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2008

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Experiments And Models For The Thermal Response Of Railroad Tapered-Roller Bearings, Constantine Tarawneh, Kevin D. Cole, Brent Wilson, Fadi Alnaimat Dec 2008

Experiments And Models For The Thermal Response Of Railroad Tapered-Roller Bearings, Constantine Tarawneh, Kevin D. Cole, Brent Wilson, Fadi Alnaimat

Mechanical Engineering Faculty Publications

The need to understand and quantify the heat transfer paths within tapered-roller bearings is of great importance in the railroad industry since bearing cup temperature measurement is the primary tool utilized in the removal of distressed bearings from service. Experiments were performed to acquire temperature histories at several locations on a stationary bearing subjected to heat sources imbedded in two rollers. The experimental results were compared to zero- and first-order thermal models to estimate overall heat transfer coefficients from the bearing. The results presented here can be used to explain some of the mechanisms that lead to overheating of tapered-roller …

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Some Items To Consider Before You Change The Calving Season Of Your Beef Cow Herd, Randall D. Weidmeier, Adam Summers, D. R. Zobell, Dillon M. Feuz Dec 2008

Some Items To Consider Before You Change The Calving Season Of Your Beef Cow Herd, Randall D. Weidmeier, Adam Summers, D. R. Zobell, Dillon M. Feuz

All Current Publications

This publication gives important items to consider before changing calving seasons of beef cow herds.

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Solution Of The Gribov Problem From Gauge Invariance, K Langfeld, T Heinzl, A Ilderton, M Lavelle, D Mcmullan Dec 2008

Solution Of The Gribov Problem From Gauge Invariance, K Langfeld, T Heinzl, A Ilderton, M Lavelle, D Mcmullan

School of Engineering, Computing and Mathematics

A new approach to gauge fixed Yang-Mills theory is derived using the Polyakov-Susskind projection techniques to build gauge invariant states. In our approach, in contrast to the Faddeev-Popov method, the Gribov problem does not prevent the gauge group from being factored out of the partition function. Lattice gauge theory is used to illustrate the method via a calculation of the static quark-antiquark potential generated by the gauge fields in the fundamental modular region of Coulomb gauge.

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Interference Effects Due To Projectile Target Nucleus Scattering In Single Ionization Of H₂ By 75-Kev Proton Impact, Jason S. Alexander, Aaron C. Laforge, Ahmad Hasan, Z. S. Machavariani, M. F. Ciappina, R. D. Rivarola, Don H. Madison, Michael Schulz Dec 2008

Interference Effects Due To Projectile Target Nucleus Scattering In Single Ionization Of H₂ By 75-Kev Proton Impact, Jason S. Alexander, Aaron C. Laforge, Ahmad Hasan, Z. S. Machavariani, M. F. Ciappina, R. D. Rivarola, Don H. Madison, Michael Schulz

Physics Faculty Research & Creative Works

Doubly differential cross sections (DDCSs) for single ionization of molecular hydrogen by 75-keV proton impact have been measured and calculated as a function of the projectile scattering angle and energy loss. Interference structures are observed in the scattering angular dependence of the DDCSs, which disappear, however, at electron speeds near the projectile speed. The comparison to our calculations shows that the projectile-target nucleus interaction plays a central role. Furthermore, our data suggest that for a given scattering angle, ionization favors well-defined molecular orientations.

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Spin- And Fine-Structure-Resolved Ionization Of Krypton, S. Bellm, J. Lower, R. P. Mceachran, E. Weigold, Ciarán Ryan-Anderson, Don H. Madison Dec 2008

Spin- And Fine-Structure-Resolved Ionization Of Krypton, S. Bellm, J. Lower, R. P. Mceachran, E. Weigold, Ciarán Ryan-Anderson, Don H. Madison

Physics Faculty Research & Creative Works

The influence of exchange, correlation, and relativistic effects in the ionization of heavy-target atoms can be sensitively probed by kinematically complete studies involving spin-polarized electrons, in particular when the fine structure of the residual ion is resolved. We present spin asymmetries, triple differential cross sections, and branching ratios for the ionization, by 127.5-eV and 114.3-eV electrons, of ground-state krypton atoms leading to the Kr+ 4s 2S1/2, 4p5 2P1/2, and 4p5 2P3/2 states. In order to untangle contributions from different physical effects, the experimental results are compared to those from distorted-wave Born approximation calculations (non- and semirelativistic) in which bound-state and …

