Digital Commons Network^™

Power Conservation In The Network Stack Of Wireless Sensors, Michael De Rosa

Dartmouth College Undergraduate Theses

Wireless sensor networks have recently become an incredibly active research area in the networking community. Much attention has been given to the construction of power-conserving protocols and techniques, as battery life is the one factor that prevents successful wide-scale deployment of such networks. These techniques concentrate on the optimization of network behavior, as the wireless transmission of data is the most expensive operation performed by a sensor node. Very little work has been published on the integration of such techniques, and their suitability to various application domains. This paper presents an exhaustive power consumption analysis of network stacks constructed with …

Enhancing Asynchronous Parallel Computing, Elizabeth Anne Hamon

Dartmouth College Undergraduate Theses

In applications using large amounts of data, hiding the latency inherent in accessing data far from the processor is often necessary in order to achieve high performance. Several researchers have observed that one way to address the challenge of latency is by using a common structure: in a series of passes, the program reads in the data, performs various operations on it, and writes out the data. Passes often consist of a pipeline structure composed of different stages. In order to achieve high performance, the stages are frequently overlapped, for example, by using asynchronous threads. Out-of-core parallel programs provide one …

Distributed Planning And Control For Modular Robots With Unit-Compressible Modules, Zack Butler, Daniela Rus

Computer Science Technical Reports

Self-reconfigurable robots are versatile systems consisting of large numbers of independent modules. Effective use of these systems requires parallel actuation and planning, both for efficiency and independence from a central controller. This paper presents the PacMan algorithm, a technique for distributed actuation and planning for systems with two- or three-dimensional unit-compressible modules. We give two versions of the algorithm along with correctness analysis. We also analyze the parallel actuation capability of the algorithm, showing that it will not deadlock and will avoid disconnecting the robot. We have implemented PacMan on the Crystal robot, a hardware system developed in our lab, …

A Surface-Based Approach For Classification Of 3d Neuroanatomic Structures, Li Shen, James Ford, Fillia Makedon, Andrew Saykin

Computer Science Technical Reports

We present a new framework for 3D surface object classification that combines a powerful shape description method with suitable pattern classification techniques. Spherical harmonic parameterization and normalization techniques are used to describe a surface shape and derive a dual high dimensional landmark representation. A point distribution model is applied to reduce the dimensionality. Fisher's linear discriminants and support vector machines are used for classification. Several feature selection schemes are proposed for learning better classifiers. After showing the effectiveness of this framework using simulated shape data, we apply it to real hippocampal data in schizophrenia and perform extensive experimental studies by …

A New Message-Based Protocol For Building A Platform And Language Independent Distributed Object Model, Hazem S. El Ashmawi

Archived Theses and Dissertations

Standardization of messaging topologies for communication in recent distributed object computing architectures is becoming more and more inevitable. The emergence of a structured and flexible document model as XML has made an entry point towards this goal. In this thesis, we are utilizing the flexibility of XML and the simplicity of low -level socket communication to build a generalized messaging model that provides a basis for standardization and supports interoperability among existing distributed object computing architectures. The proposed system is composed of the basic components of a distributed architecture constituting a number of broker components acting as naming services and …

Dynamic Joint Action Perception For Q-Learning Agents, Nancy Fulda, Dan A. Ventura

Faculty Publications

Q-learning is a reinforcement learning algorithm that learns expected utilities for state-action transitions through successive interactions with the environment. The algorithm's simplicity as well as its convergence properties have made it a popular algorithm for study. However, its non-parametric representation of utilities limits its effectiveness in environments with large amounts of perceptual input. For example, in multiagent systems, each agent may need to consider the action selections of its counterparts in order to learn effective behaviors. This creates a joint action space which grows exponentially with the number of agents in the system. In such situations, the Q-learning algorithm quickly …

On Detecting Bandwidth Theft Attacks And Sla Violations In Qos Networks, Sonia Fahmy, Srinivas R. Avasarala, Venkatesh Prabhakar

Department of Computer Science Technical Reports

No abstract provided.

Towards Cost-Effective On-Demand Continuous Media Service: A Peer-To- Peer Approach, Yicheng Tu, Shan Lei

Department of Computer Science Technical Reports

No abstract provided.

