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Theory and Algorithms

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Articles 1501 - 1530 of 2151

Full-Text Articles in Computer Sciences

Verifying Monadic Second-Order Properties Of Graph Programs, Christopher M. Poskitt, Detlef Plump Jul 2014

Verifying Monadic Second-Order Properties Of Graph Programs, Christopher M. Poskitt, Detlef Plump

Research Collection School Of Computing and Information Systems

The core challenge in a Hoare- or Dijkstra-style proof system for graph programs is in defining a weakest liberal precondition construction with respect to a rule and a postcondition. Previous work addressing this has focused on assertion languages for first-order properties, which are unable to express important global properties of graphs such as acyclicity, connectedness, or existence of paths. In this paper, we extend the nested graph conditions of Habel, Pennemann, and Rensink to make them equivalently expressive to monadic second-order logic on graphs. We present a weakest liberal precondition construction for these assertions, and demonstrate its use in verifying …


A Novel Algorithm Based On Visual Saliency Attention For Localization And Segmentation In Rapidly-Stained Leukocyte Images, Xin Zheng, Yong Wang, Guoyou Wang, Zhong Chen Jul 2014

A Novel Algorithm Based On Visual Saliency Attention For Localization And Segmentation In Rapidly-Stained Leukocyte Images, Xin Zheng, Yong Wang, Guoyou Wang, Zhong Chen

Research Collection School Of Computing and Information Systems

In this paper, we propose a fast hierarchical framework of leukocyte localization and segmentation in rapidly-stained leukocyte images (RSLI) with complex backgrounds and varying illumination. The proposed framework contains two main steps. First, a nucleus saliency model based on average absolute difference is built, which locates each leukocyte precisely while effectively removes dyeing impurities and erythrocyte fragments. Secondly, two different schemes are presented for segmenting the nuclei and cytoplasm respectively. As for nuclei segmentation, to solve the overlap problem between leukocytes, we extract the nucleus lobes first and further group them. The lobes extraction is realized by the histogram-based contrast …


Idpal – A Partially-Adiabatic Energy-Efficient Logic Family: Theory And Applications To Secure Computing, Mihail T. Cutitaru Jul 2014

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 …


A Simple Polynomial-Time Randomized Distributed Algorithm For Connected Row Convex Constraints, T. K. Satish Kumar, Nguyen Duc Thien, William Yeoh, Sven Koenig Jul 2014

A Simple Polynomial-Time Randomized Distributed Algorithm For Connected Row Convex Constraints, T. K. Satish Kumar, Nguyen Duc Thien, William Yeoh, Sven Koenig

Research Collection School Of Computing and Information Systems

In this paper, we describe a simple randomized algorithm that runs in polynomial time and solves connected row convex (CRC) constraints in distributed settings. CRC constraints generalize many known tractable classes of constraints like 2-SAT and implicational constraints. They can model problems in many domains including temporal reasoning and geometric reasoning, and generally speaking, play the role of "Gaussians" in the logical world. Our simple randomized algorithm for solving them in distributed settings, therefore, has a number of important applications. We support our claims through a theoretical analysis and empirical results.


Building Algorithm Portfolios For Memetic Algorithms, Mustafa Misir, Stephanus Daniel Handoko, Hoong Chuin Lau Jul 2014

Building Algorithm Portfolios For Memetic Algorithms, Mustafa Misir, Stephanus Daniel Handoko, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

The present study introduces an automated mechanism to build algorithm portfolios for memetic algorithms. The objective is to determine an algorithm set involving combinations of crossover, mutation and local search operators based on their past performance. The past performance is used to cluster algorithm combinations. Top performing combinations are then considered as the members of the set. The set is expected to have algorithm combinations complementing each other with respect to their strengths in a portfolio setting. In other words, each algorithm combination should be good at solving a certain type of problem instances such that this set can be …