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A Systematic Framework For Structured Object-Oriented Security Requirements Analysis In Embedded Systems, Sojan Markose, Xiaoqing Frank Liu, Bruce M. Mcmillin Dec 2008

A Systematic Framework For Structured Object-Oriented Security Requirements Analysis In Embedded Systems, Sojan Markose, Xiaoqing Frank Liu, Bruce M. Mcmillin

Computer Science Faculty Research & Creative Works

The primary goal of this paper is to develop a structured objectoriented security requirements analysis methodology for the elicitation and analysis of security requirements in embedded systems. There are several approaches to elicit, analyze and specify security requirements in embedded systems ranging from formal mathematical models for proof of certain security properties to informal methods that are easily understood. Applicability of formal security models is limited because they are complex and it is time consuming to develop. On the other hand, informal security requirements analysis methods are not integrated with conceptual models in requirements analysis, and although both external and …

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Implementation And Analysis Of Practical Algorithm For Data Security, Willi Ballenthin, F. Kacani, Julia Albath, Sanjay Kumar Madria Dec 2008

Implementation And Analysis Of Practical Algorithm For Data Security, Willi Ballenthin, F. Kacani, Julia Albath, Sanjay Kumar Madria

Computer Science Faculty Research & Creative Works

In this paper, we present a complete implementation of the Practical Algorithm for Data Security (PADS) proposed by Albath et al., an end-to-end security scheme employing symmetric key encryption. The implementation takes full advantage of the modular design of the TinyOS environment. The simplicity of the algorithm allows for efficient implementation in hardware, a requirement for resource constrained devices. The protocol adds only four bytes of data per packet, on par with industry standards. Simulation and empirical results of the scheme are also provided. The analysis shows that the Practical Algorithm for Data Security is superior to standard security schemes.

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On Step Sizes, Stochastic Shortest Paths, And Survival Probabilities In Reinforcement Learning, Abhijit Gosavi Dec 2008

On Step Sizes, Stochastic Shortest Paths, And Survival Probabilities In Reinforcement Learning, Abhijit Gosavi

Engineering Management and Systems Engineering Faculty Research & Creative Works

Reinforcement learning (RL) is a simulation-based technique useful in solving Markov decision processes if their transition probabilities are not easily obtainable or if the problems have a very large number of states. We present an empirical study of (i) the effect of step-sizes (learning rules) in the convergence of RL algorithms, (ii) stochastic shortest paths in solving average reward problems via RL, and (iii) the notion of survival probabilities (downside risk) in RL. We also study the impact of step sizes when function approximation is combined with RL. Our experiments yield some interesting insights that will be useful in practice …

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A Model Based Fault Detection And Prognostic Scheme For Uncertain Nonlinear Discrete-Time Systems, Balaje T. Thumati, Jagannathan Sarangapani Dec 2008

A Model Based Fault Detection And Prognostic Scheme For Uncertain Nonlinear Discrete-Time Systems, Balaje T. Thumati, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

A new fault detection and prognostics (FDP) framework is introduced for uncertain nonlinear discrete time system by using a discrete-time nonlinear estimator which consists of an online approximator. A fault is detected by monitoring the deviation of the system output with that of the estimator output. Prior to the occurrence of the fault, this online approximator learns the system uncertainty. In the event of a fault, the online approximator learns both the system uncertainty and the fault dynamics. A stable parameter update law in discrete-time is developed to tune the parameters of the online approximator. This update law is also …

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Robust Regularized Kernel Regression, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu Dec 2008

Robust Regularized Kernel Regression, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu

Research Collection School Of Computing and Information Systems

Robust regression techniques are critical to fitting data with noise in real-world applications. Most previous work of robust kernel regression is usually formulated into a dual form, which is then solved by some quadratic program solver consequently. In this correspondence, we propose a new formulation for robust regularized kernel regression under the theoretical framework of regularization networks and then tackle the optimization problem directly in the primal. We show that the primal and dual approaches are equivalent to achieving similar regression performance, but the primal formulation is more efficient and easier to be implemented than the dual one. Different from …

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Distributing Complementary Resources Across Multiple Periods With Stochastic Demand, Shih-Fen Cheng, John Tajan, Hoong Chuin Lau Dec 2008

