Computer Sciences Commons^™

Object Detection And Classification With Applications To Skin Cancer Screening, Jonathan Blackledge, Dmitryi Dubovitskiy

Articles

This paper discusses a new approach to the processes of object detection, recognition and classification in a digital image. The classification method is based on the application of a set of features which include fractal parameters such as the Lacunarity and Fractal Dimension. Thus, the approach used, incorporates the characterisation of an object in terms of its texture.

The principal issues associated with object recognition are presented which includes two novel fast segmentation algorithms for which C++ code is provided. The self-learning procedure for designing a decision making engine using fuzzy logic and membership function theory is also presented and …

Covert Encryption And Document Authentication Using Texture Coding, Jonathan Blackledge, Mary Hallot

Articles

With the improvements in the quality of Commercial-Off-The-Shelf (COTS) printing and scanning devices, the ability to counterfeit documents has become a widespread problem. Consequently, there has been an increasing demand to develop digital watermarking techniques which can be applied to both electronic and printed images (and documents) that can be authenticated, prevent unauthorized copying and withstand abuse and degradation. In this paper , a new approach to digital watermarking is presented and a range of possible applications are considered. The process is defined by using concepts and techniques borrowed from Cryptography. It is based on computing a 'scramble image' by …

Modeling Timed Component-Based Real-Time Systems, Huang-Ming Huang, Christopher Gill

All Computer Science and Engineering Research

Component based middleware helps to facilitate software reuse by separating application-specific concerns into modular components that are shielded from the concerns of other components and from the common concerns addressed by underlying middleware services. In real-time systems, concerns such as invocation rates, execution latencies, deadlines, and concurrency semantics cross-cut multiple component and middleware abstractions. Thus, the verification of these systems must consider features of the application components (e.g., their execution latencies and relative invocation rates) and of the supporting middleware (e.g., concurrency and scheduling) together. However, existing approaches only address a sub-set of the features that must be modeled in …

Scheduling Design And Verification For Open Soft Real-Time Systems, Robert Glaubius, Terry Tidwell, William D. Smart, Christopher Gill

All Computer Science and Engineering Research

Open soft real-time systems, such as mobile robots, experience unpredictable interactions with their environments and yet must respond both adaptively and with reasonable temporal predictability. New scheduling approaches are needed to address the demands of such systems, in which many of the assumptions made by traditional real-time scheduling theory do not hold. In previous work we established foundations for a scheduling policy design and verification approach for open soft real-time systems, that can use different decision models, e.g., a Markov Decision Process (MDP), to capture the nuances of their scheduling semantics. However, several important refinements to the preliminary techniques developed …

Faster Optimal State-Space Search With Graph Decomposition And Reduced Expansion, Yixin Chen

All Computer Science and Engineering Research

Traditional AI search methods, such as BFS, DFS, and A*, look for a path from a starting state to the goal in a state space most typically modelled as a directed graph. Prohibitively large sizes of the state space graphs make optimal search difficult. A key observation, as manifested by the SAS+ formalism for planning, is that most commonly a state-space graph is well structured as the Cartesian product of several small subgraphs. This paper proposes novel search algorithms that exploit such structure. The results reveal that standard search algorithms may explore many redundant paths. Our algorithms provide an automatic …

Local Neighborhoods For Shape Classification And Normal Estimation, Cindy Grimm, William Smart

All Computer Science and Engineering Research

We introduce the concept of local neighborhoods, a generalization of the one-ring on a mesh to unlabeled 3D data points arising from sampling a 2D surface embedded in 3D. The local neighborhood supports both local shape classification and robust normal estimation. In particular, local neighborhoods out-perform traditional approaches in unevenly sampled, curved regions. We show that the local neighborhood can be used in place of a full mesh structure for applications such as smoothing, moving least-squares reconstruction, and parameterization. Longer version of paper submitted to CAGD

Scheduling For Reliable Execution In Autonomic Systems, Terry Tidwell, Robert Glaubius, Christopher Gill, William D. Smart

All Computer Science and Engineering Research

Scheduling the execution of multiple concurrent tasks on shared resources such as CPUs and network links is essential to ensuring the reliable operation of many autonomic systems. Well known techniques such as rate-monotonic scheduling can offer rigorous timing and preemption guarantees, but only under assumptions (i.e., a fixed set of tasks with well-known execution times and invocation rates) that do not hold in many autonomic systems. New hierarchical scheduling techniques are better suited to enforce the more flexible execution constraints and enforcement mechanisms that are required for autonomic systems, but a rigorous foundation for verifying and enforcing concurrency and timing …

