Computer Sciences Commons^™

Lean, Green, And Lifetime Maximizing Sensor Deployment On A Barrier, Peter Michael Terlecky

Dissertations, Theses, and Capstone Projects

Mobile sensors are located on a barrier represented by a line segment, and each sensor has a single energy source that can be used for both moving and sensing. Sensors may move once to their desired destinations and then coverage/communication is commenced. The sensors are collectively required to cover the barrier or in the communication scenario set up a chain of communication from endpoint to endpoint. A sensor consumes energy in movement in proportion to distance traveled, and it expends energy per time unit for sensing in direct proportion to its radius raised to a constant exponent.

The first focus …

Data-Driven Synthesis Of Animations Of Spatially Inflected American Sign Language Verbs Using Human Data, Pengfei Lu

Dissertations, Theses, and Capstone Projects

Techniques for producing realistic and understandable animations of American Sign Language (ASL) have accessibility benefits for signers with lower levels of written language literacy. Previous research in sign language animation didn’t address the specific linguistic issue of space use and verb inflection, due to a lack of sufficiently detailed and linguistically annotated ASL corpora, which is necessary for modern data-driven approaches. In this dissertation, a high-quality ASL motion capture corpus with ASL-specific linguistic structures is collected, annotated, and evaluated using carefully designed protocols and well-calibrated motion capture equipment. In addition, ASL animations are modeled, synthesized, and evaluated based on samples …

Integrating Water Exclusion Theory Into Β Contacts To Predict Binding Free Energy Changes And Binding Hot Spots, Qian Liu, Steven C. H. Hoi, Chee Keong Kwoh, Limsoon Wong, Jinyan Li

Research Collection School Of Computing and Information Systems

Binding free energy and binding hot spots at protein-protein interfaces are two important research areas for understanding protein interactions. Computational methods have been developed previously for accurate prediction of binding free energy change upon mutation for interfacial residues. However, a large number of interrupted and unimportant atomic contacts are used in the training phase which caused accuracy loss. Results: This work proposes a new method, β ACV ASA , to predict the change of binding free energy after alanine mutations. β ACV ASA integrates accessible surface area (ASA) and our newly defined β contacts together into an atomic contact vector …

Pricing Strategy For Cloud Computing Services, Jianhui Huang

Dissertations and Theses Collection (Open Access)

The cloud computing services market exhibits unique characteristics such as instant accessibility, fluctuating demand and supply, and interruptible service provision. Various pricing mechanisms exist in current industry practice. None of these pricing mechanisms, however, is comprehensive enough to capture all these features in a way that allows the vendors to optimize resource allocation. This dissertation identifies key factors related to cloud computing pricing, and examines their interplays. This research uses multiple approaches, including a market survey, game theory modeling, simulation, lab experiments and econometric modeling, to analyze the pricing strategy of cloud services vendors. A field study of a representative …

Energy Prediction Based Intrusion Detection In Wireless Sensor Networks, Nancy Alrajei, George Corser, Huirong Fu, Ye Zhu

Electrical and Computer Engineering Faculty Publications

A challenge in designing wireless sensor networks is to maximize the lifetime of the network with respect to limited resources and energy. These limitations make the network particularly vulnerable to attacks from adversaries. Denial of Service (DOS) is considered a severely damaging attack in monitoring applications when intruders attack the network and force it to lose its power and die early. There are intrusion detection approaches, but they require communications and calculations which waste the network’s limited resources. In this paper, we propose a new intrusion detection model that is suitable for defending against DOS attacks. We use the idea …

Visual Typo Correction By Collocative Optimization: A Case Study On Merchandize Images, Xiao-Yong Wei, Zhen-Qun Yang, Chong-Wah Ngo, Wei Zhang

Research Collection School Of Computing and Information Systems

Near-duplicate retrieval (NDR) in merchandize images is of great importance to a lot of online applications on e-Commerce websites. In those applications where the requirement of response time is critical, however, the conventional techniques developed for a general purpose NDR are limited, because expensive post-processing like spatial verification or hashing is usually employed to compromise the quantization errors among the visual words used for the images. In this paper, we argue that most of the errors are introduced because of the quantization process where the visual words are considered individually, which has ignored the contextual relations among words. We propose …