Distributing Complementary Resources Across Multiple Periods With Stochastic Demand, Shih-Fen Cheng, John Tajan, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

In this paper, we evaluate whether the robustness of a market mechanism that allocates complementary resources could be improved through the aggregation of time periods in which resources are consumed. In particular, we study a multi-round combinatorial auction that is built on a general equilibrium framework. We adopt the general equilibrium framework and the particular combinatorial auction design from the literature, and we investigate the benefits and the limitation of time-period aggregation when demand-side uncertainties are introduced. By using simulation experiments, we show that under stochastic conditions the performance variation of the process decreases as the time frame length (time …

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Mobitop: Accessing Hierarchically Organized Georeferenced Multimedia Annotations, Thi Nhu Quynh Kim, Khasfariyati Razikin, Dion Hoe-Lian Goh, Quang Minh Nguyen, Ee Peng Lim Dec 2008

Mobitop: Accessing Hierarchically Organized Georeferenced Multimedia Annotations, Thi Nhu Quynh Kim, Khasfariyati Razikin, Dion Hoe-Lian Goh, Quang Minh Nguyen, Ee Peng Lim

Research Collection School Of Computing and Information Systems

We introduce MobiTOP, a map-based interface for accessing hierarchically organized georeferenced annotations. Each annotation contains multimedia content associated with a location, and users are able to annotate existing annotations, in effect creating a hierarchy.

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Simulation Of Nanostructured Electrodes For Polymer Electrolyte Membrane Fuel Cells, Sanjeev M. Rao, Yangchuan Xing Dec 2008

Simulation Of Nanostructured Electrodes For Polymer Electrolyte Membrane Fuel Cells, Sanjeev M. Rao, Yangchuan Xing

Chemical and Biochemical Engineering Faculty Research & Creative Works

Aligned carbon nanotubes (CNTs) with Pt uniformly deposited on them are being considered in fabricating the catalyst layer of polymer electrolyte membrane (PEM) fuel cell electrodes. When coated with a proton conducting polymer (e.g., Nafion) on the Pt/CNTs, each Pt/CNT acts as a nanoelectrode and a collection of such nanoelectrodes constitutes the proposed nanostructured electrodes. Computer modeling was performed for the cathode side, in which both multicomponent and Knudsen diffusion were taken into account. the effect of the nanoelectrode lengths was also studied with catalyst layer thicknesses of 2, 4, 6, and 10 μm. It was observed that shorter lengths …

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Pas: Predicate-Based Authentication Services Against Powerful Passive Adversaries, Sriram Chellappan, Xiaole Bai, Wenjun Gu, Xun Wang, Dong Xuan, Bin Ma Dec 2008

Pas: Predicate-Based Authentication Services Against Powerful Passive Adversaries, Sriram Chellappan, Xiaole Bai, Wenjun Gu, Xun Wang, Dong Xuan, Bin Ma

Computer Science Faculty Research & Creative Works

Securely authenticating a human user without assistance from any auxiliary device in the presence of powerful passive adversaries is an important and challenging problem. Passive adversaries are those that can passively monitor, intercept, and analyze every part of the authentication procedure, except for an initial secret shared between the user and the server. In this paper, we propose a new secure authentication scheme called predicate-based authentication service (PAS). In this scheme, for the first time, the concept of a predicate is introduced for authentication. We conduct analysis on the proposed scheme and implement its prototype system. Our analytical data and …

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Neural Network Output Feedback Control Of A Quadrotor Uav, Jagannathan Sarangapani, Travis Alan Dierks Dec 2008

Neural Network Output Feedback Control Of A Quadrotor Uav, Jagannathan Sarangapani, Travis Alan Dierks

Electrical and Computer Engineering Faculty Research & Creative Works

A neural network (NN) based output feedback controller for a quadrotor unmanned aerial vehicle (UAV) is proposed. The NNs are utilized in the observer and for generating virtual and actual control inputs, respectively, where the NNs learn the nonlinear dynamics of the UAV online including uncertain nonlinear terms like aerodynamic friction and blade flapping. It is shown using Lyapunov theory that the position, orientation, and velocity tracking errors, the virtual control and observer estimation errors, and the NN weight estimation errors for each NN are all semi-globally uniformly ultimately bounded (SGUUB) in the presence of bounded disturbances and NN functional …

