10095666
Simulation modeling within workflow technology
This paper presents an approach for integrating simulation modeling and analysis capabilities within the workflow management system (WFMS) being developed in the Large Scale Distributed Information Systems (LSDIS) Lab at the University of Georgia. Simulation modeling can be used for studying the efficiency of workflow designs as well as studying the general performance and reliability of WFMSs. We also discuss the importance of using sophisticated monitoring and animation capabilities, and the use of workflow management technology to advance simulation technology itself. Finally, we demonstrate a sample simulation where tasks and task managers are simulated.
16899510
Query driven simulation using SIMODULA
This paper describes the design and early implementation phases of a simulation modeling environment that integrates a process-oriented simulation language and a database system with object-oriented extensions. User may interact with the system simply by formulating SQL-like queries to retrieve information stored from previous simulations, or indeed cause information to be automatically generated.
15234568
Demonstrating Dynamic Configuration and Execution of Web Processes
Web processes are next generation workflows on the web, created using Web services. In this paper we demonstrate the METEOR-S Configuration and Execution Environment (MCEE) system. It will illustrate the capabilities of the system to a) Discover partners b) Optimize partner selection using constraint analysis, c) Perform interaction protocol and data mediation. A graphical execution monitor to monitor the various phases of execution will be used to demonstrate various aspects of the system.
2346213
Healthcare Enterprise Process Development and Integration
Healthcare enterprises involve complex processes that span diverse groups and organisations. These processes involve clinical and administrative tasks, large volumes of data, and large numbers of patients and personnel. The tasks can be performed either by humans or by automated systems. In the latter case, the tasks are supported by a variety of software applications and information systems which are very often heterogeneous, autonomous, and distributed. The development of systems to manage and automate these processes has increasingly played an important role in improving the efficiency of healthcare enterprises. In this paper we look at four healthcare and medical applications that involve investigative, clinical, and administrative functions. Based on these applications, we derive the requirements for developing enterprise applications that involve the coordination of a variety of tasks performed by humans, information systems, and legacy applications.
13902265
Simulation and the semantic Web
One of the missions of the semantic Web is to put more knowledge on the Web in an organized fashion and link it to other information and data sources. Three successively more capable languages are (or will soon be) provided for this: RDF, OWL, and SWRL. This paper makes a case for using all three for the domain of modeling and simulation. Based on experience developing the discrete-event modeling ontology (DeMO) some observations on the issues and challenges involved in creating such ontologies are presented. An approach for decomposing models into behavioral and observable parts, a la hidden Markov models, which can make ontologies smaller and easier to understand, is also discussed
9294328
Performance Modeling of Database Recovery Protocols
The performance modeling described in this paper compares several protocols which ensure that a database can be recovered to a consistent state after a transaction failure or system crash. The contributions of the paper include a collection of simple analytic models, based on Markov processes, for these protocols and some surprising results on the relative performance of the protocols. We consider only two-stage transactions (all reads before writes) and ignore effects of serializing transactions. The most interesting performance result presented is that, for systems obeying the assumptions of this paper, the "pessimistic" policy of holding write locks to commit point is considerably less efficient than the "optimistic" policy which allows reading of uncommitted data, but risks cascading aborts. A multiversion policy introduced in [2] was also studied and found always to be nearly as good as the optimistic policy and sometimes much better.
17043790
Collaborative, programmable intelligent agents
A growing number of computer systems,in the hope that such simulations w as we had thought. More recently, however, resources for such work can be obtained from untapped source: the generation of extremely large numbers of graduate students and their subsequent application to the creation of alternate “Simulating Complex Adaptive Systems -What can we really learn?” Dr. B. Rubble Bedrock Inst. Brub@bedrock.edu Friday, December 6, 1996 11:00 a.m. – 12:00 noon Singapore Rm. 1st Floor R&D Building #1 Place on electronic calender brub@bedrock.edu Friday,December 6, 1996 11:00 a.m... Mail to secretary for scheduling Done Figure 1. Sample invocation of Apple Data Detectors. The user has selected a portion of an email message describing an upcoming seminar. Two patterns are found: an email address (brub@bedrock.edu) and the announcement of the meeting (the sequence of date and time information starting Friday, Dec. 6, 1996). These patterns are presented in the pop-up menu; by pointing at the date information in the menu; a second pop-up menu offers a choice of actions: place an entry for the meeting on the user’s electronic calendar or mail the selection to the user’s secretary. The user can select one, thereby running a small application, or move the cursor off the menu, eliminating the pop-up menu and canceling any actions. agents also varies across different agent-based systems; some act only within one’s own machine, find others autonomously crawl the Web, searching for interesting content [4]. We tried to find a middle ground by using explicit representations of user-relevant information as a means of identifying actions users might wish to take but to leave the choice of these actions to users. Working with Information Inside User Documents Our first step was to find a user problem that needed solving in which intelligent agents would add value. In an investigation of how people file information on their computer desktops [1], we discovered that a common user complaint is that they cannot easily take action on the structured information found in everyday documents (structured information being data-recognizable by a grammar). Ordinary documents are full of such structured information: phone numbers, fax numbers, street addresses, email addresses, email signatures, abstracts, tables of contents, lists of references, tables, figures, captions, meeting announcements, Web addresses, and more. In addition, there are countless domain-specific structures, such as ISBN numbers, stock symbols, chemical structures, and mathematical equations. These structures are not only relevant to users, but because of their structure, are also recognizable by parsing technologies. Once identified, the structure’s type can be used to identify appropriate actions that might be carried out, like placing a meeting on a calendar, adding