Animal Microrna Target Prediction By Incorporating Diverse Sequence-Specific Determinants, Yun Zheng, Weixiong Zhang

All Computer Science and Engineering Research

More recent evidence has shown that access of animal microRNAs (miRNAs) to their complementary sites in target mRNAs is determined by more sequence-specific determinants than the seed regions in the 5' end of miRNAs. Although these factors have been shown to be related to the repressive power of miRNAs and used, in separate programs, to predict the efficacy of miRNA complementary sites, it remains unclear whether these factors can help to improve miRNA target prediction. We develop a new miRNA target prediction algorithm, called Hitsensor, by incorporating more sequence-specific features that determine complementarities between miRNAs and their targets, in addition …

Flexible Service Provisioning For Heterogeneous Sensor Networks, Chien-Liang Fok, Gruia-Catalin Roman, Chenyang Lu

All Computer Science and Engineering Research

This paper presents Servilla, a highly flexible service provisioning framework for heterogeneous wireless sensor networks. Its service-oriented programming model and middleware enable developers to construct platform-independent applications over a dynamic set of devices with diverse computational resources and sensors. A salient feature of Servilla is its support for dynamic discovery and binding to local and remote services, which enables flexible and energy-efficient in-network collaboration among heterogeneous devices. Furthermore, Servilla provides a modular middleware architecture that can be easily tailored for devices with a wide range of resources, allowing even resource-limited devices to provide services and leverage resource-rich devices for in-network …

Vegetation Identification Based On Satellite Imagery, Vamsi K.R. Mantena, Ramu Pedada, Srinivas Jakkula, Yuzhong Shen, Jiang Li, Hamid R. Arabnia (Ed.)

Electrical & Computer Engineering Faculty Publications

Automatic vegetation identification plays an important role in many applications including remote sensing and high performance flight simulations. This paper presents a method to automatically identify vegetation based upon satellite imagery. First, we utilize the ISODATA algorithm to cluster pixels in the images where the number of clusters is determined by the algorithm. We then apply morphological operations to the clustered images to smooth the boundaries between clusters and to fill holes inside clusters. After that, we compute six features for each cluster. These six features then go through a feature selection algorithm and three of them are determined to …

Reed-Solomon Codes Construction & Decoding, Samuel J. Parsons

Honors Capstones

Capstone submitted as a graduation requirement for the BSU Honors Program.

What Is Rcu, Fundamentally?, Paul E. Mckenney, Jonathan Walpole

Computer Science Faculty Publications and Presentations

Read-copy update (RCU) is a synchronization mechanism that was added to the Linux kernel in October of 2002. RCU achieves scalability improvements by allowing reads to occur concurrently with updates. In contrast with conventional locking primitives that ensure mutual exclusion among concurrent threads regardless of whether they be readers or updaters, or with reader-writer locks that allow concurrent reads but not in the presence of updates, RCU supports concurrency between a single updater and multiple readers. RCU ensures that reads are coherent by maintaining multiple versions of objects and ensuring that they are not freed up until all pre-existing read-side …

Evaluation Of Robocode As A Teaching Tool For Computer Programming, Arnold Hensman

Conference Papers

Robocode began as an educational tool to aid in learning Java programming. It has since evolved into something of a phenomenon, as the prospect of creating simple to complex virtual tanks appears to pose an attractive challenge to both novice and expert programmers alike. What started out as a teaching tool has grown into a worldwide network of competitors, all keen to prove that their ‘bot’ stands out from the crowd. Competitions are well organised and many Robocode events are a PR dream for the computing companies that sponsor them. Without a doubt, this easy to use application has sparked …

Study Of The Minimum Spanning Hyper-Tree Routing Algorithm In Wireless Sensor Networks, Ting Yang, Yugeng Sun, Zhaoxia Wang, Juwei Zhang, Yingqiang Ding

Research Collection School Of Computing and Information Systems

Designing energy-efficient routing protocols to effectively increase the networks' lifetime and provide the robust network service is one of the important problems in the research of wireless sensor networks. Using the hyper-graph theory, the paper represents large-scale wireless sensor networks into a hyper-graph model, which can effectively decrease the control messages in routing process. Based on this mathematic model, the paper presents the minimum spanning hyper-tree routing algorithm in synchronous wireless sensor networks (MSHT-SN), which builds a minimum energy consumption tree for data collection from multi-nodes to Sink node. The validity of the algorithm is proved by the theatrical analysis. …

