Computer Sciences Commons^™

An Empirical Study Of Off-Line Configuration And On-Line Adaptation In Operator Selection, Zhi Yuan, Stephanus Daniel Handoko, Duc Thien Nguyen, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Automating the process of finding good parameter settings is important in the design of high-performing algorithms. These automatic processes can generally be categorized into off-line and on-line methods. Off-line configuration consists in learning and selecting the best setting in a training phase, and usually fixes it while solving an instance. On-line adaptation methods on the contrary vary the parameter setting adaptively during each algorithm run. In this work, we provide an empirical study of both approaches on the operator selection problem, explore the possibility of varying parameter value by a non-adaptive distribution tuned off-line, and incorporate the off-line with on-line …

Integrating Visual Mnemonics And Input Feedback With Passphrases To Improve The Usability And Security Of Digital Authentication, Kevin Juang

All Dissertations

The need for both usable and secure authentication is more pronounced than ever before. Security researchers and professionals will need to have a deep understanding of human factors to address these issues. Due to their ubiquity, recoverability, and low barrier of entry, passwords remain the most common means of digital authentication. However, fundamental human nature dictates that it is exceedingly difficult for people to generate secure passwords on their own. System-generated random passwords can be secure but are often unusable, which is why most passwords are still created by humans. We developed a simple system for automatically generating mnemonic phrases …

Software Porting Of A 3d Reconstruction Algorithm To Razorcam Embedded System On Chip, Kevin Curtis Gunn

Graduate Theses and Dissertations

A method is presented to calculate depth information for a UAV navigation system from Keypoints in two consecutive image frames using a monocular camera sensor as input and the OpenCV library. This method was first implemented in software and run on a general-purpose Intel CPU, then ported to the RazorCam Embedded Smart-Camera System and run on an ARM CPU onboard the Xilinx Zynq-7000. The results of performance and accuracy testing of the software implementation are then shown and analyzed, demonstrating a successful port of the software to the RazorCam embedded system on chip that could potentially be used onboard a …

Reducing Carbon Emission Of Ocean Shipments By Optimizing Container Size Selection, Edwin Lik Ming Chong, Nang Laik Ma, Kar Way Tan

Research Collection School Of Computing and Information Systems

Human’s impact on earth through global warming is more or less an accepted fact. Ocean freight is estimated to contribute 4-5% of global carbon emissions and manufacturing companies can aid in reducing this amount. Many companies that ship goods through full container loads do not have the capabilities to ensure the containers they are using minimizes their carbon footprint. One of the reasons is the choice of non-ideal container sizes for their shipments. This paper provides a mathematical model to minimize companies’ shipping carbon footprints by selecting the ideal container sizes appropriate for their shipment volumes. Using data from a …

Hybrid Metaheuristics For Solving The Quadratic Assignment Problem And The Generalized Quadratic Assignment Problem, Aldy Gunawan, Kien Ming Ng, Kim Leng Poh, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

This paper presents a hybrid metaheuristic for solving the Quadratic Assignment Problem (QAP). The proposed algorithm involves using the Greedy Randomized Adaptive Search Procedure (GRASP) to construct an initial solution, and then using a hybrid Simulated Annealing and Tabu Search (SA-TS) algorithm to further improve the solution. Experimental results show that the hybrid metaheuristic is able to obtain good quality solutions for QAPLIB test problems within reasonable computation time. The proposed algorithm is extended to solve the Generalized Quadratic Assignment Problem (GQAP), with an emphasis on modelling and solving a practical problem, namely an examination timetabling problem. We found that …

Interpolating Beach Profile Data Using Linear And Non-Linear Functions, Lance Calloway Croft

USF Tampa Graduate Theses and Dissertations

ABSTRACT

Beach and nearshore surveys are conducted in a variety of ways, the most commonly used being the level-and-transit method; because it is inexpensive, time conducive and highly accurate. Specifically, beach surveys are conducted to better understand cross-shore, long-shore sediment transport processes, as well as to quantify volume changes, which are used to evaluate beach performance. In this study, a section of the beach on Sand Key, FL was surveyed using rod-and-transit. In addition to the commonly used linear data analysis, a non-linear analysis was conducted using NURBS (Non-Uniform Rational B-Splines).

