Computer Sciences Commons^™

Interacting With Web Hierarchies, Saverio Perugini, Naren Ramakrishnan

Computer Science Faculty Publications

Web site interfaces are a particularly good fit for hierarchies in the broadest sense of that idea, i.e. a classification with multiple attributes, not necessarily a tree structure. Several adaptive interface designs are emerging that support flexible navigation orders, exposing and exploring dependencies, and procedural information-seeking tasks. This paper provides a context and vocabulary for thinking about hierarchical Web sites and their design. The paper identifies three features that interface to information hierarchies. These are flexible navigation orders, the ability to expose and explore dependencies, and support for procedural tasks. A few examples of these features are also provided

A Metamodel And Uml Profile For Rule-Extended Owl Dl Ontologies, Saartje Brockmans, Peter Haase, Pascal Hitzler, Rudi Studer

Computer Science and Engineering Faculty Publications

In this paper we present a MOF compliant metamodel and UML profile for the Semantic Web Rule Language (SWRL) that integrates with our previous work on a metamodel and UML profile for OWL DL. Based on this metamodel and profile, UML tools can be used for visual modeling of rule-extended ontologies.

Python First: A Lab-Based Digital Introduction To Computer Science, Atanas Radenski

Mathematics, Physics, and Computer Science Faculty Articles and Research

The emphasis on Java and other commercial languages in CS1 has established the perception of computer science as a dry and technically difficult discipline among undecided students who are still seeking careers. This may not be a big problem during an enrolment boom, but in times of decreased enrolment such negative perception may have a devastating effect on computer science programs and therefore should not be ignored. We have made our CS1 course offerings more attractive to students (1) by introducing an easy to learn yet effective scripting language - Python, (2) by making all course resources available in a …

An Approach To The Optimization Of Convergent Networks On Ip/Mpls With An Optical Gmpls Backbone In Multicast, Yezid Donoso, Carolina Alvarado, Alfredo J. Perez, Ivan Herazo

Computer Science Faculty Publications

This paper shows the solution of a multiobjective scheme for multicast transmissions in MPLS networks with a GMLS optical backbone using evolutive algorithms. It has not been showed models that optimize one or more parameters integrating these two types of networks. Because the proposed scheme is a NP-Hard problem, an algorithm has been developed to solve the problem on polynomial time. The main contributions of this paper are the proposed mathematical model and the algorithm to solve it.

Adaptive Interpolation Algorithms For Temporal-Oriented Datasets, Jun Gao

School of Computing: Dissertations, Theses, and Student Research

Spatiotemporal datasets can be classified into two categories: temporal-oriented and spatial-oriented datasets depending on whether missing spatiotemporal values are closer to the values of its temporal or spatial neighbors. We present an adaptive spatiotemporal interpolation model that can estimate the missing values in both categories of spatiotemporal datasets. The key parameters of the adaptive spatiotemporal interpolation model can be adjusted based on experience.

Unifying Reciprocal Altruism And Inclusive Fitness Theories Of Altruism, Jeffrey Fletcher, Martin Zwick

Complex Systems Faculty Publications and Presentations

In lieu of an abstract, here is the outline:

Background

• Some History
• IPD Model of Reciprocal Altruism
• Problems Applying Hamilton’s Rule (HR)

Unification: Applying HR to Reciprocal Altruism

• Queller’s Generalized HR
• Conditional Behaviour and Non-Additivity
• Symbiotic Mutualisms

Implications of Unification

• Progressive Generalization of HR
• What happened to “indirect” fitness?
• Conceptual Parsimony

Adaptive Neural Network Control And Wireless Sensor Network Based Localization For Uav Formation, H. Wu, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

We consider a team of unmanned aerial vehicles (UAV's) equipped with sensors and motes for wireless communication for the task of navigating to a desired location in a formation. First a neural network (NN)-based control scheme is presented that allows the UAVs to track a desired position and orientation with reference to the neighboring UAVs or obstacles in the environment. Second, we discuss a graph theory-based scheme for discovery, localization and cooperative control. The purpose of the NN cooperative controller is to achieve and maintain the desired formation shape in the presence of unmodeled dynamics and bounded unknown disturbances. Numerical …

Robot Localization Using Visual Image Mapping, Carrie D. Crews

Theses and Dissertations

One critical step in providing the Air Force the capability to explore unknown environments is for an autonomous agent to be able to determine its location. The calculation of the robot's pose is an optimization problem making use of the robot's internal navigation sensors and data fusion of range sensor readings to find the most likely pose. This data fusion process requires the simultaneous generation of a map which the autonomous vehicle can then use to avoid obstacles, communicate with other agents in the same environment, and locate targets. Our solution entails mounting a Class 1 laser to an ERS-7 …