Recovery Performance Of Pgm With Redundancy Estimation For Proactive Fec, Sonia Fahmy, Renin M. Jegadeesan

Department of Computer Science Technical Reports

No abstract provided.

Efficient And Practical Constructions Of Ll/Sc Variables, Prasad Jayanti, Srdjan Petrovic

Computer Science Technical Reports

Over the past decade, LL/SC have emerged as the most suitable synchronization instructions for the design of lock-free algorithms. However, current architectures do not support these instructions; instead, they support either CAS or RLL/RSC (e.g. POWER4, MIPS, SPARC, IA-64). To bridge this gap, this paper presents two efficient wait-free algorithms for implementing 64-bit LL/SC objects from 64-bit CAS or RLL/RSC objects. Our first algorithm is practical: it has a small, constant time complexity (of 4 for LL and 5 for SC) and a space overhead of only 4 words per process. This algorithm uses unbounded sequence numbers. For theoretical interest, …

Ladar-Based Detection And Tracking Of Moving Objects From A Ground Vehicle At High Speeds, Chieh-Chih Wang, Charles Thorpe, Arne Suppe

Research Collection School Of Computing and Information Systems

Detection and tracking of moving objects (DATMO) in crowded urban areas from a ground vehicle at high speeds is difficult because of a wide variety of targets and uncertain pose estimation from odometry and GPS/DGPS. In this paper we present a solution of the simultaneous localization and mapping (SLAM) with DATMO problem to accomplish this task using ladar sensors and odometry. With a precise pose estimate and a surrounding map from SLAM, moving objects are detected without a priori knowledge of the targets. The interacting multiple model (IMM) estimation algorithm is used for modeling the motion of a moving object …

Using Support Vector Machines For Terrorism Information Extraction, Aixin Sun, Myo-Myo Naing, Ee Peng Lim, Wai Lam

Research Collection School Of Computing and Information Systems

Information extraction (IE) is of great importance in many applications including web intelligence, search engines, text understanding, etc. To extract information from text documents, most IE systems rely on a set of extraction patterns. Each extraction pattern is defined based on the syntactic and/or semantic constraints on the positions of desired entities within natural language sentences. The IE systems also provide a set of pattern templates that determines the kind of syntactic and semantic constraints to be considered. In this paper, we argue that such pattern templates restricts the kind of extraction patterns that can be learned by IE systems. …

Adaptive Filters For Continuous Queries Over Distributed Data Stream, Chris Olston, Jing Jiang, Jennifer Widom

Research Collection School Of Computing and Information Systems

We consider an environment where distributed data sources continuously stream updates to a centralized processor that monitors continuous queries over the distributed data. Significant communication overhead is incurred in the presence of rapid update streams, and we propose a new technique for reducing the overhead. Users register continuous queries with precision requirements at the central stream processor, which installs filters at remote data sources. The filters adapt to changing conditions to minimize stream rates while guaranteeing that all continuous queries still receive the updates necessary to provide answers of adequate precision at all times. Our approach enables applications to trade …

Image Morphological Processing, Vijayalakshmi Gaddipati

Dissertations

Mathematical Morphology with applications in image processing and analysis has been becoming increasingly important in today's technology. Mathematical Morphological operations, which are based on set theory, can extract object features by suitably shaped structuring elements. Mathematical Morphological filters are combinations of morphological operations that transform an image into a quantitative description of its geometrical structure based on structuring elements. Important applications of morphological operations are shape description, shape recognition, nonlinear filtering, industrial parts inspection, and medical image processing.

In this dissertation, basic morphological operations, properties and fuzzy morphology are reviewed. Existing techniques for solving corner and edge detection are presented. …

Image Enhancement Techniques Applied To Solar Feature Detection, Artur J. Kowalski

Dissertations

This dissertation presents the development of automatic image enhancement techniques for solar feature detection. The new method allows for detection and tracking of the evolution of filaments in solar images. Series of H-alpha full-disk images are taken in regular time intervals to observe the changes of the solar disk features. In each picture, the solar chromosphere filaments are identified for further evolution examination. The initial preprocessing step involves local thresholding to convert grayscale images into black-and-white pictures with chromosphere granularity enhanced. An alternative preprocessing method, based on image normalization and global thresholding is presented. The next step employs morphological closing …

Making Connections: Using Analogies To Enrich Understanding Of Mathematical Ideas And Biblical Truths, Ron Benbow

ACMS Conference Proceedings 2003

Recent standards and research, published by mathematics education professional organizations, place a great emphasis on “connections” in all grade levels. Through this emphasis on interrelatedness, students begin to see the subject not as a collection of separate strands, but rather as an integrated field of study. When linkages between diverse domains of knowledge are formed (by comparing, contrasting, analyzing, and applying), we have increased the likelihood that we develop deeper understandings within both domains. This paper explores some specific examples of the use of analogies to connect mathematical and Biblical concepts.