Survey data was collected within a short time window …

Is Your Ontology As Hard As You Think? Rewriting Ontologies Into Simpler Dls, David Carral, Cristina Feier, Ana Armas Romero, Bernardo Cuenca-Grau, Pascal Hitzler, Ian Horrocks

Computer Science and Engineering Faculty Publications

We investigate cases where an ontology expressed in a seemingly hard DL can be polynomially reduced to one in a simpler logic, while preserving reasoning outcomes for classification and fact entailment. Our transformations target the elimination of inverse roles, universal and existential restrictions, and in the best case allow us to rewrite the given ontology into one of the OWL 2 profiles. Even if an ontology cannot be fully rewritten into a profile, in many cases our transformations allow us to exploit further optimisation techniques. Moreover, the elimination of some out-of-profile axioms can improve the performance of modular reasoners, such …

A Knowledge Discovery Approach For The Detection Of Power Grid State Variable Attacks, Nathan Wallace

Doctoral Dissertations

As the level of sophistication in power system technologies increases, the amount of system state parameters being recorded also increases. This data not only provides an opportunity for monitoring and diagnostics of a power system, but it also creates an environment wherein security can be maintained. Being able to extract relevant information from this pool of data is one of the key challenges still yet to be obtained in the smart grid. The potential exists for the creation of innovative power grid cybersecurity applications, which harness the information gained from advanced analytics. Such analytics can be based on the extraction …

Accurate Local Estimation Of Geo-Coordinates For Social Media Posts, Derek Doran, Swapna S. Gokhale, Aldo Dagnino

Computer Science and Engineering Faculty Publications

Associating geo-coordinates with the content of social media posts can enhance many existing applications and services and enable a host of new ones. Unfortunately, a majority of social media posts are not tagged with geo-coordinates. Even when location data is available, it may be inaccurate, very broad or sometimes fictitious. Contemporary location estimation approaches based on analyzing the content of these posts can identify only broad areas such as a city, which limits their usefulness. To address these shortcomings, this paper proposes a methodology to narrowly estimate the geo-coordinates of social media posts with high accuracy. The methodology relies solely …

Paxos Based Directory Updates For Geo-Replicated Cloud Storage, Srivathsava Rangarajan

Open Access Theses

Modern cloud data stores (e.g., Spanner, Cassandra) replicate data across geographically distributed data centers for availability, redundancy and optimized latencies.^ An important class of cloud data stores involves the use of directories to track the location of individual data objects. Directory-based datastores allow flexible data placement, and the ability to adapt placement in response to changing workload dynamics. However, a key challenge is maintaining and updating the directory state when replica placement changes.^ In this thesis, we present the design and implementation of a system to address the problem of correctly updating these directories. Our system is built around JPaxos, …

Tracking Dynamic Construction Objects ---A Key Node Modeling Approach Using Color-Depth Cameras, Chenxi Yuan

Open Access Theses

A construction site presents a dynamic scenario. Locations of multiple objects are continuously changing and a lot of objects enter and exit the site in high frequencies. Meanwhile a construction activity consists of a large amount of stochastic operations, many uncertainties occur when making decisions. Believing that detecting, locating and tracking dynamic construction objects in real time improve construction productivity and enhance construction safety, a large number of studies have applied a variety of sensing technologies to construction sites. Hybrid image-point cloud sensing technologies, such as color-depth cameras, have a great potential in achieving real time object recognition and tracking …

Click-Through-Based Cross-View Learning For Image Search, Yingwei Pan, Ting Yao, Tao Mei, Houqiang Li, Chong-Wah Ngo, Yong Rui