Mitigating Insider Threat Using Human Behavior Influence Models, Anthony J. Puleo

Theses and Dissertations

Insider threat is rapidly becoming the largest information security problem that organizations face. With large numbers of personnel having access to internal systems, it is becoming increasingly difficult to protect organizations from malicious insiders. The typical methods of mitigating insider threat are simply not working, primarily because this threat is a people problem, and most mitigation strategies are geared towards profiling and anomaly detection, which are problematic at best. As a result, a new type of model is proposed in this thesis, one that incorporates risk management with human behavioral science. The new risk-based model focuses on observable influences that …

Afit Uav Swarm Mission Planning And Simulation System, James N. Slear

Theses and Dissertations

The purpose of this research is to design and implement a comprehensive mission planning system for swarms of autonomous aerial vehicles. The system integrates several problem domains including path planning, vehicle routing, and swarm behavior. The developed system consists of a parallel, multi-objective evolutionary algorithm-based path planner, a genetic algorithm-based vehicle router, and a parallel UAV swarm simulator. Each of the system's three primary components are developed on AFIT's Beowulf parallel computer clusters. Novel aspects of this research include: integrating terrain following technology into a swarm model as a means of detection avoidance, combining practical problems of path planning and …

Development Of A Methodology For Customizing Insider Threat Auditing On A Microsoft Windows Xp® Operating System, Terry E. Levoy

Theses and Dissertations

Most organizations are aware that threats from trusted insiders pose a great risk to their organization and are very difficult to protect against. Auditing is recognized as an effective technique to detect malicious insider activities. However, current auditing methods are typically applied with a one-size-fits-all approach and may not be an appropriate mitigation strategy, especially towards insider threats. This research develops a 4-step methodology for designing a customized auditing template for a Microsoft Windows XP operating system. Two tailoring methods are presented which evaluate both by category and by configuration. Also developed are various metrics and weighting factors as a …

Development Of A Malicious Insider Composite Vulnerability Assessment Methodology, William H. King

Theses and Dissertations

Trusted employees pose a major threat to information systems. Despite advances in prevention, detection, and response techniques, the number of malicious insider incidents and their associated costs have yet to decline. There are very few vulnerability and impact models capable of providing information owners with the ability to comprehensively assess the effectiveness an organization's malicious insider mitigation strategies. This research uses a multi-dimensional approach: content analysis, attack tree framework, and an intent driven taxonomy model are used to develop a malicious insider Decision Support System (DSS) tool. The DSS tool's utility and applicability is demonstrated using a notional example. This …

Computation Reuse In Statics And Dynamics Problems For Assemblies Of Rigid Bodies, Anne Loomis

Dartmouth College Master’s Theses

The problem of determining the forces among contacting rigid bodies is fundamental to many areas of robotics, including manipulation planning, control, and dynamic simulation. For example, consider the question of how to unstack an assembly, or how to find stable regions of a rubble pile. In considering problems of this type over discrete or continuous time, we often encounter a sequence of problems with similar substructure. The primary contribution of our work is the observation that in many cases, common physical structure can be exploited to solve a sequence of related problems more efficiently than if each problem were considered …

A Multidiscipline Approach To Mitigating The Insider Threat, Jonathan W. Butts, Robert F. Mills, Gilbert L. Peterson

Faculty Publications

Preventing and detecting the malicious insider is an inherently difficult problem that expands across many areas of expertise such as social, behavioral and technical disciplines. Unfortunately, current methodologies to combat the insider threat have had limited success primarily because techniques have focused on these areas in isolation. The technology community is searching for technical solutions such as anomaly detection systems, data mining and honeypots. The law enforcement and counterintelligence communities, however, have tended to focus on human behavioral characteristics to identify suspicious activities. These independent methods have limited effectiveness because of the unique dynamics associated with the insider threat. The …

Batch Mode Active Learning And Its Applications To Medical Image Classification, Steven C. H. Hoi, Rong Jin, Jianke Zhu, Michael R. Lyu

Research Collection School Of Computing and Information Systems

The goal of active learning is to select the most informative examples for manual labeling. Most of the previous studies in active learning have focused on selecting a single unlabeled example in each iteration. This could be inefficient since the classification model has to be retrained for every labeled example. In this paper, we present a framework for "batch mode active learning" that applies the Fisher information matrix to select a number of informative examples simultaneously. The key computational challenge is how to efficiently identify the subset of unlabeled examples that can result in the largest reduction in the Fisher …

Learning Distance Metrics With Contextual Constraints For Image Retrieval, Steven C. H. Hoi, Wei Liu, Michael R. Lyu, Wei-Ying Ma

