitt, Gilbert L. Peterson

Faculty Publications

During the 1950s and 1960s the United States conducted and filmed over 200 atmospheric nuclear tests establishing the foundations of atmospheric nuclear detonation behavior. Each explosion was documented with about 20 videos from three or four points of view. Synthesizing the videos into a 3D video will improve yield estimates and reduce error factors. The videos were captured at a nominal 2500 frames per second, but range from 2300-3100 frames per second during operation. In order to combine them into one 3D video, individual video frames need to be correlated in time with each other. When the videos were captured …

Gpu Computation Checkpoint/Restart Scheme With Application-Level Stacks, Xinyuan Guo

Student Theses and Dissertations

To achieve high performance parallel computing, the graphic processing unit (GPU) plays a critical role. NVIDIA invented CUDA as a parallel processing platform and programming model in the late 1990s. With CUDA, we can directly use GPU with C, C++, Fortran, Java or Python code by NVCC compiler. We introduced checkpoint/restart scheme and computation states migration strategy for fault tolerance. Checkpoint/Restart scheme is used to save all the computation state in run-time for later restoration if necessary. Migrating computation state is the process of moving computation states from one heavily loaded host to a lightly loaded host for load balancing …

Masthead

Journal of Digital Forensics, Security and Law

No abstract provided.

Back Matter

Journal of Digital Forensics, Security and Law

No abstract provided.

Front Matter

Journal of Digital Forensics, Security and Law

No abstract provided.

Designing For Statistical Reasoning And Thinking In A Technology-Enhanced Learning Environment, Wendy Tu

CCAC Theses and Dissertations

Difficulties in learning and understanding statistics in college education have led to a reform movement in statistics education in the early 1990s. Although much work has been done, there is more work that needs to be done in statistics education. The progress depends on how well the educators bring interesting real-life data into the classroom.

The goal was to understand how course design based on First Principles of Instruction could facilitate tertiary-level students' conceptual understanding when learning introductory statistics in a technology-enhanced learning environment. An embedded single descriptive case design was employed to investigate how integrating technology and real data …

Secure Mobile Deployment Of Nfl Training Materials, Alexander R. Corris

CCAC Theses and Dissertations

The problem addressed is the lack of empirical research describing the delivery of individualized learning material in a secure and mobile manner. The goal was to investigate the effectiveness of deploying training materials to National Football League (NFL) players during a recent NFL season. Over the past few seasons, NFL teams have started to deliver player training material to mobile devices. The training material is sensitive and includes planning documents for upcoming games. An effort was made to survey a representative at each of the 32 NFL teams in order to gain insight on effectiveness, security, and process. Nearly half …

Performance Comparison Of Projective Elliptic-Curve Point Multiplication In 64-Bit X86 Runtime Environment, Ninh Winson

CCAC Theses and Dissertations

For over two decades, mathematicians and cryptologists have evaluated and presented the theoretical performance of Elliptic-curve scalar point-multiplication in projective geometry. Because computation in projective domain is composed of a wide array of formulations and computing optimizations, there is not a comprehensive performance comparison of point-multiplication using projective transformation available to verify its realistic efficiency in 64-bit x86 computing platforms. Today, research on explicit mathematical formulations in projective domain continues to excel by seeking higher computational efficiency and ease of realization. An explicit performance evaluation will help implementers choose better implementation methods and improve Elliptic-curve scalar point-multiplication. This paper was …

A Study Of The N-D-K Scalability Problem In Large-Scale Image Classification, Carlos E. Del-Castillo-Negrete, Sreenivas R. Sukumar

Yale Day of Data

Image classification is a extensively studied problem that lies at the heart of computer vision. However, the challenge remains to develop a system that can identify and classify thousands of objects like the human visual system. The accumulation of massive image data sets has permitted the study of this problem at a big-data scale. However current algorithms have been shown to fall short of being practical and accurate at scale. To further understand how these algorithms scale, we developed a library of functions to explore the scalability of the support vector machine (SVM) linear classification algorithm when applied to problems …

Investigating The Fractal Nature Of Individual User Netflow Data, Levi Malott, Sriram Chellappan

Computer Science Faculty Research & Creative Works

Modeling and characterizing Internet traffic has been a widely studied problem since the conception of the Internet. The self-similar, bursty nature of the traffic has led to a number of conventional statistical models that unfortunately provide relatively weak modeling power. Recently, fractal analysis techniques have emerged to better characterize and model Internet traffic data. However, past research studies have focused on describing and quantifying the fractal nature of Internet traffic on user groups, instead of a single user. In this paper the authors investigate the issue of individual users exhibiting fractal (self-similar behavior) behavior across multiple application types. Using real …

E-Darwin: Energy Aware Disaster Recovery Network Using Wifi Tethering, Mayank Raj, Krishna Kant, Sajal K. Das

Computer Science Faculty Research & Creative Works

In this paper, we propose a novel architecture called Energy Aware Disaster Recovery Network using Wi-Fi Tethering (E-DARWIN). The underlying idea is to make use of Wi-Fi Tethering technology ubiquitously available on wireless devices, like smartphones and tablets, to set up an ad hoc network for data collection in disaster scenarios. To this end, we design novel mechanisms, which aid in autonomous creation of the ad hoc network, distribution of data capturing task among the devices, and collection of data with minimum delay. Specifically, we design and implement a distributed coalition formation game for distributing the data capturing task among …

Dmctcp: Desynchronized Multi-Channel Tcp For High Speed Access Networks With Tiny Buffers, Cheng Cui, Lin Xue, Chui Hui Chiu, Praveenkumar Kondikoppa, Seung Jong Park

Computer Science Faculty Research & Creative Works

The past few years have witnessed debate on how to improve link utilization of high-speed tiny-size buffer routers. Widely argued proposals for TCP traffic to realize acceptable link capacities mandate: (i) over-provisioned core link bandwidth; and (ii) non-bursty flows; and (iii) tens of thousands of asynchronous flows. However, in high-speed access networks where flows are bursty, sparse and synchronous, TCP traffic suffer severely from routers with tiny buffers. We propose a new congestion control algorithm called Desyn-chronized Multi-Channel TCP (DMCTCP) that creates a flow with multiple channels. It avoids TCP loss synchronization by desynchronizing channels, and it avoids sending rate …

Understanding Usability-Related Information Security Failures In A Healthcare Context, Edward D. Boyer

CCAC Theses and Dissertations

This research study explores how the nature and type of usability failures impact task performance in a healthcare organization. Healthcare organizations are composed of heterogeneous and disparate information systems intertwined with complex business processes that create many challenges for the users of the system. The manner in which Information Technology systems and products are implemented along with the overlapping intricate tasks the users have pose problems in the area of usability. Usability research primarily focuses on the user interface; therefore, designing a better interface often leaves security in question. When usability failures arise from the incongruence between healthcare task and …

Performance Analysis Of Real-Time Traffic Over 802.11n Wireless Local Area Networks: An Experimental Study, John Podolanko, Sajib Datta, Sajal K. Das

Computer Science Faculty Research & Creative Works

In this paper, we describe a practical model of analyzing the performance of 802.11n Wireless Local Area Networks (WLANs) carrying real-time voice over IP (VoIP) traffic. In particular, we determine the response-time and packet loss of client nodes using traffic generators and network monitors. We demonstrate that there exists a correlation between the number of VoIP calls on a WLAN and the response time and packet loss between the nodes. We also determine maximum number of calls that can be handled on a WLAN before call quality is degraded. In addition, we calculate bandwidth utilization of the WLAN based on …