Computer Sciences Commons^™

Cloud To Cloud Registration For 3d Point Data, Darion Shawn Grant

Open Access Dissertations

The vast potential of digital representation of objects by large collections of 3D points is being recognized on a global scale and has given rise to the popularity of point cloud data (PCD). 3D imaging sensors provide a means for quickly capturing dense and accurate geospatial information that represent the 3D geometry of objects in a digital environment. Due to spatial and temporal constraints, it is quite common that two or more sets of PCD are obtained to provide full 3D analysis. It is therefore quite essential that all the PCD are referenced to a homogeneous coordinate frame of reference. …

Improving Virtual Machine I/O Performance In Cloud Environments Via I/O Functionality Offloading, Sahan Bamunavita Gamage

Open Access Dissertations

In recent years there has been a rapid growth in the adoption of cloud computing. A key technology that drives cloud computing is virtualization. In addition to enabling multi-tenancy in cloud environments, virtualizing hosts in the cloud environments has made management of hardware resources increasingly flexible. An important consequence of virtualizing hosts in the cloud is the negative impact it has on the I/O performance of the applications running in the virtual machines.

In this dissertation, we address the important problem of alleviating the negative impact of virtualization on I/O of the virtual machines. First, we show that virtual machine …

Designing Mobile Educational Games On Voter‟S Education: A Tale Of Three Engines, Ma. Regina Justina E. Estuar, Nadia Rowena C. Leetian, Michael B. Syson

Department of Information Systems & Computer Science Faculty Publications

The rapid growth of mobile learning is influenced by the ability to access learning content anytime and anywhere. The on demand capability is available because mobile devices allow for convergence of internet and communications technologies. At the same time, the availability of engines makes development of mobile applications faster and seamless. However, not all mobile development engines are alike. This paper discusses on the development of mobile learning applications using mobile development engines in teaching Filipinos on responsible voting. Specifically, this paper discusses how AndEngine, Ren’Py, and homegrown Usbong were used to develop a mobile board game and a mobile …

Adaptive Gameplay For Programming Practice, Chris Boesch, Sandra Boesch

Research Collection School Of Computing and Information Systems

Over the past four years, we have collaborated to develop a set of online games to enable users to practice software languages in a self-directed manner and as part of a class. Recently we introduced a new adaptive difficulty feature that enables players to self-regulate the difficulty of the games they are playing to practice. These new features also provide additional information to further adapt the problem content to better meet the needs of the users.

Modeling Interaction Features For Debate Side Clustering, Minghui Qiu, Liu Yang, Jing Jiang

Research Collection School Of Computing and Information Systems

Online discussion forums are popular social media platforms for users to express their opinions and discuss controversial issues with each other. To automatically identify the sides/stances of posts or users from textual content in forums is an important task to help mine online opinions. To tackle the task, it is important to exploit user posts that implicitly contain support and dispute (interaction) information. The challenge we face is how to mine such interaction information from the content of posts and how to use them to help identify stances. This paper proposes a two-stage solution based on latent variable models: an …

Wind Power Uncertainty And Power System Performance, C. Lindsay Anderson, Judith Cardell

Engineering: Faculty Publications

The penetration of wind power into global electric power systems is steadily increasing, with the possibility of 30% to 80% of electrical energy coming from wind within the coming decades. At penetrations below 10% of electricity from wind, the impact of this variable resource on power system operations is manageable with historical operating strategies. As this penetration increases, new methods for operating the power system and electricity markets need to be developed. As part of this process, the expected impact of increased wind penetration needs to be better understood and quantified. This paper presents a comprehensive modeling framework, combining optimal …

San José State University Building Editor, Viet Trinh

Master's Projects

The San José State University (SJSU) Building Editor is a graphic application that renders the SJSU architectures in a multidimensional space and simulates the flows of people evacuating in the buildings under different circumstances. For a given building, the goals of this application are to analyze a density of people on each floor, to predict bottlenecks in each structure, and to simulate an optimal evacuation plan in case of an emergency for selected SJSU buildings that are visualized in multidimensional models. This report describes in detail functionalities of the application, studies key points in its implementation, and analyzes the application’s …

Pattern Recognition Of Dna Sequences Using Automata With Application To Species Distinction, Parnika P. Achrekar

Master's Projects

"Darwin wasn't just provocative in saying that we descend from the apes—he didn't go far enough, we are apes in every way, from our long arms and tailless bodies to our habits and temperament." said Frans de Waal, a primate scientist at Emory University in Atlanta, Georgia. 1.3 million Species have been named and analyzed by scientists. This project focuses on capturing various nucleotide sequences of various species and determining the similarity and differences between them. Finite state automata have been used to accomplish this. The automata for a DNA genome is created using Alergia algorithm and is used as …

Articulatory Distinctiveness Of Vowels And Consonants: A Data-Driven Approach, Jun Wang, Jordan R. Green, Ashok Samal, Yana Yunusova

School of Computing: Faculty Publications

Purpose: To quantify the articulatory distinctiveness of 8 major English vowels and 11 English consonants based on tongue and lip movement time series data using a data-driven approach.

