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Full-Text Articles in Physical Sciences and Mathematics
Scaling A Dataflow Testing Methodology To The Multiparadigm World Of Commercial Spreadsheets, Marc Randall Fisher Ii, Gregg Rothermel, Tyler Creelan, Margaret Burnett
Scaling A Dataflow Testing Methodology To The Multiparadigm World Of Commercial Spreadsheets, Marc Randall Fisher Ii, Gregg Rothermel, Tyler Creelan, Margaret Burnett
CSE Technical Reports
Spreadsheet languages are widely used by end users to perform a broad range of important tasks. Evidence shows, however, that spreadsheets often contain faults. Thus, in prior work we presented a dataflow testing methodology for use with spreadsheets, that provides feedback about the coverage of cells in spreadsheets via visual devices. Studies have shown that this methodology, which we call WYSIWYT (What You See Is What You Test), can be used cost-effectively by end-user programmers. To date, however, the methodology has been investigated across a limited set of spreadsheet language features. Commercial spreadsheet environments are multiparadigm languages, utilizing features often …
A Performance And Schedulability Analysis Of An Autonomous Mobile Robot, Ala' Adel Qadi, Steve Goddard, Jiangyang Huang, Shane Farritor
A Performance And Schedulability Analysis Of An Autonomous Mobile Robot, Ala' Adel Qadi, Steve Goddard, Jiangyang Huang, Shane Farritor
CSE Technical Reports
We present an autonomous, mobile, robotics application that requires dynamic adjustments of task execution rates to meet the demands of an unpredictable environment. The Robotic Safety Marker (RSM) system consists of one lead robot, the foreman, and a group of guided robots, called robotic safety markers (a.k.a., barrels). An extensive analysis is conducted of two applications running on the foreman. Both applications require adjusting task periods to achieve desired performance metrics with respect to the speed at which a system task is completed, the accuracy of RSM placement, or the number of RSMs controlled by the foreman. A static priority …
Applications Of Decision And Utility Theory In Multi-Agent Systems, Xin Li, Leen-Kiat Soh
Applications Of Decision And Utility Theory In Multi-Agent Systems, Xin Li, Leen-Kiat Soh
CSE Technical Reports
This report reviews the applications of decision-related theories (decision theory, utility theory, probability theory, and game theory) in various aspects of multi-agent systems. In recent years, multi-agent systems (MASs) have become a highly active research area as multi-agent systems have a wide range of applications. However, most of real-world environments are very complex and of uncertainty. An agent’s knowledge about the world is rather incomplete and uncertain. The actions of the agent are non-deterministic with a range of possible outcomes. The agent may have many desires that conflict each other. The agent also needs to know about other agents and …
An Adaptive Mechanism For Improving File Transfer Performance, Eric Moss, Leen-Kiat Soh
An Adaptive Mechanism For Improving File Transfer Performance, Eric Moss, Leen-Kiat Soh
CSE Technical Reports
A variant of instance-based learning is described which detects periodic patterns in the presence of sparse data. A weighted average gives higher weight to values in the recent past as well as those at expected periods in the past. After each new measurement, the space of weights near the current set is searched for a set that minimizes the error of prediction, thus providing a learning mechanism. The method is described in terms of an application which minimizes file download times by choosing between available servers.
An Online Survey Framework Using The Life Events Calendar, Jared Kite, Leen-Kiat Soh
An Online Survey Framework Using The Life Events Calendar, Jared Kite, Leen-Kiat Soh
CSE Technical Reports
We describe an online survey framework programmed as a Java applet with a MySQL back-end. Our framework is built specifically as a Event History Calendar for the study of tobacco users and their behavior over a six month period. We introduce the notion of a Life Events Calendar and the relevance of an intelligent survey system in this context. We describe our methods and our component application approach and expand on the opportunities for artificial intelligence research with the system.