Network And Energy-Aware Resource Selection Model For Opportunistic Grids, Izaias Faria, Mario Dantas, Miriam A M Capretz, Wilson Higashino Jun 2014

Network And Energy-Aware Resource Selection Model For Opportunistic Grids, Izaias Faria, Mario Dantas, Miriam A M Capretz, Wilson Higashino

Electrical and Computer Engineering Publications

Due to increasing hardware capacity, computing grids have been handling and processing more data. This has led to higher amount of energy being consumed by grids; hence the necessity for strategies to reduce their energy consumption. Scheduling is a process carried out to define in which node tasks will be executed in the grid. This process can significantly impact the global system performance, including energy consumption. This paper focuses on a scheduling model for opportunistic grids that considers network traffic, distance between input files and execution node as well as the execution node status. The model was tested in a …


Query Analyzer And Manager For Complex Event Processing As A Service, Wilson Higashino, Cedric Eichler, Miriam A M Capretz, Thierry Monteil, M. Beatriz F. Toledo, Patricia Stolf Jun 2014

Query Analyzer And Manager For Complex Event Processing As A Service, Wilson Higashino, Cedric Eichler, Miriam A M Capretz, Thierry Monteil, M. Beatriz F. Toledo, Patricia Stolf

Electrical and Computer Engineering Publications

Complex Event Processing (CEP) is a set of tools and techniques that can be used to obtain insights from high-volume, high-velocity continuous streams of events. CEP-based systems have been adopted in many situations that require prompt establishment of system diagnostics and execution of reaction plans, such as in monitoring of complex systems. This article describes the Query Analyzer and Manager (QAM) module, a first effort toward the development of a CEP as a Service (CEPaaS) system. This module is responsible for analyzing user-defined CEP queries and for managing their execution in distributed cloud-based environments. Using a language-agnostic internal query representation, …


Evaluation Of Particle Swarm Optimization Applied To Grid Scheduling, Wilson Higashino, Miriam A M Capretz, M. Beatriz F. Toledo Jun 2014

Evaluation Of Particle Swarm Optimization Applied To Grid Scheduling, Wilson Higashino, Miriam A M Capretz, M. Beatriz F. Toledo

Electrical and Computer Engineering Publications

The problem of scheduling independent users’ jobs to resources in Grid Computing systems is of paramount importance. This problem is known to be NP-hard, and many techniques have been proposed to solve it, such as heuristics, genetic algorithms (GA), and, more recently, particle swarm optimization (PSO). This article aims to use PSO to solve grid scheduling problems, and compare it with other techniques. It is shown that many often-overlooked implementation details can have a huge impact on the performance of the method. In addition, experiments also show that the PSO has a tendency to stagnate around local minima in high-dimensional …


Contextual Anomaly Detection In Big Sensor Data, Michael Hayes, Miriam A M Capretz Jun 2014

Contextual Anomaly Detection In Big Sensor Data, Michael Hayes, Miriam A M Capretz

Electrical and Computer Engineering Publications

Performing predictive modelling, such as anomaly detection, in Big Data is a difficult task. This problem is compounded as more and more sources of Big Data are generated from environmental sensors, logging applications, and the Internet of Things. Further, most current techniques for anomaly detection only consider the content of the data source, i.e. the data itself, without concern for the context of the data. As data becomes more complex it is increasingly important to bias anomaly detection techniques for the context, whether it is spatial, temporal, or semantic. The work proposed in this paper outlines a contextual anomaly detection …


Placing Videos On A Semantic Hierarchy For Search Result Navigation, Song Tan, Yu-Gang Jiang, Chong-Wah Ngo Jun 2014

Placing Videos On A Semantic Hierarchy For Search Result Navigation, Song Tan, Yu-Gang Jiang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Organizing video search results in a list view is widely adopted by current commercial search engines, which cannot support efficient browsing for complex search topics that have multiple semantic facets. In this article, we propose to organize video search results in a highly structured way. Specifically, videos are placed on a semantic hierarchy that accurately organizes various facets of a given search topic. To pick the most suitable videos for each node of the hierarchy, we define and utilize three important criteria: relevance, uniqueness, and diversity. Extensive evaluations on a large YouTube video dataset demonstrate the effectiveness of our approach.