An Empirical Study Of Bug Report Field Reassignment, Xin Xia, David Lo, Ming Wen, Shihab Emad, Bo Zhou

Research Collection School Of Computing and Information Systems

A bug report contains many fields, such as product, component, severity, priority, fixer, operating system (OS), platform, etc., which provide important information for the bug triaging and fixing process. It is important to make sure that bug information is correct since previous studies showed that the wrong assignment of bug report fields could increase the bug fixing time, and even delay the delivery of the software. In this paper, we perform an empirical study on bug report field reassignments in open-source software projects. To better understand why bug report fields are reassigned, we manually collect 99 recent bug reports that …

Barometric Phone Sensors: More Hype Than Hope!, Kartik Muralidharan, Azeem Javed Khan, Archan Misra, Rajesh Krishna Balan, Sharad Agarwal

Research Collection School Of Computing and Information Systems

The inclusion of the barometer sensor in smartphones signaled an opportunity for aiding indoor localization efforts. In this paper, we therefore investigate a possible use of the barometer sensor for detecting vertically oriented activities. We start by showing the accuracies of various commodity measurement devices and the challenges they bring forth. We then show how to use the barometer values to build a predictor that can detect floor changes and the mode (elevator, escalator, or stairs) used to change floors with nearly 100% accuracy. We validate these properties with data collected using 3 different measurement devices from 7 different buildings. …

Building Thinc: User Incentivization And Meeting Rescheduling For Energy Savings, Jun Young Kwak, Debarun Kar, William Haskell, Pradeep Reddy Varakantham, Milind Tambe

Research Collection School Of Computing and Information Systems

This paper presents THINC, an agent developed for saving energy in real-world commercial buildings. While previous work has presented techniques for computing energy-efficient schedules, it fails to address two issues, centered on human users, that are essential in real-world agent deployments: (i) incentivizing users for their energy saving activities and (ii) interacting with users to reschedule key “energy-consuming” meetings in a timely fashion, while handling the uncertainty in such interactions. THINC addresses these shortcomings by providing four new major contributions. First, THINC computes fair division of credits from energy savings. For this fair division, THINC provides novel algorithmic advances for …

Los And Nlos Classification For Underwater Acoustic Localization, Roee Diamant, Hwee-Pink Tan, Lutz Lampe

Research Collection School Of Computing and Information Systems

The low sound speed in water makes propagation delay (PD)-based range estimation attractive for underwater acoustic localization (UWAL). However, due to the long channel impulse response and the existence of reflectors, PD-based UWAL suffers from significant degradation when PD measurements of nonline-of-sight (NLOS) communication links are falsely identified as line-of-sight (LOS). In this paper, we utilize expected variation of PD measurements due to mobility of nodes and present an algorithm to classify the former into LOS and NLOS links. First, by comparing signal strength-based and PD-based range measurements, we identify object-related NLOS (ONLOS) links, where signals are reflected from objects …

Livelabs: Building An In-Situ Real-Time Mobile Experimentation Testbed, Rajesh Krishna Balan, Archan Misra, Youngki Lee

Research Collection School Of Computing and Information Systems

We present LiveLabs, a mobile experimentation testbed that is currently deployed across our university campus with further deployments at a large shopping mall, a commercial airport, and a resort island soon to follow. The key goal of LiveLabs is to allow in-situ real-time experimentation of mobile applications and services that require context-specific triggers with real participants on their actual smart phones. We describe how LiveLabs works, and then explain the novel R&D required to realise it. We end with a descriptionof the current LiveLabs status (> 700 active participants to date) as well as present some key lessons learned.