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Neural-Network-Based State Feedback Control Of A Nonlinear Discrete-Time System In Nonstrict Feedback Form, Pingan He, Jagannathan Sarangapani Dec 2008

Neural-Network-Based State Feedback Control Of A Nonlinear Discrete-Time System In Nonstrict Feedback Form, Pingan He, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a suite of adaptive neural network (NN) controllers is designed to deliver a desired tracking performance for the control of an unknown, second-order, nonlinear discrete-time system expressed in nonstrict feedback form. In the first approach, two feedforward NNs are employed in the controller with tracking error as the feedback variable whereas in the adaptive critic NN architecture, three feedforward NNs are used. In the adaptive critic architecture, two action NNs produce virtual and actual control inputs, respectively, whereas the third critic NN approximates certain strategic utility function and its output is employed for tuning action NN weights …

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Link Rate Allocation Under Bandwidth And Energy Constraints In Sensor Networks, Maggie Cheng, Xuan Gong, Lin Cai Dec 2008

Link Rate Allocation Under Bandwidth And Energy Constraints In Sensor Networks, Maggie Cheng, Xuan Gong, Lin Cai

Computer Science Faculty Research & Creative Works

In sensor networks, both energy and band width are scarce resources. in the past, the energy efficient routing problem has been vastly studied in order to maximize network lifetime, but link bandwidth has been optimistically assumed to be abundant. as energy con straint affects how data should be routed, link bandwidth also affects not just the routing topology but also the allowed data rate on each link, which in turn affects lifetime. Previous works that focus on energy efficient operations in sensor networks with the sole objective of maximizing network lifetime only consider the energy constraint and ignore the bandwidth …

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Position Transformation: A Location Privacy Protection Method For Moving Objects, Dan Lin, Elisa Bertino, Reynold Cheng, Sunil Prabhakar Dec 2008

Position Transformation: A Location Privacy Protection Method For Moving Objects, Dan Lin, Elisa Bertino, Reynold Cheng, Sunil Prabhakar

Computer Science Faculty Research & Creative Works

The expanding use of location-Based services has profound implications on the privacy of personal information. in this paper, we propose a framework for preserving location privacy based on the idea of sending to the service provider suitably modified location information. Agents execute data transformation, and the service provider directly processes the transformed dataset. Our technique not only prevents the service provider from knowing the exact locations of users, but also protects information about user movements and locations from being disclosed to other users who are not authorized to access this information. We also define a privacy model to analyze our …

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Improvements In Steel Melting Efficiency -- Industrial Trials, Kent D. Peaslee, Semen Naumovich Lekakh, Edith Martinez Dec 2008

Improvements In Steel Melting Efficiency -- Industrial Trials, Kent D. Peaslee, Semen Naumovich Lekakh, Edith Martinez

Materials Science and Engineering Faculty Research & Creative Works

Industrial trials were completed to improve energy efficiency in steel melting. First, the benefits of increased chemical energy from an oxyfuel burner and a Co-Jet system in a basic 20 ton electric arc furnace (EAF) were studied. Observations and measurements were made during production before and after the installation of the two systems. The additional chemical energy improved energy efficiency and resulted in increased production. In addition, production using a basic EAF practice was compared to the traditional acid EAF practice. Second, an industrial trial using a 750 lb ladle with a combination of a lightweight alumina castable refractory and …

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Using Clinical Decision Support To Maintain Medication And Problem Lists: A Pilot Study To Yield Higher Patient Safety, Chiang S. Jao, Daniel B. Hier, William L. Galanter Dec 2008

Using Clinical Decision Support To Maintain Medication And Problem Lists: A Pilot Study To Yield Higher Patient Safety, Chiang S. Jao, Daniel B. Hier, William L. Galanter

Chemistry Faculty Research & Creative Works

To Investigate Whether Clinical Decision Support that Automates the Matching of Ordered Drugs to Problems (Clinical Diagnoses) on the Problem List Can Enhance the Maintenance of Both Medication and Problem Lists in the Electronic Medical Record, We Designed a Clinical Decision Support System to Match Ordered Drugs on the Medication List and Ongoing Problems on the Problem List. We Evaluated the Capability and Performance of This Clinical Decision Support System in Medication-Problem Matching using Physician Expert Chart Audits to Match Ordered Drugs to Ongoing Clinical Problems. a Clinical Decision Support System Was Shown to Be Useful in Improving Medication-Problem Matches …