Regen: Optimizing Genetic Selection Algorithms For Heterogeneous Computing, Scott Kenneth Swinkleb Winkleblack Jun 2014

Regen: Optimizing Genetic Selection Algorithms For Heterogeneous Computing, Scott Kenneth Swinkleb Winkleblack

Master's Theses

GenSel is a genetic selection analysis tool used to determine which genetic markers are informational for a given trait. Performing genetic selection related analyses is a time consuming and computationally expensive task. Due to an expected increase in the number of genotyped individuals, analysis times will increase dramatically. Therefore, optimization efforts must be made to keep analysis times reasonable.

This thesis focuses on optimizing one of GenSel’s underlying algorithms for heterogeneous computing. The resulting algorithm exposes task-level parallelism and data-level parallelism present but inaccessible in the original algorithm. The heterogeneous computing solution, ReGen, outperforms the optimized CPU implementation achieving a …


Bootstrapping Simulation-Based Algorithms With A Suboptimal Policy, Nguyen T., Silander T., Lee W., Tze-Yun Leong Jun 2014

Bootstrapping Simulation-Based Algorithms With A Suboptimal Policy, Nguyen T., Silander T., Lee W., Tze-Yun Leong

Research Collection School Of Computing and Information Systems

Finding optimal policies for Markov Decision Processes with large state spaces is in general intractable. Nonetheless, simulation-based algorithms inspired by Sparse Sampling (SS) such as Upper Confidence Bound applied in Trees (UCT) and Forward Search Sparse Sampling (FSSS) have been shown to perform reasonably well in both theory and practice, despite the high computational demand. To improve the efficiency of these algorithms, we adopt a simple enhancement technique with a heuristic policy to speed up the selection of optimal actions. The general method, called Aux, augments the look-ahead tree with auxiliary arms that are evaluated by the heuristic policy. In …


Global Immutable Region Computation, Jilian Zhang, Kyriakos Mouratidis, Hwee Hwa Pang Jun 2014

Global Immutable Region Computation, Jilian Zhang, Kyriakos Mouratidis, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

A top-k query shortlists the k records in a dataset that best match the user's preferences. To indicate her preferences, the user typically determines a numeric weight for each data dimension (i.e., attribute). We refer to these weights collectively as the query vector. Based on this vector, each data record is implicitly mapped to a score value (via a weighted sum function). The records with the k largest scores are reported as the result. In this paper we propose an auxiliary feature to standard top-k query processing. Specifically, we compute the maximal locus within which the query vector incurs no …


Fault Attacks On Hyperelliptic Curve Discrete Logarithm Problem Over Binary Field, Mingqiang Wang, Haiyang Xue, Tao Zhan Jun 2014

Fault Attacks On Hyperelliptic Curve Discrete Logarithm Problem Over Binary Field, Mingqiang Wang, Haiyang Xue, Tao Zhan

Research Collection School Of Computing and Information Systems

In this paper, we present invalid-curve attacks that apply to the hyperelliptic curve scalar multiplication (HECSM) algorithm proposed by Avanzi et al. on the genus 2 hyperelliptic curve over binary field. We observe some new properties of the HECSM. Our attacks are based on these new properties and the observation that the parameters f 0 and f 1 of the hyperelliptic curve equation are not utilized for the HECSM. We show that with different “values” for curve parameters f 0, f 1, there exsit cryptographically weak groups in the Koblitz hyperelliptic curve. Also, we compute the theoretical probability of getting …


Introducing Non-Determinism To The Parallel C Compiler, Rowen Concepcion Jun 2014

Introducing Non-Determinism To The Parallel C Compiler, Rowen Concepcion

Electronic Theses, Projects, and Dissertations

The Planguages project is the birthplace of the Planguage programming
approach, which is designed to alleviate the task of writing parallel
programs and harness massively parallel computers and networks of workstations.