Representative Discovery Of Structure Cues For Weakly-Supervised Image Segmentation, Luming Zhang, Yue Gao, Yingjie Xia, Ke Lu, Jialie Shen, Rongrong Ji

Research Collection School Of Computing and Information Systems

Weakly-supervised image segmentation is a challenging problem with multidisciplinary applications in multimedia content analysis and beyond. It aims to segment an image by leveraging its imagelevel semantics (i.e., tags). This paper presents a weakly-supervised image segmentation algorithm that learns the distribution of spatially structural superpixel sets from image-level labels. More specifically, we first extract graphlets from a given image, which are small-sized graphs consisting of superpixels and encapsulating their spatial structure. Then, an ecient manifold embedding algorithm is proposed to transfer labels from training images into graphlets. It is further observed that there are numerous redundant graphlets that are not …

Integrating Water Exclusion Theory Into Β Contacts To Predict Binding Free Energy Changes And Binding Hot Spots, Qian Liu, Steven C. H. Hoi, Chee Keong Kwoh, Limsoon Wong, Jinyan Li

Research Collection School Of Computing and Information Systems

Binding free energy and binding hot spots at protein-protein interfaces are two important research areas for understanding protein interactions. Computational methods have been developed previously for accurate prediction of binding free energy change upon mutation for interfacial residues. However, a large number of interrupted and unimportant atomic contacts are used in the training phase which caused accuracy loss. Results: This work proposes a new method, β ACV ASA , to predict the change of binding free energy after alanine mutations. β ACV ASA integrates accessible surface area (ASA) and our newly defined β contacts together into an atomic contact vector …

Democracy Is Good For Ranking: Towards Multi-View Rank Learning And Adaptation In Web Search, Wei Gao, Pei Yang

Research Collection School Of Computing and Information Systems

No abstract provided.

Automated Learner Classification Through Interface Event Stream And Summary Statistics Analysis, Edgar E. Troudt

Dissertations, Theses, and Capstone Projects

Reading comprehension is predominately measured through multiple choice examinations. Yet, as we will discuss in this thesis, such exams are often criticized for their inaccuracies. With the advent of "big data" and the rise of ITS (Intelligent Tutoring Systems), increasing focus will be placed on finding dynamic, automated ways of measuring students' aptitude and progress.

This work takes the first step towards automated learner classification based on the application of graphic organizers. We address the following specific problem experimentally: How effectively can we measure task comprehension via human translation of written text into a visual representation on a computer? Can …

A Parametrization-Based Surface Reconstruction System For Triangular Mesh Simplification With Application To Large Scale Scenes, Adriana Wise

Dissertations, Theses, and Capstone Projects

The laser scanner is nowadays widely used to capture the geometry of art, animation maquettes, or large architectural, industrial, and land form models. It thus poses specific problems depending on the model scale. This thesis provides a solution for simplification of triangulated data and for surface reconstruction of large data sets, where feature edges provide an obvious segmentation structure. It also explores a new method for model segmentation, with the goal of applying multiresolution techniques to data sets characterized by curvy areas and the lack of clear demarcation features. The preliminary stage of surface segmentation, which takes as input single …

Libol: A Library For Online Learning Algorithms, Steven C. H. Hoi, Jialei Wang, Peilin Zhao

Research Collection School Of Computing and Information Systems

LIBOL is an open-source library for large-scale online learning, which consists of a large family of efficient and scalable state-of-the-art online learning algorithms for large- scale online classification tasks. We have offered easy-to-use command-line tools and examples for users and developers, and also have made comprehensive documents available for both beginners and advanced users. LIBOL is not only a machine learning toolbox, but also a comprehensive experimental platform for conducting online learning research.

Sketch: Pen And Touch Recognition [Workshop Summary], Richard C. Davis, Aaron Adler

Research Collection School Of Computing and Information Systems

Sketch recognition has technically been around for 40 years, but it has come and gone several times due to the difficulty of the problem. With the rise of touch and pen enabled phones and tablets, sketch recognition is regaining popularity and public presence, and more people are becoming aware of and interested in this difficult, but valuable, problem. It is important to harness the Sketch Recognition community at this time to encourage the flourishing of this topic.