Self-Organizing Neural Architectures And Cooperative Learning In A Multiagent Environment, Dan Xiao, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Temporal-Difference–Fusion Architecture for Learning, Cognition, and Navigation (TD-FALCON) is a generalization of adaptive resonance theory (a class of self-organizing neural networks) that incorporates TD methods for real-time reinforcement learning. In this paper, we investigate how a team of TD-FALCON networks may cooperate to learn and function in a dynamic multiagent environment based on minefield navigation and a predator/prey pursuit tasks. Experiments on the navigation task demonstrate that TD-FALCON agent teams are able to adapt and function well in a multiagent environment without an explicit mechanism of collaboration. In comparison, traditional Q-learning agents using gradient-descent-based feedforward neural networks, trained with the …

Tuning Tabu Search Strategies Via Visual Diagnosis, Steven Halim, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

While designing working metaheuristics can be straightforward, tuning them to solve the underlying combinatorial optimization problem well can be tricky. Several tuning methods have been proposed but they do not address the new aspect of our proposed classification of the metaheuristic tuning problem: tuning search strategies. We propose a tuning methodology based on Visual Diagnosis and a generic tool called Visualizer for Metaheuristics Development Framework(V-MDF) to address specifically the problem of tuning search (particularly Tabu Search) strategies. Under V-MDF, we propose the use of a Distance Radar visualizer where the human and computer can collaborate to diagnose the occurrence of …

Designing The Market Game For A Commodity Trading Simulation, Shih-Fen Cheng

Research Collection School Of Computing and Information Systems

In this paper, we propose to design a market game that (a) can be used in modeling and studying commodity trading scenarios, and (b) can be used in capturing human traders' behaviors. Specifically, we demonstrate the usefulness of this commodity trading game in a single-commodity futures trading scenario. A pilot experiment was run with a mixture of human traders and an autonomous agent that emulates the aggregatedmarket condition, with the assumption that this autonomous agent would hint each of its action through a public announcement. We show that the information collected from this simulation can be used to extract the …

Multi-Period Combinatorial Auction Mechanism For Distributed Resource Allocation And Scheduling, Hoong Chuin Lau, Shih-Fen Cheng, Thin Yin Leong, Jong Han Park, Zhengyi Zhao

Research Collection School Of Computing and Information Systems

We consider the problem of resource allocation and scheduling where information and decisions are decentralized, and our goal is to propose a market mechanism that allows resources from a central resource pool to be allocated to distributed decision makers (agents) that seek to optimize their respective scheduling goals. We propose a generic combinatorial auction mechanism that allows agents to competitively bid for the resources needed in a multi-period setting, regardless of the respective scheduling problem faced by the agent, and show how agents can design optimal bidding strategies to respond to price adjustment strategies from the auctioneer. We apply our …

The Price Of Stability In Selfish Scheduling Games, Lucas Agussurja, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Game theory has gained popularity as an approach to analysing and understanding distributed systems with selfinterested agents. Central to game theory is the concept of Nash equilibrium as a stable state (solution) of the system, which comes with a price - the loss in efficiency. The quantification of the efficiency loss is one of the main research concerns. In this paper, we study the quality and computational characteristic of the best Nash equilibrium in two selfish scheduling models: the congestion model and the sequencing model. In particular, we present the following results: (1) In the congestion model: first, the best …

Predictive Congestion Control Protocol For Wireless Sensor Networks, Maciej Jan Zawodniok, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

Available congestion control schemes, for example transport control protocol (TCP), when applied to wireless networks, result in a large number of packet drops, unfair scenarios and low throughputs with a significant amount of wasted energy due to retransmissions. To fully utilize the hop by hop feedback information, this paper presents a novel, decentralized, predictive congestion control (DPCC) for wireless sensor networks (WSN). The DPCC consists of an adaptive flow and adaptive back-off interval selection schemes that work in concert with energy efficient, distributed power control (DPC). The DPCC detects the onset of congestion using queue utilization and the embedded channel …

Effects Of Electromagnetic Interference On Control Area Network Performance, Fei Ren, Y. Rosa Zheng, Maciej Jan Zawodniok, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, the effects of electromagnetic interference (EMI) on control area network (CAN) communications are investigated by hardware experiments. Distinct CAN bit rates, communication cables, and networks are used to test effects of EMI on CAN bus. Waveforms of CAN data frames in EMI environment are observed and analyzed for figuring out details of effects. Experiments show that the EMI pulses frequently encountered in automobile and off-road machinery can cause the reduction of bit rates and errors in high-speed CAN communications. Replacing traditional unshielded parallel communication cables with shielded communication cables is proved to be an effective method of …