Planguage has two existing translators, Parallel C (PC) and Pfortran,
which is used for their base languages, C and Fortran77. The translators
work with MPI (Message Passing Interface) for communications. SOS
(ipStreams, Overlapping and Shortcutting), a function library that supports
the three named functionalities, can be used to further optimize parallel algorithms.


This project is the next step in the continuing project of updating
the PC Compiler. The goal …


Procedural Music Generation And Adaptation Based On Game State, Timothey Andrew Adam Jun 2014

Procedural Music Generation And Adaptation Based On Game State, Timothey Andrew Adam

Master's Theses

Video game developers attempt to convey moods to emphasize their game's narrative. Events that occur within the game usually convey success or failure in some way meaningful to the story's progress. Ideally, when these events occur, the intended change in mood should be perceivable to the player. One way of doing so is to change the music. This requires musical tracks to represent many possible moods, states and game events. This can be very taxing on composers, and encoding the control flow (when to transition) of the tracks can prove to be tricky as well.

This thesis presents AUD.js, a …


Generalized Mandelbrot Sets, Aaron Schlenker May 2014

Generalized Mandelbrot Sets, Aaron Schlenker

Undergraduate Honors Thesis Collection

A complex point Z0 is defined to be a member of the famous Mandelbrot set fractal when the iterative process using the function Z2 stays bounded when applied to Z0. We investigate what happens if we change the iterative process so that Z2 is now composed with, for example, a Mobius transformation, indexed on a parameter a. The Mandelbrot set corresponds to a = O. What happens when we change a = 0 to other values, repeating the iterative process and then drawing the sets? Do these Generalized Mandelbrot sets have similar properties to …


Decaf: A New Event Detection Logic For The Purpose Of Fusing Delineated-Continuous Spatial Information, Kerry Q. Hart May 2014

Decaf: A New Event Detection Logic For The Purpose Of Fusing Delineated-Continuous Spatial Information, Kerry Q. Hart

School of Computing: Dissertations, Theses, and Student Research

Geospatial information fusion is the process of synthesizing information from complementary data sources located at different points in space and time. Spatial phenomena are often measured at discrete locations by sensor networks, technicians, and volunteers; yet decisions often require information about locations where direct measurements do not exist. Traditional methods assume the spatial phenomena to be either discrete or continuous, an assumption that underlies and informs all subsequent analysis. Yet certain phenomena defy this dichotomy, alternating as they move across spatial and temporal scales. Precipitation, for example, appears continuous at large scales, but it can be temporally decomposed into discrete …


Using Statistical Methods To Determine Geolocation Via Twitter, Christopher M. Wright May 2014

Using Statistical Methods To Determine Geolocation Via Twitter, Christopher M. Wright

Masters Theses & Specialist Projects

With the ever expanding usage of social media websites such as Twitter, it is possible to use statistical inquires to form a geographic location of a person using solely the content of their tweets. According to a study done in 2010, Zhiyuan Cheng, was able to detect a location of a Twitter user within 100 miles of their actual location 51% of the time. While this may seem like an already significant find, this study was done while Twitter was still finding its ground to stand on. In 2010, Twitter had 75 million unique users registered, as of March 2013, …


Persistent Community Detection In Dynamic Social Networks, Siyuan Liu, Shuhui Wang, Ramayya Krishnan May 2014

Persistent Community Detection In Dynamic Social Networks, Siyuan Liu, Shuhui Wang, Ramayya Krishnan

Research Collection School Of Computing and Information Systems

While community detection is an active area of research in social network analysis, little effort has been devoted to community detection using time-evolving social network data. We propose an algorithm, Persistent Community Detection (PCD), to identify those communities that exhibit persistent behavior over time, for usage in such settings. Our motivation is to distinguish between steady-state network activity, and impermanent behavior such as cascades caused by a noteworthy event. The results of extensive empirical experiments on real-life big social networks data show that our algorithm performs much better than a set of baseline methods, including two alternative models and the …