Research Collection School Of Computing and Information Systems

Relevant Component Analysis (RCA) has been proposed for learning distance metrics with contextual constraints for image retrieval. However, RCA has two important disadvantages. One is the lack of exploiting negative constraints which can also be informative, and the other is its incapability of capturing complex nonlinear relationships between data instances with the contextual information. In this paper, we propose two algorithms to overcome these two disadvantages, i.e., Discriminative Component Analysis (DCA) and Kernel DCA. Compared with other complicated methods for distance metric learning, our algorithms are rather simple to understand and very easy to solve. We evaluate the performance of …

On The Release Of Crls In Public Key Infrastructure, Chengyu Ma, Nan Hu, Yingjiu Li

Research Collection School Of Computing and Information Systems

Public key infrastructure provides a promising foundation for verifying the authenticity of communicating parties and transferring trust over the internet. The key issue in public key infrastructure is how to process certificate revocations. Previous research in this aspect has concentrated on the tradeoffs that can be made among different revocation options. No rigorous efforts have been made to understand the probability distribution of certificate revocation requests based on real empirical data. In this study, we first collect real empirical data from VeriSign and derive the probability function for certificate revocation requests. We then prove that a revocation system will become …

Security Analysis On A Conference Scheme For Mobile Communications, Zhiguo Wan, Feng Bao, Robert H. Deng, A. L. Ananda

Research Collection School Of Computing and Information Systems

The conference key distribution scheme (CKDS) enables three or more parties to derive a common conference key to protect the conversation content in their conference. Designing a conference key distribution scheme for mobile communications is a difficult task because wireless networks are more susceptible to attacks and mobile devices usually obtain low power and limited computing capability. In this paper we study a conference scheme for mobile communications and find that the scheme is insecure against the replay attack. With our replay attack, an attacker with a compromised conference key can cause the conferees to reuse the compromised conference key, …

Can Online Reviews Reveal A Product's True Quality? Empirical Findings Analytical Modeling Of Online Word-Of-Mouth Communication, Nan Hu, Paul Pavlou, Jennifer Zhang

Research Collection School Of Computing and Information Systems

As a digital version of word-of-mouth, online review has become a major information source for consumers and has very important implications for a wide range of management activities. While some researchers focus their studies on the impact of online product review on sales, an important assumption remains unexamined, that is, can online product review reveal the true quality of the product? To test the validity of this key assumption, this paper first empirically tests the underlying distribution of online reviews with data from Amazon. The results show that 53% of the products have a bimodal and non-normal distribution. For these …

Multilearner Based Recursive Supervised Training, Kiruthika Ramanathan, Sheng Uei Guan, Laxmi R. Iyer

Research Collection School Of Computing and Information Systems

In supervised learning, most single solution neural networks such as constructive backpropagation give good results when used with some datasets but not with others. Others such as probabilistic neural networks (PNN) fit a curve to perfection but need to be manually tuned in the case of noisy data. Recursive percentage based hybrid pattern training (RPHP) overcomes this problem by recursively training subsets of the data, thereby using several neural networks. MultiLearner based recursive training (MLRT) is an extension of this approach, where a combination of existing and new learners are used and subsets are trained using the weak learner which …

Fuzzy Cognitive Goal Net For Interactive Storytelling Plot Design, Yundong Cai, Chunyan Miao, Ah-Hwee Tan, Zhiqi Shen

Research Collection School Of Computing and Information Systems

Interactive storytelling attracts a lot of research interests among the interactive entertainments in recent years. Designing story plot for interactive storytelling is currently one of the most critical problems of interactive storytelling. Some traditional AI planning methods, such as Hierarchical Task Network, Heuristic Searching Method are widely used as the planning tool for the story plot design. This paper proposes a model called Fuzzy Cognitive Goal Net as the story plot planning tool for interactive storytelling, which combines the planning capability of Goal net and reasoning ability of Fuzzy Cognitive Maps. Compared to conventional methods, the proposed model shows a …

Cognitive Mapping Techniques For User-Database Interaction, Keng Siau, X. Tan

Research Collection School Of Computing and Information Systems

In this paper, we first develop a framework of user-database interaction. Based on this framework, we then provide a discussion on how notable human factors influence various dimensions of user-database interaction. Following that, we propose using cognitive mapping techniques to overcome some cognitive and behavioral biases during user-database interaction. Three popular cognitive mapping techniques-causal mapping, semantic mapping, and concept mapping-are introduced as techniques to elicit an individual's belief systems regarding a problem domain. Through an example database application, we demonstrate how to use these cognitive mapping techniques to improve user-database interaction. Finally, we discuss the implications of this research for …

Exploiting Domain Structure For Named Entity Recognition, Jing Jiang, Chengxiang Zhai