Research Collection School Of Computing and Information Systems

One of the fundamental problems in image search is to rank image documents according to a given textual query. Existing search engines highly depend on surrounding texts for ranking images, or leverage the query-image pairs annotated by human labelers to train a series of ranking functions. However, there are two major limitations: 1) the surrounding texts are often noisy or too few to accurately describe the image content, and 2) the human annotations are resourcefully expensive and thus cannot be scaled up. We demonstrate in this paper that the above two fundamental challenges can be mitigated by jointly exploring the …

Creating Autonomous Adaptive Agents In A Real-Time First-Person Shooter Computer Game, Di Wang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Games are good test-beds to evaluate AI methodologies. In recent years, there has been a vast amount of research dealing with real-time computer games other than the traditional board games or card games. This paper illustrates how we create agents by employing FALCON, a self-organizing neural network that performs reinforcement learning, to play a well-known first-person shooter computer game called Unreal Tournament. Rewards used for learning are either obtained from the game environment or estimated using the temporal difference learning scheme. In this way, the agents are able to acquire proper strategies and discover the effectiveness of different weapons without …

El-Ifying Ontologies, David Carral, Cristina Feier, Bernardo Cuenca Grau, Pascal Hitzler, Ian Horrocks

Computer Science and Engineering Faculty Publications

The OWL 2 profiles are fragments of the ontology language OWL 2 for which standard reasoning tasks are feasible in polynomial time. Many OWL ontologies, however, contain a typically small number of out-of-profile axioms, which may have little or no influence on reasoning outcomes. We investigate techniques for rewriting axioms into the EL and RL profiles of OWL 2. We have tested our techniques on both classification and data reasoning tasks with encouraging results.

Ultimate Codes: Near-Optimal Mds Array Codes For Raid-6, Zhijie Huang, Hong Jiang, Chong Wang, Ke Zhou, Yuhong Zhao

School of Computing: Technical Reports

As modern storage systems have grown in size and complexity, RAID-6 is poised to replace RAID-5 as the dominant form of RAID architectures due to its ability to protect against double disk failures. Many excellent erasure codes specially designed for RAID-6 have emerged in recent years. However, all of them have limitations. In this paper, we present a class of near perfect erasure codes for RAID-6, called the Ultimate codes. These codes encode, update and decode either optimally or nearly optimally, regardless of what the code length is. This implies that utilizing these codes we can build highly efficient and …

S-Code: Lowest Density Mds Array Codes For Raid-6, Zhijie Huang, Hong Jiang, Ke Zhou, Yuhong Zhao, Chong Wang

School of Computing: Technical Reports

RAID, a storage architecture designed to exploit I/O parallelism and provide data reliability, has been deployed widely in computing systems as a storage building block. In large scale storage systems, in particular, RAID-6 is gradually replacing RAID-5 as the dominant form of disk arrays due to its capability of tolerating concurrent failures of any two disks. MDS (maximum distance separable) array codes are the most popular erasure codes that can be used for implementing RAID-6, since they enable optimal storage efficiency and efficient encoding and decoding algorithms. In this paper, we propose a new class of MDS array codes called …

Influences Of Influential Users: An Empirical Study Of Music Social Network, Jing Ren, Zhiyong Cheng, Jialie Shen, Feida Zhu

Research Collection School Of Computing and Information Systems

Influential user can play a crucial role in online social networks. This paper documents an empirical study aiming at exploring the effects of influential users in the context of music social network. To achieve this goal, music diffusion graph is developed to model how information propagates over network. We also propose a heuristic method to measure users' influences. Using the real data from Last. fm, our empirical test demonstrates key effects of influential users and reveals limitations of existing influence identification/characterization schemes.

Querie: Collaborative Database Exploration, Magdalini Eirinaki, Suju Abraham, Neoklis Polyzotis, Naushin Shaikh

Faculty Publications

No abstract provided.