Visualizing Morphometric Data Of Vasculatures, Thomas Wischgoll

Computer Science and Engineering Faculty Publications

Volume visualization is a common, very well-established visualization technique for volumetric data sets. Numerous advancements have been proposed and sophisticated improvements have been implemented to produce elaborated renderings that are capable of enhancing details within the volume. However, volume visualization alone is often not sufficient for the application domain. Often times, researchers are interested in accurate measurements extracted from volumetric data to gain further insight of the specimen. These extracted measurements can then be used to generate and visualize a geometric reconstruction of the specimen. The visualization can incorporate additional tools that allow researchers to determine additional measurements of the …

A Two-Phase Approach To Interactivity Enhancement For Large-Scale Distributed Virtual Environments, Nguyen Binh Duong Ta, Suiping Zhou

Research Collection School Of Computing and Information Systems

Distributed virtual environments (DVEs) are distributed systems that allow multiple geographically distributed clients (users) to interact simultaneously in a computer-generated, shared virtual world. Applications of DVEs can be seen in many areas nowadays, such as online games, military simulations, collaborative designs, etc. To support large-scale DVEs with real-time interactions among thousands or even more distributed clients, a geographically distributed server architecture (GDSA) is generally needed, and the virtual world can be partitioned into many distinct zones to distribute the load among the servers. Due to the geographic distributions of clients and servers in such architectures, it is essential to efficiently …

Comparisons Of An Adaptive Neural Network Based Controller And An Optimized Conventional Power System Stabilizer, Wenxin Liu, Ganesh K. Venayagamoorthy, Jagannathan Sarangapani, Donald C. Wunsch, Mariesa Crow, Li Liu, David A. Cartes

Electrical and Computer Engineering Faculty Research & Creative Works

Power system stabilizers are widely used to damp out the low frequency oscillations in power systems. In power system control literature, there is a lack of stability analysis for proposed controller designs. This paper proposes a Neural Network (NN) based stabilizing controller design based on a sixth order single machine infinite bus power system model. The NN is used to compensate the complex nonlinear dynamics of power system. To speed up the learning process, an adaptive signal is introduced to the NN's weights updating rule. The NN can be directly used online without offline training process. Magnitude constraint of the …

Ceg 220: Introduction To C Programming For Engineers I, Jay Dejongh

Computer Science & Engineering Syllabi

This course provides a general introduction to computers as a problem-solving tool using the C programming language. Emphasis is on algorithms and techniques useful to engineers. Topics include data representation, debugging, and program verification. 4 credit hours. Prerequisite: MTH 229 (Calculus I) or EGR 101 (Engineering Mathematics).

Cs 405/605: Introduction To Database Management Systems, Soon M. Chung

Computer Science & Engineering Syllabi

Survey of logical and physical aspects of database management systems. Entity Relationship, relational, object-oriented models for databases are presented. Physical implementation methods are discussed.

Energy-Efficient Hybrid Key Management Protocol For Wireless Sensor Networks, Timothy J. Landstra, Maciej Jan Zawodniok, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, we propose a subnetwork key management strategy in which the heterogeneous security requirements of a wireless sensor network are considered to provide differing levels of security with minimum communication overhead. Additionally, it allows the dynamic creation of high security subnetworks within the wireless sensor network and provides subnetworks with a mechanism for dynamically creating a secure key using a novel and dynamic group key management protocol. The proposed energy-efficient protocol utilizes a combination of pre-deployed group keys and initial trustworthiness of nodes to create a level of trust between neighbors in the network. This trust is later …

Control Of Nonholonomic Mobile Robot Formations Using Neural Networks, Jagannathan Sarangapani, Travis Alan Dierks

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper the control of formations of multiple nonholonomic mobile robots is attempted by integrating a kinematic controller with a neural network (NN) computed-torque controller. A combined kinematic/torque control law is developed for leader-follower based formation control using backstepping in order to accommodate the dynamics of the robots and the formation in contrast with kinematic-based formation controllers. The NN is introduced to approximate the dynamics of the follower as well as its leader using online weight tuning. It is shown using Lyapunov theory that the errors for the entire formation are uniformly ultimately bounded, and numerical results are provided.

Cs 240: Computer Programming I, Dale E. Nelson

Computer Science & Engineering Syllabi

Basic concepts of programming and programming languages are introduced. Emphasis is on structured programming and stepwise refinement. Prerequisite: MTH 130 or MPL 5.

Cs 400/600: Computer Science, Eric Maston

Computer Science & Engineering Syllabi

This is the initial course in the understanding of data structures. This course focuses on data structures with abstract data types, such as trees, stacks, queues and graphs. The course will use projects, developed on UNIX, to create a deeper understanding of data structure and their use.