Generating Combinatorial Objects- A New Perspective, Alexander Chizoma Nwala May 2014

Generating Combinatorial Objects- A New Perspective, Alexander Chizoma Nwala

Computer Science Theses & Dissertations

Combinatorics is the science of "possibilities." This definition, while not formal is a fair statement because all too often, in order to gain insight into the solution of many counting problems, we explore the possibilities. In some cases we seek to know how many options, while in other cases we seek to enumerate or list the options. Irrespective of the scenario, combinatorics plays a vital role today. In many instances such as exploring the options for choosing a new password for a combination lock, we employ combinatorics. In considering the possible license plate permutations for a state, or to see …


Mechanisms For Arranging Ride Sharing And Fare Splitting For Last-Mile Travel Demands, Shih-Fen Cheng, Duc Thien Nguyen, Hoong Chuin Lau May 2014

Mechanisms For Arranging Ride Sharing And Fare Splitting For Last-Mile Travel Demands, Shih-Fen Cheng, Duc Thien Nguyen, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

A great challenge of city planners is to provide efficient and effective connection service to travelers using public transportation system. This is commonly known as the last-mile problem and is critical in promoting the utilization of public transportation system. In this paper, we address the last-mile problem by considering a dynamic and demand-responsive mechanism for arranging ride sharing on a non-dedicated commercial fleet (such as taxis or passenger vans). Our approach has the benefits of being dynamic, flexible, and with low setup cost. A critical issue in such ride-sharing service is how riders should be grouped and serviced, and how …


Didn’T You See My Message?: Predicting Attentiveness To Mobile Instant Messages, Martin Pielot, Rodrigo De Oliveira, Haewoon Kwak, Nuria. Oliver May 2014

Didn’T You See My Message?: Predicting Attentiveness To Mobile Instant Messages, Martin Pielot, Rodrigo De Oliveira, Haewoon Kwak, Nuria. Oliver

Research Collection School Of Computing and Information Systems

Mobile instant messaging (e.g., via SMS or WhatsApp) often goes along with an expectation of high attentiveness, i.e., that the receiver will notice and read the message within a few minutes. Hence, existing instant messaging services for mobile phones share indicators of availability, such as the last time the user has been online. However, in this paper we not only provide evidence that these cues create social pressure, but that they are also weak predictors of attentiveness. As remedy, we propose to share a machine-computed prediction of whether the user will view a message within the next few minutes or …


Automatic Objects Removal For Scene Completion, Jianjun Yang, Yin Wang, Honggang Wang, Kun Hua, Wei Wang, Ju Shen Apr 2014

Automatic Objects Removal For Scene Completion, Jianjun Yang, Yin Wang, Honggang Wang, Kun Hua, Wei Wang, Ju Shen

Computer Science Faculty Publications

With the explosive growth of Web-based cameras and mobile devices, billions of photographs are uploaded to the Internet. We can trivially collect a huge number of photo streams for various goals, such as 3D scene reconstruction and other big data applications. However, this is not an easy task due to the fact the retrieved photos are neither aligned nor calibrated. Furthermore, with the occlusion of unexpected foreground objects like people, vehicles, it is even more challenging to find feature correspondences and reconstruct realistic scenes. In this paper, we propose a structure-based image completion algorithm for object removal that produces visually …


Multi-Threaded Automatic Integration Using Openmp And Cuda, Rida Assaf Apr 2014

Multi-Threaded Automatic Integration Using Openmp And Cuda, Rida Assaf

Masters Theses

Problems in many areas give rise to computationally expensive integrals that beg the need of efficient techniques to solve them, e.g., in computational finance for the modeling of cash flows; for the computation of Feynman loop integrals in high energy physics; and in stochastic geometry with applications to computer graphics.