Creationism - A Viable Philosophy Of Mathematics, Jonathan Zderad

ACMS Conference Proceedings 2003

The purpose of this essay is to try to answer the ontological and epistemological question of mathematics. Specifically, "What, if any, of mathematics exists in the objective sense?" And, "How do we as humans know that our knowledge of mathematics is correct?" These questions will be investigated by looking at the applications or mathematics, the practice of mathematicians, and most telling, the content of mathematics. Mathematics, admittedly, can only go so far in answering its own philosophical questions, even when aided by recent developments in the field of logic. The overwhelming evidence, as will be shown, points toward a theistic, …

A Greater Tantalizer, Andrew Simoson

ACMS Conference Proceedings 2003

The children’s puzzle, sometimes called the Great Tantalizer, consists of four blocks each of whose faces have been colored with four colors; a solution consists in stacking the blocks so that on each stack face, all four colors appear. This article renders the puzzle as six octahedral blocks, each of which is colored with six colors, and describes a scheme to successfully stack all six.

The Search For The Real Josephus Problem, Eric Gossett

ACMS Conference Proceedings 2003

Many of the problems that mathematicians and computer scientists dearly love have been around for a long time. One such problem is known as the Josephus Problem, named after the first century Jewish historian Flavius Josephus. Josephus did not invent the problem. Instead, an event from his life served as the inspiration for the problem statement. Many current books refer to "Mathematical Recreations and Essays" by W. W. Rouse Ball [originally published in 1892] for the problem statement. The problem is quite interesting (and will be solved here). However, the story, as quoted in Bell, is not completely accurate.

Feedback Algorithm For Switch Location : Analysis Of Complexity And Application To Network Design, Yuriy S. Polyakov

Theses

An accelerated feedback algorithm to solve the single-facility minisum problem is studied with application to designing networks with the star topology. The algorithm, in which the acceleration with respect to the Weiszfeld procedure is achieved by multiplying the current Weiszfeld iterate by an accelerating feedback factor, is shown to converge faster than the accelerating procedures available in the literature. Singularities encountered in the algorithm are discussed in detail. A simple practical exception handling subroutine is developed. Several applications of the algorithm to designing computer networks with the star topology are demonstrated. Applications of the algorithm as a subroutine for multi-switch …

Uber-Claws : Unsupervised Pattern Classification For Multi-Unit Extracellular Neuronal Burst Extraction, Rama Natarajan

Theses

To further an understanding of how a neuronal population generates patterns of rhythmic activity, the temporal dynamics of the group of neurons must be formalized. Essential to this pursuit, is the ability to reliably detect and separate the classes of single-unit neuronal activity from multi-unit extracellular signals recorded in a single channel. This study proposes a unified approach to automatically detect and classify single-unit bursts, and to observe the precise onset and offset of burst activity. Existing approaches to the problem fundamentally depend on the statistics of spike waveform variability, both extrinsic and intrinsic to the neuron. In contrast, the …

Electronic Documents And Digital Signatures, Kunal Kain

Dartmouth College Master’s Theses

Often, the main motivation for using PKI in business environments is to streamline workflow, by enabling humans to digitally sign electronic documents, instead of manually signing paper ones. However, this application fails if adversaries can construct electronic documents whose viewed contents can change in useful ways, without invalidating the digital signature. In this paper, we examine the space of such attacks, and describe how many popular electronic document formats and PKI packages permit them.