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Maximum Likelihood And Gaussian Estimation Of Continuous Time Models In Finance, Peter C. B. Phillips, Jun Yu Dec 2008

Maximum Likelihood And Gaussian Estimation Of Continuous Time Models In Finance, Peter C. B. Phillips, Jun Yu

Research Collection School Of Economics

This paper overviews maximum likelihood and Gaussian methods of estimating continuous time models used in finance. Since the exact likelihood can be constructed only in special cases, much attention has been devoted to the development of methods designed to approximate the likelihood. These approaches range from crude Euler-type approximations and higher order stochastic Taylor series expansions to more complex polynomial-based expansions and infill approximations to the likelihood based on a continuous time data record. The methods are discussed, their properties are outlined and their relative finite sample performance compared in a simulation experiment with the nonlinear CIR diffusion model, which …

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Planning With Ifalcon: Towards A Neural-Network-Based Bdi Agent Architecture, Budhitama Subagdja, Ah-Hwee Tan Dec 2008

Planning With Ifalcon: Towards A Neural-Network-Based Bdi Agent Architecture, Budhitama Subagdja, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

This paper presents iFALCON, a model of BDI (beliefdesire-intention) agents that is fully realized as a selforganizing neural network architecture. Based on multichannel network model called fusion ART, iFALCON is developed to bridge the gap between a self-organizing neural network that autonomously adapts its knowledge and the BDI agent model that follows explicit descriptions. Novel techniques called gradient encoding are introduced for representing sequences and hierarchical structures to realize plans and the intention structure. This paper shows that a simplified plan representation can be encoded as weighted connections in the neural network through a process of supervised learning. A case …

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Cognitive Agents Integrating Rules And Reinforcement Learning For Context-Aware Decision Support, Teck-Hou Teng, Ah-Hwee Tan Dec 2008

Cognitive Agents Integrating Rules And Reinforcement Learning For Context-Aware Decision Support, Teck-Hou Teng, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

While context-awareness has been found to be effective for decision support in complex domains, most of such decision support systems are hard-coded, incurring significant development efforts. To ease the knowledge acquisition bottleneck, this paper presents a class of cognitive agents based on self-organizing neural model known as TD-FALCON that integrates rules and learning for supporting context-aware decision making. Besides the ability to incorporate a priori knowledge in the form of symbolic propositional rules, TD-FALCON performs reinforcement learning (RL), enabling knowledge refinement and expansion through the interaction with its environment. The efficacy of the developed Context-Aware Decision Support (CaDS) system is …

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Scaling Up Multi-Agent Reinforcement Learning In Complex Domains, Dan Xiao, Ah-Hwee Tan Dec 2008

Scaling Up Multi-Agent Reinforcement Learning In Complex Domains, Dan Xiao, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

TD-FALCON (Temporal Difference - Fusion Architecture for Learning, COgnition, and Navigation) is a class of self-organizing neural networks that incorporates Temporal Difference (TD) methods for real-time reinforcement learning. In this paper, we present two strategies, i.e. policy sharing and neighboring-agent mechanism, to further improve the learning efficiency of TD-FALCON in complex multi-agent domains. Through experiments on a traffic control problem domain and the herding task, we demonstrate that those strategies enable TD-FALCON to remain functional and adaptable in complex multi-agent domains

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A Fast Pruned‐Extreme Learning Machine For Classification Problem, Hai-Jun Rong, Yew-Soon Ong, Ah-Hwee Tan, Zexuan Zhu Dec 2008

A Fast Pruned‐Extreme Learning Machine For Classification Problem, Hai-Jun Rong, Yew-Soon Ong, Ah-Hwee Tan, Zexuan Zhu

Research Collection School Of Computing and Information Systems

Extreme learning machine (ELM) represents one of the recent successful approaches in machine learning, particularly for performing pattern classification. One key strength of ELM is the significantly low computational time required for training new classifiers since the weights of the hidden and output nodes are randomly chosen and analytically determined, respectively. In this paper, we address the architectural design of the ELM classifier network, since too few/many hidden nodes employed would lead to underfitting/overfitting issues in pattern classification. In particular, we describe the proposed pruned-ELM (P-ELM) algorithm as a systematic and automated approach for designing ELM classifier network. P-ELM uses …