An Analysis Of Mcmc Sampling Methods For Estimating Weighted Sums In Winnow, Qingping Tao, Stephen Scott
An Analysis Of Mcmc Sampling Methods For Estimating Weighted Sums In Winnow, Qingping Tao, Stephen Scott
CSE Technical Reports
Chawla et al. introduced a way to use the Markov chain Monte Carlo method to estimate weighted sums in multiplicative weight update algorithms when the number of inputs is exponential. But their algorithm still required extensive simulation of the Markov chain in order to get accurate estimates of the weighted sums. We propose an optimized version of Chawla et al.’s algorithm, which produces exactly the same classifications while often using fewer Markov chain simulations. We also apply two other sampling techniques and empirically compare them with Chawla et al.’s Metropolis sampler to determine how effective each is in drawing good …
Ai In Computer Games: From The Player’S Goal To Ai’S Role, Jeremy A. Glasser, Leen-Kiat Soh
Ai In Computer Games: From The Player’S Goal To Ai’S Role, Jeremy A. Glasser, Leen-Kiat Soh
CSE Technical Reports
This paper addresses the role of Artificial Intelligence (AI) in a variety of game genres. Every game aims to entertain (though educational games have secondary objectives). Each genre approaches entertainment in a unique way. We explore the methods used to draw the game player’s attention. We then consider how the AI interacts with the player to promote both entertainment and an interactive environment. We also consider some of the techniques that will shape tomorrow’s games. Included are opponent strategies, interactive environments, and multiagent systems (MAS). While different, each approach can aid in creating more immersive and challenging gaming experiences. Our …
Reasoning And Learning With Imperfect Casebases: An Agent Perspective With An Expert Model, Leen-Kiat Soh
Reasoning And Learning With Imperfect Casebases: An Agent Perspective With An Expert Model, Leen-Kiat Soh
CSE Technical Reports
Traditionally, case-based reasoning (CBR) (e.g., Watson and Marir 1994) assumes that the cases in the casebase are correct, useful in both time and space. Otherwise, the cases would not have been stored in the casebase in the first place. Cases are supposed to be useful in guiding us to a successful solution, or in preventing us from repeating the same failure.
A Study In Modeling Low-Conservation Protein Superfamilies, Chang Wang, Stephen Scott, Jun Zhang, Qingping Tao, Dmitri E. Fomenko, Vadim N. Gladyshev
A Study In Modeling Low-Conservation Protein Superfamilies, Chang Wang, Stephen Scott, Jun Zhang, Qingping Tao, Dmitri E. Fomenko, Vadim N. Gladyshev
CSE Technical Reports
We present several algorithms for identification of new proteins in superfamilies with low primary sequence conservation. The low conservation of primary sequence in protein superfamilies such as Thioredoxin-fold (Trxfold) makes conventional methods such as hidden Markov models (HMMs) difficult to use. Therefore, we use structural properties to build our classifiers. These structural properties include secondary structure patterns as well as various properties of the residues in the protein sequences. We use this information to model proteins via hidden Markov models, support vector machines and algorithms in the multiple-instance learning model. In 20-fold jackknife tests, some of our models performed well, …
A Study In Modeling Low-Conservation Protein Superfamilies, Chang Wang, Stephen Scott, Jun Zhang, Qingping Tao, Dmitri E. Fomenko, Vadim N. Gladyshev
A Study In Modeling Low-Conservation Protein Superfamilies, Chang Wang, Stephen Scott, Jun Zhang, Qingping Tao, Dmitri E. Fomenko, Vadim N. Gladyshev
CSE Technical Reports
We present several algorithms for identification of new proteins in superfamilies with low primary sequence conservation. The low conservation of primary sequence in protein superfamilies such as Thioredoxin-fold (Trx-fold) makes conventional methods such as hidden Markov models (HMMs) difficult to use. Therefore, we use structural properties to build our classifiers. These structural properties include secondary structure patterns as well as various properties of the residues in the protein sequences. We use this information to model proteins via hidden Markov models, support vector machines and algorithms in the multiple-instance learning model. In 20-fold jack-knife tests, some of our models performed well, …
Variable Rate Execution, Steve Goddard, Xin Liu
Variable Rate Execution, Steve Goddard, Xin Liu
CSE Technical Reports
We present a task model for adaptive real-time tasks in which a task’s execution rate requirements are allowed to change at any time. The model, variable rate execution (VRE), is an extension of the rate-based execution (RBE) model. We relax the constant execution rate assumption of canonical realtime task models by allowing both the worst case execution time (WCET) and the period to be variable. The VRE model also supports tasks joining and leaving the system at any time. Another advantage of the new task model is that the exact execution rate need not be known for soft real-time or …