Grounded Ontology – A Proposed Methodology For Emergent Ontology Engineering, Syed Irfan Nabi, Zaheeruddin Asif

Business Review

This research posits that a domain ontology developed using text-coding technique contributes in conceptualizing and representing state-of-the-art as given by published research in a particular domain. The motivation behind this research is to provide means for creating a better understanding among the researchers through ontology that would present a clearer picture of any domain of interest. However, a general observation on ontology engineering methods is the domination of personal perspective of ontology developer and/or expert in the resultant ontology. Current ontology engineering methods bestow a primary role to ontology developer. Ontology thus developed is heavily biased towards the domain expert’s …

Understanding The Paradigm Shift To Computational Social Science In The Presence Of Big Data, Ray M. Chang, Robert J. Kauffman, Young Ok Kwon

Research Collection School Of Computing and Information Systems

The era of big data has created new opportunities for researchers to achieve high relevance and impact amid changes and transformations in how we study social science phenomena. With the emergence of new data collection technologies, advanced data mining and analytics support, there seems to be fundamental changes that are occurring with the research questions we can ask, and the research methods we can apply. The contexts include social networks and blogs, political discourse, corporate announcements, digital journalism, mobile telephony, home entertainment, online gaming, financial services, online shopping, social advertising, and social commerce. The changing costs of data collection and …

Decentralized Stochastic Planning With Anonymity In Interactions, Pradeep Varakantham, Yossiri Adulyasak, Patrick Jaillet

Research Collection School Of Computing and Information Systems

In this paper, we solve cooperative decentralized stochastic planning problems, where the interactions between agents (specified using transition and reward functions) are dependent on the number of agents (and not on the identity of the individual agents) involved in the interaction. A collision of robots in a narrow corridor, defender teams coordinating patrol activities to secure a target, etc. are examples of such anonymous interactions. Formally, we consider problems that are a subset of the well known Decentralized MDP (DEC-MDP) model, where the anonymity in interactions is specified within the joint reward and transition functions. In this paper, not only …

Streets: Game-Theoretic Traffic Patrolling With Exploration And Exploitation, Matthew Brown, Sandhya Saisubramanian, Pradeep Varakantham, Milind Tambe

Research Collection School Of Computing and Information Systems

To dissuade reckless driving and mitigate accidents, cities deploy resources to patrol roads. In this paper, we present STREETS, an application developed for the city of Singapore, which models the problem of computing randomized traffic patrol strategies as a defenderattacker Stackelberg game. Previous work on Stackelberg security games has focused extensively on counterterrorism settings. STREETS moves beyond counterterrorism and represents the first use of Stackelberg games for traffic patrolling, in the process providing a novel algorithm for solving such games that addresses three major challenges in modeling and scale-up. First, there exists a high degree of unpredictability in travel times …

Decentralized Multi-Agent Reinforcement Learning In Average-Reward Dynamic Dcops, Duc Thien Nguyen, William Yeoh, Hoong Chuin Lau, Shlomo Zilberstein, Chongjie Zhang

Research Collection School Of Computing and Information Systems

Researchers have introduced the Dynamic Distributed Constraint Optimization Problem (Dynamic DCOP) formulation to model dynamically changing multi-agent coordination problems, where a dynamic DCOP is a sequence of (static canonical) DCOPs, each partially different from the DCOP preceding it. Existing work typically assumes that the problem in each time step is decoupled from the problems in other time steps, which might not hold in some applications. Therefore, in this paper, we make the following contributions: (i) We introduce a new model, called Markovian Dynamic DCOPs (MD-DCOPs), where the DCOP in the next time step is a function of the value assignments …

Reinforcement Learning For Adaptive Operator Selection In Memetic Search Applied To Quadratic Assignment Problem, Stephanus Daniel Handoko, Duc Thien Nguyen, Zhi Yuan, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Memetic search is well known as one of the state-of-the-art metaheuristics for finding high-quality solutions to NP-hard problems. Its performance is often attributable to appropriate design, including the choice of its operators. In this paper, we propose a Markov Decision Process model for the selection of crossover operators in the course of the evolutionary search. We solve the proposed model by a Q-learning method. We experimentally verify the efficacy of our proposed approach on the benchmark instances of Quadratic Assignment Problem.