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Adoption Of 3-D Virtual Worlds For Education, X. Chen, Keng Siau, Fiona Fui-Hoon Nah Dec 2008

Adoption Of 3-D Virtual Worlds For Education, X. Chen, Keng Siau, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

As an emerging phenomenon, virtual world education is rarely researched in MIS literature. With stiff competition among institutions using virtual worlds for education, a legitimate research question is: What factors influence students’ intention to adopt 3-D virtual world environment for their education needs? Drawing on existing technology acceptance models and studies in other IS contexts, we developed a model to predict students’ acceptance of a 3-D virtual world education environment and plan to empirically test the model using survey data collected from college students. From the academic research perspective, studies on the use of the new technology for education will …

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Chosen-Ciphertext Secure Proxy Re-Encryption Without Pairing, Robert H. Deng, Jian Weng, Shengli Liu, Kefei Chen Dec 2008

Chosen-Ciphertext Secure Proxy Re-Encryption Without Pairing, Robert H. Deng, Jian Weng, Shengli Liu, Kefei Chen

Research Collection School Of Computing and Information Systems

In a proxy re-encryption system, a semi-trusted proxy can convert a ciphertext originally intended for Alice into a ciphertext intended for Bob, without learning the underlying plaintext. Proxy re-encryption has found many practical applications, such as encrypted email forwarding, secure distributed file systems, and outsourced filtering of encrypted spam. In ACM CCS'07, Canetti and Hohenberger presented a proxy re-encryption scheme with chosen-ciphertext security, and left an important open problem to construct a chosen-ciphertext secure proxy re-encryption scheme without pairings. In this paper, we solve this open problem by proposing a new proxy re-encryption scheme without resort to bilinear pairings. Based …

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Privacy Engine For Context-Aware Enterprise Application Services, Marion Blount, John Davis, Maria Ebling, William Jerome, Barry Leiba, Xuan Liu, Archan Misra Dec 2008

Privacy Engine For Context-Aware Enterprise Application Services, Marion Blount, John Davis, Maria Ebling, William Jerome, Barry Leiba, Xuan Liu, Archan Misra

Research Collection School Of Computing and Information Systems

Satisfying the varied privacy preferences of individuals, while exposing context data to authorized applications and individuals, remains a major challenge for context-aware computing. This paper describes our experiences in building a middleware component, the context privacy engine (CPE), that enforces a role-based, context-dependent privacy model for enterprise domains. While fundamentally an ACL-based access control scheme, CPE extends the traditional ACL mechanism with usage control and context constraints. This paper focuses on discussing issues related to managing and evaluating context-dependent privacy policies. Extensive experimental studies with a production-grade implementation and real-life context sources demonstrate that the CPE can support a large …

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Innovation In The Programmable Web: Characterizing The Mashup Ecosystem, C. Jason Woodard, Shuli Yu Dec 2008

Innovation In The Programmable Web: Characterizing The Mashup Ecosystem, C. Jason Woodard, Shuli Yu

Research Collection School Of Computing and Information Systems

This paper investigates the structure and dynamics of the Web 2.0 software ecosystem by analyzing empirical data on web service APIs and mashups. Using network analysis tools to visualize the growth of the ecosystem from December 2005 to 2007, we find that the APIs are organized into three tiers, and that mashups are often formed by combining APIs across tiers. Plotting the cumulative distribution of mashups to APIs reveals a power-law relationship, although the tail is short compared to previously reported distributions of book and movie sales. While this finding highlights the dominant role played by the most popular APIs …

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Making Sense Of Technology Trends In The Information Technology Landscape, Gediminas Adomavicius, Jesse C. Bockstedt, Alok Gupta, Robert J. Kauffman Dec 2008

Making Sense Of Technology Trends In The Information Technology Landscape, Gediminas Adomavicius, Jesse C. Bockstedt, Alok Gupta, Robert J. Kauffman

Research Collection School Of Computing and Information Systems

A major problem for firms making information technology investment decisions is predicting and understanding the effects of future technological developments on the value of present technologies. Failure to adequately address this problem can result in wasted organization resources in acquiring, developing, managing, and training employees in the use of technologies that are short-lived and fail to produce adequate return on investment. The sheer number of available technologies and the complex set of relationships among them make IT landscape analysis extremely challenging. Most IT-consuming firms rely on third parties and suppliers for strategic recommendations on IT investments, which can lead to …

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