A Dynamic Real-Time Scheduling Algorithm For Reduced Energy Consumption, Rohini Krishnapura, Steve Goddard, Ala' Adel Qadi
A Dynamic Real-Time Scheduling Algorithm For Reduced Energy Consumption, Rohini Krishnapura, Steve Goddard, Ala' Adel Qadi
CSE Technical Reports
In embedded real-time systems, Dynamic Power Management (DPM) techniques have traditionally focused on reducing the dynamic power dissipation that occurs when a CMOS gate switches in a processor. Less attention has been given to processor leakage power or power consumed by I/O devices and other subsystems. I/O-based DPM techniques, however, have been extensively researched in non-real-time systems. These techniques focus on switching I/O devices to low power states based on various policies and are not applicable to real-time environments because of the non-deterministic nature of the policies. The challenge in conserving energy in embedded real-time systems is thus to reduce …
Ilmda: Intelligent Learning Materials Delivery Agents, Leen-Kiat Soh, L.D. Miller, Todd Blank, Suzette Person
Ilmda: Intelligent Learning Materials Delivery Agents, Leen-Kiat Soh, L.D. Miller, Todd Blank, Suzette Person
CSE Technical Reports
In this paper, we describe an intelligent agent that delivers learning materials adaptively to different students, factoring in the usage history of the learning materials, the student static background profile, and the student dynamic activity profile. Our assumption is that through the interaction of a student going through a learning material (i.e., a topical tutorial, a set of examples, and a set of problems), our agent will be able to capture and utilize the student’s activity as the primer to select the appropriate example or problem to administer to the student. Even if the agent fails to do so, it …
On Cooperative Learning Teams For Multiagent Team Formation, Leen-Kiat Soh
On Cooperative Learning Teams For Multiagent Team Formation, Leen-Kiat Soh
CSE Technical Reports
In this paper, we propose a team formation methodology based on cooperative learning teams, adopted from the area of educational research. Cooperative learning is a type of learning where students work in teams and learn through team-based interactions. In education, research in assigning students to appropriate teams and enforcing fair assessment of student performance in a team have generated useful policies and rules. In our multiagent systems project, we use these policies and rules as the underlying framework to evaluate and form teams. We have built a system called I-MINDS as an infrastructure to support cooperative learning among remote and …
Reasoning And Learning With Imperfect Casebases: An Agent Perspective With An Expert Model, Leen-Kiat Soh
Reasoning And Learning With Imperfect Casebases: An Agent Perspective With An Expert Model, Leen-Kiat Soh
CSE Technical Reports
Traditionally, case-based reasoning (CBR) (e.g., Watson and Marir 1994) assumes that the cases in the casebase are correct, useful in both time and space. Otherwise, the cases would not have been stored in the casebase in the first place. Cases are supposed to be useful in guiding us to a successful solution, or in preventing us from repeating the same failure.
Dynamic Voltage Scaling For Sporadic And Periodic Tasks, Ala' Adel Qadi, Steve Goddard, Shane Farritor
Dynamic Voltage Scaling For Sporadic And Periodic Tasks, Ala' Adel Qadi, Steve Goddard, Shane Farritor
CSE Technical Reports
Dynamic voltage scaling (DVS) algorithms save energy by scaling down the processor frequency when the processor is not fully loaded. Many algorithms have been proposed for periodic and aperiodic task models but none support the periodic and sporadic task models when the deadlines are not equal to their periods. A DVS algorithm, called General Dynamic Voltage Scaling (GDVS), that can be used with sporadic or periodic tasks in conjunction with the preemptive EDF scheduling algorithm with no constraints on the deadlines is presented here. The algorithm is proven to guarantee each task meets its deadline while saving the maximum amount …
An Analysis Of Mcmc Sampling Methods For Estimating Weighted Sums In Winnow, Qingping Tao, Stephen Scott
An Analysis Of Mcmc Sampling Methods For Estimating Weighted Sums In Winnow, Qingping Tao, Stephen Scott
CSE Technical Reports
Chawla et al. introduced a way to use the Markov chain Monte Carlo method to estimate weighted sums in multiplicative weight update algorithms when the number of inputs is exponential. But their algorithm still required extensive simulation of the Markov chain in order to get accurate estimates of the weighted sums. We propose an optimized version of Chawla et al.’s algorithm, which produces exactly the same classifications while often using fewer Markov chain simulations. We also apply three other sampling techniques and empirically compare them with Chawla et al.’sMetropolis sampler to determine how effective each is in drawing good samples …