We demonstrate feasible numerical approaches in the framework of the PARINT multivariate integration package. The parallel environment is provided by the cluster of the High Performance Computational Science (HPCS) laboratory, with 22 (16- or 32-core) nodes, NVIDIA GPUs, and Intel Xeon Phi coprocessors.

Monte Carlo integration is implemented in CUDA …


Are Timed Automata Bad For A Specification Language? Language Inclusion Checking For Timed Automata, Ting Wang, Jun Sun, Yang Liu, Xinyu Wang, Shanping Li Apr 2014

Are Timed Automata Bad For A Specification Language? Language Inclusion Checking For Timed Automata, Ting Wang, Jun Sun, Yang Liu, Xinyu Wang, Shanping Li

Research Collection School Of Computing and Information Systems

Given a timed automaton P modeling an implementation and a timed automaton S as a specification, language inclusion checking is to decide whether the language of P is a subset of that of S. It is known that this problem is undecidable and “this result is an obstacle in using timed automata as a specification language” [2]. This undecidability result, however, does not imply that all timed automata are bad for specification. In this work, we propose a zone-based semi-algorithm for language inclusion checking, which implements simulation reduction based on Anti-Chain and LU-simulation. Though it is not guaranteed to terminate, …


Machine Learning In Wireless Sensor Networks: Algorithms, Strategies, And Applications, Mohammad Abu Alsheikh, Shaowei Lin, Dusit Niyato, Hwee-Pink Tan Apr 2014

Machine Learning In Wireless Sensor Networks: Algorithms, Strategies, And Applications, Mohammad Abu Alsheikh, Shaowei Lin, Dusit Niyato, Hwee-Pink Tan

Research Collection School Of Computing and Information Systems

Wireless sensor networks (WSNs) monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in WSNs. The advantages and disadvantages of each proposed algorithm are …


A Hamming Embedding Kernel With Informative Bag-Of-Visual Words For Video Semantic Indexing, Feng Wang, Wen-Lei Zhao, Chong-Wah Ngo, Bernard Merialdo Apr 2014

A Hamming Embedding Kernel With Informative Bag-Of-Visual Words For Video Semantic Indexing, Feng Wang, Wen-Lei Zhao, Chong-Wah Ngo, Bernard Merialdo

Research Collection School Of Computing and Information Systems

In this article, we propose a novel Hamming embedding kernel with informative bag-of-visual words to address two main problems existing in traditional BoW approaches for video semantic indexing. First, Hamming embedding is employed to alleviate the information loss caused by SIFT quantization. The Hamming distances between keypoints in the same cell are calculated and integrated into the SVM kernel to better discriminate different image samples. Second, to highlight the concept-specific visual information, we propose to weight the visual words according to their informativeness for detecting specific concepts. We show that our proposed kernels can significantly improve the performance of concept …


Data Supply Chains, Tamara Kneese Mar 2014

Data Supply Chains, Tamara Kneese

Media Studies

As data moves between actors and organizations, what emerges is a data supply chain. Unlike manufacturing supply chains, transferred data is often duplicated in the process, challenging the essence of ownership. What does ethical data labor look like? How are the various stakeholders held accountable for being good data guardians? What does clean data transfer look like? What kinds of best practices can business and government put into place? What upstream rights to data providers have over downstream commercialization of their data?


Predicting Human Behavior, Tamara Kneese Mar 2014

Predicting Human Behavior, Tamara Kneese

Media Studies

Countless highly accurate predictions can be made from trace data, with varying degrees of personal or societal consequence (e.g., search engines predict hospital admission, gaming companies can predict compulsive gambling problems, government agencies predict criminal activity). Predicting human behavior can be both hugely beneficial and deeply problematic depending on the context. What kinds of predictive privacy harms are emerging? And what are the implications for systems of oversight and due process protections? For example, what are the implications for employment, health care and policing when predictive models are involved? How should varied organizations address what they can predict?