an address to an address book, dialing a phone number, opening a URL, finding the current price of a stock, filing an ISBN number, and compiling a list of abstracts. Apple Data Detectors supports a wide range of uses. Think of all the structured information in the documents you work with; in addition to those mentioned already, add bibliography items, forms (such as travel expense reports and non-disclosure agreements), executive summaries, and most important, such domain-specific kinds of data as legal boilerplate, customer orders, and library search requests. Specific detectors can be created for each of these types of information. User interface. To use Apple Data Detectors, users select a region of a document with some information of interest. Pressing a modifier key and the mouse button instructs the system to analyze the data within the selected region and to find all structures for which it has grammars. It then offers appropriate actions for each structure (see Figure 1). For example, for users reading email who come across a seminar announcement they would like to put on a calendar, Apple Data Detectors parses the relevant information within the selected text, including the meeting’s place, time, and date and puts this data into the appropriate fields on the calendar. A user can select a whole document or part of a document without having to make a careful selection; the grammars find any embedded structures they know about within the selection and offer an appropriate set of actions from which to choose. The use of anthropomorphism in an agent interface [12] was incongruent with our goal of unobtrusiveness. We designed Apple Data Detectors to be invis98 March 1998/Vol. 41, No. 3 COMMUNICATIONS OF THE ACM User Application Presentation User Interface Apple Data Detectors Detectors Database Actions Folder HTTP = (Http Protocol, Host, Port?, Path?, {Http Location, Http Search} ? ) Http Protocol = {“http://”, “https://”} Port = (“:”, Port Number) Port Number = Digits Figure 2. The Apple Data Detectors architecture, which separates the application in which the information is found, the presentation of the analysis and possible actions, and the analysis of the information itself. This separation means that Apple Data Detectors can be invoked in any application and that the user interface can be implemented, refined, and evolved separately from the analysis module. Figure 3. A grammar to define a URL. The language implements a context-free grammar in which sequences of terms are matched against the input stream. References to other grammars are permitted, as are optional and repeated terms. Here, the HTTP grammar finds a match when it finds an HTTP protocol, a host, a port (optional), a path (optional), and either an HTTP location indicator or an HTTP search command and arguments.
35037776
Assessing the Performance of Neural Encoding Models in the Presence of Noise
An analytical method is introduced for evaluating the performance of neural encoding models. The method addresses a critical question that arises during the course of the development and validation of encoding models: is a given model near optimal in terms of its accuracy in predicting the stimulus-elicited responses of a neural system, or can the predictive accuracy be improved significantly by further model development? The evaluation method is based on a derivation of the minimum mean-square error between actual responses and modeled responses. It is formulated as a comparison between the mean-square error of the candidate model and the theoretical minimum mean-square error attainable through an optimal model for the system. However, no a priori information about the nature of the optimal model is required. The theoretically minimum error is determined solely from the coherence function between pairs of system responses to repeated presentations of the same dynamic stimulus. Thus, the performance of the candidate model is judged against the performance of an optimal model rather than against that of an arbitrarily assumed model.Using this method, we evaluated a linear model for neural encoding by mechanosensory cells in the cricket cercal system. At low stimulus intensities, the best-fit linear model of encoding by single cells was found to be nearly optimal, even though the coherence between stimulus-response pairs (a commonly used measure of system linearity) was low. In this low-stimulus-intensity regime, the mean square error of the linear model was on the order of the power of the cell responses. In contrast, at higher stimulus intensities the linear model was not an accurate representation of neural encoding, even though the stimulus-response coherence was substantially higher than in the low-intensity regime.
8365397
Input modeling when simple models fail
A simulation model is composed of inputs and logic; the inputs represent the uncertainty or randomness in the system, while the logic determines how the system reacts to the uncertain elements. Simple input models, consisting of independent and identically distributed sequences of random variates from standard probability distributions, are included in every commercial simulation language. Software to fit these distributions to data is also available. In this tutorial we describe input models that are useful when simple models are not.
206463342
The User Experience
In this article the author provides perspective on user experience, usability and user-centered design. User experience is a broad collection of user-centric issues that cut through the full extent of a project. The author points out new developments in the user experience world that are opening up new opportunities for research and projects. The author also discusses how good user experience processes can be built into the kinds of system development projects that many of us are involved in.
7380263
Getting more from the data in a multinomial selection problem
We consider the problem of determining which of k simulated systems is most likely to be the best per former based on some objective performance measure. The standard experiment is to generate v in dependent vector observations (replications) across the k- systems. A classical multinomial selection pro cedure, BEM (Bechhofer, Elmaghraby, and Morse), prescribes a minimum number of replications so that the probability of correctly selecting the true best system meets or exceeds a prespecified probability. Assuming that larger is better, BEM selects as best the system having the largest value of the performance measure in more replications than any other. We propose using these same v replications across k systems to form vk pseudoreplications (no longer in dependent) that contain one observation from each system, and again select as best the system having the largest value of the performance measure in more pseudoreplications than any other. We expect that this new procedure, AVC (all vector comparisons), dominates BEM in the sense that AVC will never require more independent replications than DEM to meet a prespecified probability of correct selection. We present analytical and simulation results to show how AVC fares versus BEM for different underly ing distribution families, different numbers of populations and various values of v. We also present results for the closely related problem of estimating the probability that a specific system is the best.