Method: Tongue and lip movements of 8 vowels and 11 consonants from 10 healthy talkers were collected. First, classification accuracies were obtained using 2 complementary approaches: (a) Procrustes analysis and (b) a support vector machine. Procrustes distance was then used to measure the articulatory distinctiveness among vowels and consonants. Finally, the distance (distinctiveness) matrices of different vowel pairs and consonant pairs were used to derive articulatory vowel and consonant spaces …

Interactive Focus+Context Glyph And Streamline Vector Visualization, Joshua Joseph Anghel

Boise State University Theses and Dissertations

With data sets growing in size, more efficient methods of visualizing and analyzing data are required. A user can become overwhelmed if too much data is displayed at once and be distracted from identifying potentially important features. This thesis presents methods for focus+context visualization of vector fields. Users can interact with the data in real time to choose which regions should have more emphasis through a mouse or touch interface. Streamlines and hedgehog based visualizations are used to provide focus+context to vector visualizations. The presented visualization methods are shown to be more computationally efficient and are shown to scale well …

Todmis: Mining Communities From Trajectories, Siyuan Liu, Shuhui Wang, Kasthuri Jayarajah, Archan Misra, Rammaya Krishnan

Research Collection School Of Computing and Information Systems

Existing algorithms for trajectory-based clustering usually rely on simplex representation and a single proximity-related distance (or similarity) measure. Consequently, additional information markers (e.g., social interactions or the semantics of the spatial layout) are usually ignored, leading to the inability to fully discover the communities in the trajectory database. This is especially true for human-generated trajectories, where additional fine-grained markers (e.g., movement velocity at certain locations, or the sequence of semantic spaces visited) can help capture latent relationships between cluster members. To address this limitation, we propose TODMIS: a general framework for Trajectory cOmmunity Discovery using Multiple Information Sources. TODMIS combines …

Understanding Online Consumer’S Inter-Purchase Time, Youngsoo Kim

Research Collection School Of Computing and Information Systems

This study is motivated by the premise that online consumers can make a purchase at any time of day if they have even a tiny time slot along with Internet access. Given the increased shopping time flexibility, we first examine the patterns of online purchase timing at an online shopping mall handling diverse products (e.g., Amazon.com). The results show (1) the breakdown of purchase timing regularity and (2) the change of weekly spike purchase occurrence. Second, we build online inter-purchase time and price promotion utilization models and estimate them with the data collected from one of the premier online shopping …

Automatic Recovery Of Root Causes From Bug-Fixing Changes, Ferdian Thung, David Lo, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

What is the root cause of this failure? This question is often among the first few asked by software debuggers when they try to address issues raised by a bug report. Root cause is the erroneous lines of code that cause a chain of erroneous program states eventually leading to the failure. Bug tracking and source control systems only record the symptoms (e.g., bug reports) and treatments of a bug (e.g., committed changes that fix the bug), but not its root cause. Many treatments contain non-essential changes, which are intermingled with root causes. Reverse engineering the root cause of a …

Automated Library Recommendation, Ferdian Thung, David Lo, Julia Lawall

Research Collection School Of Computing and Information Systems

Many third party libraries are available to be downloaded and used. Using such libraries can reduce development time and make the developed software more reliable. However, developers are often unaware of suitable libraries to be used for their projects and thus they miss out on these benefits. To help developers better take advantage of the available libraries, we propose a new technique that automatically recommends libraries to developers. Our technique takes as input the set of libraries that an application currently uses, and recommends other libraries that are likely to be relevant. We follow a hybrid approach that combines association …

On Effects Of Visual Query Complexity, Jialie Shen, Cheng Zhiyong

Research Collection School Of Computing and Information Systems

As an effective technique to manage large scale image collections, content-based image retrieval (CBIR) has been received great attentions and became a very active research domain in recent years. While assessing system performance is one of the key factors for the related technological advancement, relatively little attention has been paid to model and analyze test queries. This paper documents a study on the problem of determining visual query complexity as a measure for predicting image retrieval performance. We propose a quantitative metric for measuring complexity of image queries for content-based image search engine. A set of experiments are carried out …

Cell: A Compositional Verification Framework, Kun Ji, Yang Liu, Jun Sun, Jun Sun, Jin Song Dong, Truong Khanh Nguyen