A Progressive Folding Algorithm For Rna Secondary Structure Prediction, Samuel J. Stearns

Dartmouth College Master’s Theses

RNA secondary structure prediction is an area where computational techniques have shown great promise. Most RNA secondary structure prediction algorithms use dynamic programming to compute a secondary structure with minimum free energy. Energy minimization algorithms are less accurate on larger RNA molecules. One potential reason is that larger RNA molecules do not fold instantaneously. Instead, several studies show that RNA molecules fold progressively during transcription. This process could encourage the molecule to fold into a structure that is not at the global lowest energy level. Additionally, dynamic programming algorithms do not allow for a important type of structure called a …

Using Low Level Linear Memory Management For Type-Preserving Mark-Sweep Garbage Collector, Edward Wei

Dartmouth College Undergraduate Theses

Efficient low-level systems such as garbage collectors need more control over memory than safe high-level languages usually provide. Due to this constraint, garbage collectors are typically written in unsafe languages such as C. A collector of this form usually resides as a trusted primitive runtime service outside the model of the programming language. The type safety of these languages depends on the assumption that the garbage collector will not violate any typing invariants. However, no realistic systems provide proof of this assumption. A garbage collector written in a strongly typed language can guarantee not only the safety of the garbage …

An Analysis Of Convergence Properties Of The Border Gateway Protocol Using Discrete Event Simulation, Brian J. Premore

Dartmouth College Ph.D Dissertations

The Internet is an enormous internetwork formed by connecting tens of thousands of independently managed computer networks. Though the Internet has no central authority and is highly heterogeneous, a universally adopted addressing scheme---defined by the Internet Protocol (IP)---makes interaction between the individual networks possible. Complementing IP is the Border Gateway Protocol (BGP), which facilitates communication between parts of the internetwork by determining paths by which data can get from one network to any other. Just as IP is used ubiquitously as an addressing scheme, BGP is used ubiquitously for the purpose of network-to-network routing. Because BGP is universal, its well-being …

Semantic Web Process Lifecycle: Role Of Semantics In Annotation, Discovery, Composition And Orchestration, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

Simplifying Ocr Neural Networks With Oracle Learning, Tony R. Martinez, Joshua Menke

Faculty Publications

Often the best model to solve a real world problem is relatively complex. The following presents oracle learning, a method using a larger model as an oracle to train a smaller model on unlabeled data in order to obtain (1) a simpler acceptable model and (2) improved results over standard training methods on a similarly sized smaller model. In particular, this paper looks at oracle learning as applied to multi-layer perceptrons trained using standard backpropagation. For optical character recognition, oracle learning results in an 11.40% average decrease in error over direct training while maintaining 98.95% of the initial oracle accuracy.

A Noise Filtering Method Using Neural Networks, Tony R. Martinez, Xinchuan Zeng

Faculty Publications

During the data collecting and labeling process it is possible for noise to be introduced into a data set. As a result, the quality of the data set degrades and experiments and inferences derived from the data set become less reliable. In this paper we present an algorithm, called ANR (automatic noise reduction), as a filtering mechanism to identify and remove noisy data items whose classes have been mislabeled. The underlying mechanism behind ANR is based on a framework of multi-layer artificial neural networks. ANR assigns each data item a soft class label in the form of a class probability …

Authoritative Citation Knn Learning With Noisy Training Datasets, Leen-Kiat Soh, Joseph Bernadt

School of Computing: Technical Reports

In this paper, we investigate the effectiveness of Citation K-Nearest Neighbors (KNN) learning with noisy training datasets. We devise an authority measure associated with each training instance that changes based on the outcome of Citation KNN classification. The authority is increased when a citer’s classification had been right; and vice versa. We show that by modifying only these authority measures, the classification accuracy of Citation KNN improves significantly in a variety of datasets with different noise levels. We also identify the general characteristics of a dataset that affect the improvement percentages. We conclude that the new algorithm is able to …

Extending Csp To Disambiguate Linda Predicate Operations, Kyle Burke

Honors Theses

The Tuple Space communication environment is plagued by the apparent ambiguity present in the predicate operations of Linda, the programming extension used to implement Tuple Space. It bas been shown that by using a method of reasoning which describes only sequentialized traces of events, it is unclear what a failed predicate operation actually means. Using an operational semantics model of Tuple Space, an analysis of the predicate operations using a description of events occurring simultaneously has disambiguated the meanings of the failure cases. Here an algebraic model is provided, using the Communicating Sequential Process (CSP) process algebra as a base. …