Extended Comprehensive Study Of Association Measures For Fault Localization, Lucia Lucia, David Lo, Lingxiao Jiang, Ferdian Thung, Aditya Budi

Research Collection School Of Computing and Information Systems

Spectrum-based fault localization is a promising approach to automatically locate root causes of failures quickly. Two well-known spectrum-based fault localization techniques, Tarantula and Ochiai, measure how likely a program element is a root cause of failures based on profiles of correct and failed program executions. These techniques are conceptually similar to association measures that have been proposed in statistics, data mining, and have been utilized to quantify the relationship strength between two variables of interest (e.g., the use of a medicine and the cure rate of a disease). In this paper, we view fault localization as a measurement of the …

Key-Aggregate Cryptosystem For Scalable Data Sharing In Cloud Storage, Cheng-Kang Chu, Sherman S. M. Chow, Wen-Guey Tzeng, Jiangying Zhou, Robert H. Deng

Research Collection School Of Computing and Information Systems

Data sharing is an important functionality in cloud storage. In this article, we show how to securely, efficiently, and flexibly share data with others in cloud storage. We describe new public-key cryptosystems which produce constant-size ciphertexts such that efficient delegation of decryption rights for any set of ciphertexts are possible. The novelty is that one can aggregate any set of secret keys and make them as compact as a single key, but encompassing the power of all the keys being aggregated. In other words, the secret key holder can release a constant-size aggregate key for flexible choices of ciphertext set …

Ropecker: A Generic And Practical Approach For Defending Against Rop Attack, Yueqiang Cheng, Zongwei Zhou, Yu Miao, Xuhua Ding, Robert H. Deng

Research Collection School Of Computing and Information Systems

Return-Oriented Programming (ROP) is a sophisticated exploitation technique that is able to drive target applications to perform arbitrary unintended operations by constructing a gadget chain reusing existing small code sequences (gadgets). Existing defense mechanisms either only handle specific types of gadgets, require access to source code and/or a customized compiler, break the integrity of application binary, or suffer from high performance overhead. In this paper, we present a novel system, ROPecker, to efficiently and effectively defend against ROP attacks without relying on any other side information (e.g., source code and compiler support) or binary rewriting. ROPecker detects an ROP attack …

Predicting Response In Mobile Advertising With Hierarchical Importance-Aware Factorization Machine, Richard Jayadi Oentaryo, Ee Peng Lim, Jia Wei Low, David Lo, Michael Finegold

Research Collection School Of Computing and Information Systems

Mobile advertising has recently seen dramatic growth, fueled by the global proliferation of mobile phones and devices. The task of predicting ad response is thus crucial for maximizing business revenue. However, ad response data change dynamically over time, and are subject to cold-start situations in which limited history hinders reliable prediction. There is also a need for a robust regression estimation for high prediction accuracy, and good ranking to distinguish the impacts of different ads. To this end, we develop a Hierarchical Importance-aware Factorization Machine (HIFM), which provides an effective generic latent factor framework that incorporates importance weights and hierarchical …

Towards More Accurate Multi-Label Software Behavior Learning, Xin Xia, Feng Yang, David Lo, Zhenyu Chen, Xinyu Wang

Research Collection School Of Computing and Information Systems

In a modern software system, when a program fails, a crash report which contains an execution trace would be sent to the software vendor for diagnosis. A crash report which corresponds to a failure could be caused by multiple types of faults simultaneously. Many large companies such as Baidu organize a team to analyze these failures, and classify them into multiple labels (i.e., multiple types of faults). However, it would be time-consuming and difficult for developers to manually analyze these failures and come out with appropriate fault labels. In this paper, we automatically classify a failure into multiple types of …

Automated Construction Of A Software-Specific Word Similarity Database, Yuan Tian, David Lo, Julia Lawall

Research Collection School Of Computing and Information Systems

Many automated software engineering approaches, including code search, bug report categorization, and duplicate bug report detection, measure similarities between two documents by analyzing natural language contents. Often different words are used to express the same meaning and thus measuring similarities using exact matching of words is insufficient. To solve this problem, past studies have shown the need to measure the similarities between pairs of words. To meet this need, the natural language processing community has built WordNet which is a manually constructed lexical database that records semantic relations among words and can be used to measure how similar two words …

Sinabro: Opportunistic And Unobtrusive Mobile Ecg Monitoring System, Seungwoo Kang, Sungjun Kwon, Sangwon Seo, Chungkuk Yoo, Kwangsuk Park, Junehwa Song, Youngki Lee