Idpal – A Partially-Adiabatic Energy-Efficient Logic Family: Theory And Applications To Secure Computing, Mihail T. Cutitaru

Electrical & Computer Engineering Theses & Dissertations

Low-power circuits and issues associated with them have gained a significant amount of attention in recent years due to the boom in portable electronic devices. Historically, low-power operation relied heavily on technology scaling and reduced operating voltage, however this trend has been slowing down recently due to the increased power density on chips. This dissertation introduces a new very-low power partially-adiabatic logic family called Input-Decoupled Partially-Adiabatic Logic (IDPAL) with applications in low-power circuits. Experimental results show that IDPAL reduces energy usage by 79% compared to equivalent CMOS implementations and by 25% when compared to the best adiabatic implementation. Experiments ranging …

Meshless Mechanics And Point-Based Visualization Methods For Surgical Simulations, Rifat Aras

Computational Modeling & Simulation Engineering Theses & Dissertations

Computer-based modeling and simulation practices have become an integral part of the medical education field. For surgical simulation applications, realistic constitutive modeling of soft tissue is considered to be one of the most challenging aspects of the problem, because biomechanical soft-tissue models need to reflect the correct elastic response, have to be efficient in order to run at interactive simulation rates, and be able to support operations such as cuts and sutures.

Mesh-based solutions, where the connections between the individual degrees of freedom (DoF) are defined explicitly, have been the traditional choice to approach these problems. However, when the problem …

A Framework For Web Object Self-Preservation, Charles L. Cartledge

Computer Science Theses & Dissertations

We propose and develop a framework based on emergent behavior principles for the long-term preservation of digital data using the web infrastructure. We present the development of the framework called unsupervised small-world (USW) which is at the nexus of emergent behavior, graph theory, and digital preservation. The USW algorithm creates graph based structures on the Web used for preservation of web objects (WOs). Emergent behavior activities, based on Craig Reynolds’ “boids” concept, are used to preserve WOs without the need for a central archiving authority. Graph theory is extended by developing an algorithm that incrementally creates small-world graphs. Graph theory …

High Dimensional Data Set Analysis Using A Large-Scale Manifold Learning Approach, Loc Tran

Electrical & Computer Engineering Theses & Dissertations

Because of technological advances, a trend occurs for data sets increasing in size and dimensionality. Processing these large scale data sets is challenging for conventional computers due to computational limitations. A framework for nonlinear dimensionality reduction on large databases is presented that alleviates the issue of large data sets through sampling, graph construction, manifold learning, and embedding. Neighborhood selection is a key step in this framework and a potential area of improvement. The standard approach to neighborhood selection is setting a fixed neighborhood. This could be a fixed number of neighbors or a fixed neighborhood size. Each of these has …

Preliminary Test Of A Real-Time, Interactive Silent Speech Interface Based On Electromagnetic Articulograph, Jun Wang, Ashok Samal, Jordan R. Green

School of Computing: Conference and Workshop Papers

A silent speech interface (SSI) maps articulatory movement data to speech output. Although still in experimental stages, silent speech interfaces hold significant potential for facilitating oral communication in persons after laryngectomy or with other severe voice impairments. Despite the recent efforts on silent speech recognition algorithm development using offline data analysis, online test of SSIs have rarely been conducted. In this paper, we present a preliminary, online test of a real-time, interactive SSI based on electromagnetic motion tracking. The SSI played back synthesized speech sounds in response to the user’s tongue and lip movements. Three English talkers participated in this …

From The Editor-In-Chief, Ibrahim A. Baggili

Journal of Digital Forensics, Security and Law

We are proud to share with you this special edition issue of the JDFSL. This year, JDFSL partnered with both the 6th International Conference on Digital Forensics and Cyber Crime (ICDF2C) and Systematic Approaches to Digital Forensic Engineering (SADFE)–two prominent conferences in our field that were co-hosted. Fifty-three papers were submitted, and the Technical Program Committee accepted only 17 after a rigorous review process.