Research Collection School Of Computing and Information Systems

This paper presents CELL, a comprehensive and extensible framework for compositional verification of concurrent and real-time systems based on commonly used semantic models. For each semantic model, CELL offers three libraries, i.e., compositional verification paradigms, learning algorithms and model checking methods to support various state-of-the-art compositional verification approaches. With well-defined APIs, the framework could be applied to build customized model checkers. In addition, each library could be used independently for verification and program analysis purposes. We have built three model checkers with CELL. The experimental results show that the performance of these model checkers can offer similar or often better …

Consistent Stereo Image Editing, Tao Yan, Shengfeng He, Rynson W.H. Lau, Yun Xu

Research Collection School Of Computing and Information Systems

Stereo images and videos are very popular in recent years, and techniques for processing this media are attracting a lot of attention. In this paper, we extend the shift-map method for stereo image editing. Our method simultaneously processes the left and right images on pixel level using a global optimization algorithm. It enforces photo consistence between the two images and preserves 3D scene structures. It also addresses the occlusion and disocclusion problem, which may enable many stereo image editing functions, such as depth mapping, object depth adjustment and non-homogeneous image resizing. Our experiments show that the proposed method produces high …

Image Search By Graph-Based Label Propagation With Image Representation From Dnn, Yingwei Pan, Yao Ting, Kuiyuan Yang, Houqiang Li, Chong-Wah Ngo, Jingdong Wang, Tao Mei

Research Collection School Of Computing and Information Systems

Our objective is to estimate the relevance of an image to a query for image search purposes. We address two limitations of the existing image search engines in this paper. First, there is no straightforward way of bridging the gap between semantic textual queries as well as users’ search intents and image visual content. Image search engines therefore primarily rely on static and textual features. Visual features are mainly used to identify potentially useful recurrent patterns or relevant training examples for complementing search by image reranking. Second, image rankers are trained on query-image pairs labeled by human experts, making the …

Skyhunter: A Multi-Surface Environment For Supporting Oil And Gas Exploration, Teddy Seyed, Mario Costa Sousa, Frank Maurer, Anthony Tang

Research Collection School Of Computing and Information Systems

The process of oil and gas exploration and its result, the decision to drill for oil in a specific location, relies on a number of distinct but related domains. These domains require effective collaboration to come to a decision that is both cost effective and maintains the integrity of the environment. As we show in this paper, many of the existing technologies and practices that support the oil and gas exploration process overlook fundamental user issues such as collaboration, interaction and visualization. The work presented in this paper is based upon a design process that involved expert users from an …

Online Multimodal Distance Metric Learning With Application To Image Retrieval, Pengcheng Wu, Steven C. H. Hoi, Hao Xia, Peilin Zhao, Dayong Wang, Chunyan Miao

Research Collection School Of Computing and Information Systems

Recent years have witnessed extensive studies on distance metric learning (DML) for improving similarity search in multimedia information retrieval tasks. Despite their successes, most existing DML methods suffer from two critical limitations: (i) they typically attempt to learn a linear distance function on the input feature space, in which the assumption of linearity limits their capacity of measuring the similarity on complex patterns in real-world applications; (ii) they are often designed for learning distance metrics on uni-modal data, which may not effectively handle the similarity measures for multimedia objects with multimodal representations. To address these limitations, in this paper, we …

An Experimental Study For Inter-User Interference Mitigation In Wireless Body Sensor Networks, Bin Cao, Yu Ge, Chee Wee Kim, Gang Feng, Hwee-Pink Tan, Yun Li

Research Collection School Of Computing and Information Systems

Inter-user interference degrades the reliability of data delivery in wireless body sensor networks (WBSNs) in dense deployments when multiple users wearing WBSNs are in close proximity to one another. The impact of such interference in realistic WBSN systems is significant but is not well explored. To this end, we investigate and analyze the impact of inter-user interference on packet delivery ratio (PDR) and throughput. We conduct extensive experiments based on the TelosB WBSN platform, considering unslotted carrier sense multiple access (CSMA) with collision avoidance (CA) and slotted CSMA/CA modes in IEEE 802.15.4 MAC, respectively. In order to mitigate interuser interference, …

Metamorphic Detection Using Singular Value Decomposition, Ranjith Kumar Jidigam

Master's Projects

Metamorphic malware changes its internal structure with each infection, while maintaining its original functionality. Such malware can be difficult to detect using static techniques, since there may be no common signature across infections. In this research we apply a score based on Singular Value Decomposition (SVD) to the problem of metamorphic detection. SVD is a linear algebraic technique which is applicable to a wide range of problems, including facial recognition. Previous research has shown that a similar facial recognition technique yields good results when applied to metamorphic malware detection. We present experimental results and we analyze the effectiveness and efficiency …

Predictive Handling Of Asynchronous Concept Drifts In Distributed Environments, Hock Hee Ang, Vivek Gopalkrishnan, Indre Zliobaite, Mykola Pechenizkiy, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