Research Collection School Of Computing and Information Systems

In this paper, we propose Sinabro, an opportunistic and unobtrusive mobile electrocardiogram (ECG) monitoring system that monitors the user’s ECG opportunistically during daily smartphone use. Daily ECG monitoring will open up an unprecedented opportunity for pervasive healthcare applications. It will enable the daily detection and prevention of heart problems and also allow inferences about stress, emotion, and even sleep quality. Despite its huge potential, daily ECG monitoring still has not become reality due to its obtrusiveness. In this paper, we first study the potential opportunity to capture ECGs from daily use of smartphones, without requiring the user’s explicit attention. Based …

Examining The Growth Of Digital Wireless Phone Technology: A Take-Off Theory Analysis, Angsana A. Techatassanasoontorn, Robert J. Kauffman

Research Collection School Of Computing and Information Systems

The early phase of diffusion plays a critical role in determining information technology (IT) success in a market. Takeoff, the transition point from the introduction to the growth phase in the IT life cycle, is viewed as an acid test for whether a technology will succeed. We develop a theory to understand global takeoff for digital wireless phones that can be extended to other technologies with related characteristics. Drawing on technology dominance and product life cycle theories, we build a model that consists of standards, market competition, technology costs, and technology substitution to explain takeoff and subsequent market penetration growth. …

Digital Certificate Management: Optimal Pricing And Crl Releasing Strategies, Jie Zhang, Nan Hu, M. K. Raka

Research Collection School Of Computing and Information Systems

The fast growth of e-commerce and online activities places increasing needs for authentication and secure communication to enable information exchange and online transactions. The public key infrastructure (PKI) provides a promising foundation for meeting such demand, in which certificate authorities (CAs) provide digital certificates. In practice, it is critical to understand consumer purchasing and revocation behaviors so that CAs can better manage the digital certificates and its CRL releasing process. To address this problem, we analytically model a CA's pricing and revocation releasing strategies taking into consideration the users' rational decisions. The model provides solutions two main research questions: (1) …

Identity Based Identification From Algebraic Coding Theory, Guomin Yang, Chik How Tan, Yi Mu, Willy Susilo, Duncan S. Wong

Research Collection School Of Computing and Information Systems

Cryptographic identification schemes allow a remote user to prove his/her identity to a verifier who holds some public information of the user, such as the user public key or identity. Most of the existing cryptographic identification schemes are based on numbertheoretic hard problems such as Discrete Log and Factorization. This paper focuses on the design and analysis of identity based identification (IBI) schemes based on algebraic coding theory. We first revisit an existing code-based IBI scheme which is derived by combining the Courtois–Finiasz–Sendrier signature scheme and the Stern zero-knowledge identification scheme. Previous results have shown that this IBI scheme is …

Increasing Adolescent Interest In Computing Through The Use Of Social Cognitive Career Theory, Osama Eljabiri

Dissertations

While empirical research efforts are sufficient to provide evidence of the role of most constructs in the Social Cognitive Career Theory (SCCT), this dissertation shifts the research focus and finds serious shortcomings in defining the construct of computer technology learning experiences design.

The purpose of this dissertation is to investigate whether, and to what extent, the proposed SCCT-enhanced framework can increase self-efficacy and interest of pre-college and college students in computer-based technology through the newly proposed “Learning Experiences” construct; in particular, whether it can reduce the gender gaps.

As a result of a comprehensive literature review, the dissertation connects learning, …

Innovative Local Texture Descriptors With Application To Eye Detection, Jiayu Gu

Dissertations

Local Binary Patterns (LBP), which is one of the well-known texture descriptors, has broad applications in pattern recognition and computer vision. The attractive properties of LBP are its tolerance to illumination variations and its computational simplicity. However, LBP only compares a pixel with those in its own neighborhood and encodes little information about the relationship of the local texture with the features. This dissertation introduces a new Feature Local Binary Patterns (FLBP) texture descriptor that can compare a pixel with those in its own neighborhood as well as in other neighborhoods and encodes the information of both local texture and …