Research Collection School Of Computing and Information Systems

Named Entity Recognition (NER) is a fundamental task in text mining and natural language understanding. Current approaches to NER (mostly based on supervised learning) perform well on domains similar to the training domain, but they tend to adapt poorly to slightly different domains. We present several strategies for exploiting the domain structure in the training data to learn a more robust named entity recognizer that can perform well on a new domain. First, we propose a simple yet effective way to automatically rank features based on their generalizabilities across domains. We then train a classifier with strong emphasis on the …

Histogram Matching For Camera Pose Neighbor Selection, Parris K. Egbert, Bryan S. Morse, Kevin L. Steele

Faculty Publications

A prerequisite to calibrated camera pose estimation is the construction of a camera neighborhood adjacency graph, a connected graph defining the pose neighbors of the camera set. Pose neighbors to a camera C are images containing sufficient overlap in image content with the image from C that they can be used to correctly estimate the pose of C using structure-from-motion techniques. In a video stream, the camera neighborhood adjacency graph is often a simple connected path; frame poses are only estimated relative to their immediate neighbors. We propose a novel method to build more complex camera adjacency graphs that are …

Minimum Spanning Tree Pose Estimation, Parris K. Egbert, Kevin L. Steele

Faculty Publications

The extrinsic camera parameters from video stream images can be accurately estimated by tracking features through the image sequence and using these features to compute parameter estimates. The poses for long video sequences have been estimated in this manner. However, the poses of large sets of still images cannot be estimated using the same strategy because wide-baseline correspondences are not as robust as narrow-baseline feature tracks. Moreover, video pose estimation requires a linear or hierarchically-linear ordering on the images to be calibrated, reducing the image matches to the neighboring video frames. We propose a novel generalization to the linear ordering …

Facial Analysis In Video : Detection And Recognition, Peichung Shih

Dissertations

Biometric authentication systems automatically identify or verify individuals using physiological (e.g., face, fingerprint, hand geometry, retina scan) or behavioral (e.g., speaking pattern, signature, keystroke dynamics) characteristics. Among these biometrics, facial patterns have the major advantage of being the least intrusive. Automatic face recognition systems thus have great potential in a wide spectrum of application areas. Focusing on facial analysis, this dissertation presents a face detection method and numerous feature extraction methods for face recognition.

Concerning face detection, a video-based frontal face detection method has been developed using motion analysis and color information to derive field of interests, and distribution-based distance …

Enhancing Web Marketing By Using Ontology, Xuan Zhou

Dissertations

The existence of the Web has a major impact on people's life styles. Online shopping, online banking, email, instant messenger services, search engines and bulletin boards have gradually become parts of our daily life. All kinds of information can be found on the Web. Web marketing is one of the ways to make use of online information. By extracting demographic information and interest information from the Web, marketing knowledge can be augmented by applying data mining algorithms. Therefore, this knowledge which connects customers to products can be used for marketing purposes and for targeting existing and potential customers. The Web …

Structural Auditing Methodologies For Controlled Terminologies, Hua Min

Dissertations

Several auditing methodologies for large controlled terminologies are developed. These are applied to the Unified Medical Language System XXXX and the National Cancer Institute Thesaurus (NCIT). Structural auditing methodologies are based on the structural aspects such as IS-A hierarchy relationships groups of concepts assigned to semantic types and groups of relationships defined for concepts. Structurally uniform groups of concepts tend to be semantically uniform. Structural auditing methodologies focus on concepts with unlikely or rare configuration. These concepts have a high likelihood for errors.

One of the methodologies is based on comparing hierarchical relationships between the META and SN, two major …

Limited Delegation (Without Sharing Secrets) In Web Applications, Nicholas J. Santos

Dartmouth College Undergraduate Theses

Delegation is the process wherein an entity Alice designates an entity Bob to speak on her behalf. In password-based security systems, delegation is easy: Alice gives Bob her password. This is a useful feature, and is used often in the real world. But it's also problematic. When Alice shares her password, she must delegate all her permissions, but she may wish to delegate a limited set. Also, as we move towards PKI-based systems, secret-sharing becomes impractical. This thesis explores one solution to these problems. We use proxy certificates in a non-standard way so that user Alice can delegate a subset …

Image Vectorization, Brian L. Price

Theses and Dissertations

We present a new technique for creating an editable vector graphic from an object in a raster image. Object selection is performed interactively in subsecond time by calling graph cut with each mouse movement. A renderable mesh is then computed automatically for the selected object and each of its (sub)objects by (1) generating a coarse object mesh; (2) performing recursive graph cut segmentation and hierarchical ordering of subobjects; (3) applying error-driven mesh refinement to each (sub)object. The result is a fully layered object hierarchy that facilitates object-level editing without leaving holes. Object-based vectorization compares favorably with current approaches in the …