In a distributed computing environment, peers collaboratively learn to classify concepts of interest from each other. When external changes happen and their concepts drift, the peers should adapt to avoid increase in misclassification errors. The problem of adaptation becomes more difficult when the changes are asynchronous, i.e., when peers experience drifts at different times. We address this problem by developing an ensemble approach, PINE, that combines reactive adaptation via drift detection, and proactive handling of upcoming changes via early warning and adaptation across the peers. With empirical study on simulated and real-world data sets, we show that PINE handles asynchronous …

Online Multi-Task Collaborative Filtering For On-The-Fly Recommender Systems, Jialei Wang, Steven C. H. Hoi, Peilin Zhao, Zhi-Yong Liu

Research Collection School Of Computing and Information Systems

Traditional batch model-based Collaborative Filtering (CF) approaches typically assume a collection of users' rating data is given a priori for training the model. They suffer from a common yet critical drawback, i.e., the model has to be re-trained completely from scratch whenever new training data arrives, which is clearly non-scalable for large real recommender systems where users' rating data often arrives sequentially and frequently. In this paper, we investigate a novel efficient and scalable online collaborative filtering technique for on-the-fly recommender systems, which is able to effectively online update the recommendation model from a sequence of rating observations. Specifically, we …

A Collusion-Resistant Conditional Access System For Flexible-Pay-Per-Channel Pay-Tv Broadcasting, Zhiguo Wan, June Liu, Rui Zhang, Robert H. Deng

Research Collection School Of Computing and Information Systems

Pay-TV Broadcasting system, an extensively de- ployed application, charges its subscribers when receiving the broadcasted video. A conditional access system (CAS) ensures security for the Pay-TV broadcasting system, which is designed to control TV channel/program access to only authorized subscribers. There are mainly three CAS models: pay-per-channel (PPC), pay-per-view (PPV), and flexible-pay-per-channel (F- PPC). F-PPC is a novel model which combines the properties and advantages of both PPC and PPV. Several key management schemes with four-level hierarchical key structure have been proposed for this model. In this paper, we point out a severe security weakness of these schemes against collusion …

Merged Aggregate Nearest Neighbor Query Processing In Road Networks, Weiwei Sun, Chong Chen, Baihua Zheng, Chunan Chen, Liang Zhu

Research Collection School Of Computing and Information Systems

Aggregate nearest neighbor query, which returns a common interesting point that minimizes the aggregate distance for a given query point set, is one of the most important operations in spatial databases and their application domains. This paper addresses the problem of finding the aggregate nearest neighbor for a merged set that consists of the given query point set and multiple points needed to be selected from a candidate set, which we name as merged aggregate nearest neighbor(MANN) query. This paper proposes an effective algorithm to process MANN query in road networks based on our pruning strategies. Extensive experiments are conducted …

Accurate Developer Recommendation For Bug Resolution, Xin Xia, David Lo, Xinyu Wang, Bo Zhou

Research Collection School Of Computing and Information Systems

Bug resolution refers to the activity that developers perform to diagnose, fix, test, and document bugs during software development and maintenance. It is a collaborative activity among developers who contribute their knowledge, ideas, and expertise to resolve bugs. Given a bug report, we would like to recommend the set of bug resolvers that could potentially contribute their knowledge to fix it. We refer to this problem as developer recommendation for bug resolution. In this paper, we propose a new and accurate method named DevRec for the developer recommendation problem. DevRec is a composite method which performs two kinds of analysis: …

Creating Adaptive Quests To Support Personalized Learning Experiences When Learning Software Languages, Chris Boesch, Sandra Boesch

Research Collection School Of Computing and Information Systems

Over the past three years the authors have been developing and refining an online practicing platform called SingPath, which enables users to practice writing code in various software languages. The most recent feature to be released is a Quest mode that encourages users by showing short video clips each time a user solves five problems. In addition, users are able to choose whether to play through these quests on easy, medium, or hard levels of difficulty. The ability for users to customize their game play enables them to modify the difficulty of the experience and ideally self-regulate how frustrating or …

Automatic Recovery Of Root Causes From Bug-Fixing Changes, Ferdian Thung, David Lo, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

No abstract provided.

A Unified Model For Topics, Events And Users On Twitter, Qiming Diao, Jing Jiang

Research Collection School Of Computing and Information Systems

With the rapid growth of social media, Twitter has become one of the most widely adopted platforms for people to post short and instant message. On the one hand, people tweets about their daily lives, and on the other hand, when major events happen, people also follow and tweet about them. Moreover, people’s posting behaviors on events are often closely tied to their personal interests. In this paper, we try to model topics, events and users on Twitter in a unified way. We propose a model which combines an LDA-like topic model and the Recurrent Chinese Restaurant Process to capture …