Designing intelligent computer‐based simulations: A pragmatic approach

This paper examines the design of intelligent multimedia simulations. A case study is presented which uses an approach based in part on intelligent tutoring system design to integrate formative assessment into the learning of clinical decision‐making skills for nursing students. The approach advocated uses a modular design with an integrated intelligent agent within a multimedia simulation. The application was created using an object‐orientated programming language for the multimedia interface (Delphi) and a logic‐based interpreted language (Prolog) to create an expert assessment system. Domain knowledge is also encoded in a Windows help file reducing some of the complexity of the expert system. This approach offers a method for simplifying the production of an intelligent simulation system. The problems developing intelligent tutoring systems are examined and an argument is made for a practical approach to developing intelligent multimedia simulation systems

The design and implementation of a continuous network file system

This thesis presents the design and implementation of Continuous Network File System (CNFS), a file system that provides a framework for developing efficient multimedia servers using Linux operating system. CNFS uses a modular approach for designing multimedia file systems utilizing a user-level technique and off-the-shelf commercial products. Multimedia traffic smoothing techniques and real-time issues are explored for the real implementation work. At client-side, CNFS chooses Userfs, a kernel file system skeleton, as its low-level IPC mechanism. The Userfs allows a file system be implemented in user processes. Thus, the whole development environment is more manageable for future research. At server side, KURT, a real-time extension of Linux, is used to provide QoS support for I/O operations. The technique for using KURT for multimedia system is discussed in detail. A complete prototype and functional system using CNFS is built and the process is described in the thesis. Initial performance measurements of the prototype implementation show CNFS capable of achieving real-time delivery of MPEG-1 file under reasonable system loads

Efficient and Reliable Task Scheduling, Network Reprogramming, and Data Storage for Wireless Sensor Networks

Wireless sensor networks (WSNs) typically consist of a large number of resource-constrained nodes. The limited computational resources afforded by these nodes present unique development challenges. In this dissertation, we consider three such challenges. The first challenge focuses on minimizing energy usage in WSNs through intelligent duty cycling. Limited energy resources dictate the design of many embedded applications, causing such systems to be composed of small, modular tasks, scheduled periodically. In this model, each embedded device wakes, executes a task-set, and returns to sleep. These systems spend most of their time in a state of deep sleep to minimize power consumption. We refer to these systems as almost-always-sleeping (AAS) systems. We describe a series of task schedulers for AAS systems designed to maximize sleep time. We consider four scheduler designs, model their performance, and present detailed performance analysis results under varying load conditions. The second challenge focuses on a fast and reliable network reprogramming solution for WSNs based on incremental code updates. We first present VSPIN, a framework for developing incremental code update mechanisms to support efficient reprogramming of WSNs. VSPIN provides a modular testing platform on the host system to plug-in and evaluate various incremental code update algorithms. The framework supports Avrdude, among the most popular Linux-based programming tools for AVR microcontrollers. Using VSPIN, we next present an incremental code update strategy to efficiently reprogram wireless sensor nodes. We adapt a linear space and quadratic time algorithm (Hirschberg\u27s Algorithm) for computing maximal common subsequences to build an edit map specifying an edit sequence required to transform the code running in a sensor network to a new code image. We then present a heuristic-based optimization strategy for efficient edit script encoding to reduce the edit map size. Finally, we present experimental results exploring the reduction in data size that it enables. The approach achieves reductions of 99.987% for simple changes, and between 86.95% and 94.58% for more complex changes, compared to full image transmissions - leading to significantly lower energy costs for wireless sensor network reprogramming. The third challenge focuses on enabling fast and reliable data storage in wireless sensor systems. A file storage system that is fast, lightweight, and reliable across device failures is important to safeguard the data that these devices record. A fast and efficient file system enables sensed data to be sampled and stored quickly and batched for later transmission. A reliable file system allows seamless operation without disruptions due to hardware, software, or other unforeseen failures. While flash technology provides persistent storage by itself, it has limitations that prevent it from being used in mission-critical deployment scenarios. Hybrid memory models which utilize newer non-volatile memory technologies, such as ferroelectric RAM (FRAM), can mitigate the physical disadvantages of flash. In this vein, we present the design and implementation of LoggerFS, a fast, lightweight, and reliable file system for wireless sensor networks, which uses a hybrid memory design consisting of RAM, FRAM, and flash. LoggerFS is engineered to provide fast data storage, have a small memory footprint, and provide data reliability across system failures. LoggerFS adapts a log-structured file system approach, augmented with data persistence and reliability guarantees. A caching mechanism allows for flash wear-leveling and fast data buffering. We present a performance evaluation of LoggerFS using a prototypical in-situ sensing platform and demonstrate between 50% and 800% improvements for various workloads using the FRAM write-back cache over the implementation without the cache

Realising the open virtual commissioning of modular automation systems

To address the challenges in the automotive industry posed by the need to rapidly manufacture more product variants, and the resultant need for more adaptable production systems, radical changes are now required in the way in which such systems are developed and implemented. In this context, two enabling approaches for achieving more agile manufacturing, namely modular automation systems and virtual commissioning, are briefly reviewed in this contribution. Ongoing research conducted at Loughborough University which aims to provide a modular approach to automation systems design coupled with a virtual engineering toolset for the (re)configuration of such manufacturing automation systems is reported. The problems faced in the virtual commissioning of modular automation systems are outlined. AutomationML - an emerging neutral data format which has potential to address integration problems is discussed. The paper proposes and illustrates a collaborative framework in which AutomationML is adopted for the data exchange and data representation of related models to enable efficient open virtual prototype construction and virtual commissioning of modular automation systems. A case study is provided to show how to create the data model based on AutomationML for describing a modular automation system

Modular OrCAD simulation approach in teaching power electronics

In this paper the authors present a new technique which can be used in simulating multi power electronic circuits at the same time in a very accurate way without the worries of the circuit analysis being diverted during the simulation. In this technique each circuits is simulated alone and the output current/voltage waveform(s) of this circuit is presented as a 'wave-form' generator. Then the final multi circuit design will be a collection of these 'wave-form' generators. This technique can be used in teaching power electronics system design for undergraduate as well as postgraduate levels and can also be used in the industry. A UPS system is used as an example in demonstrating this technique but this approach could equally be applicable to other multi circuit design configurations

Hybrid Prototypes to Assist Modeling Automotive Seats

The development of new modular seats is an important issue in the automotive industry. However, is very time consuming and costly. Virtual models and hybrid prototypes could accelerate the car seats development process. The hybrid prototypes are mainly manufactured by rapid prototyping with multi materials. The objective of this paper is to establish a methodology to develop innovative lightweight multi-functional, modular car seats to be used in Multi-Purpose Vehicles (MPV), by means of FEA simulation and rapid prototyping additive/subtractive technologies utilizing multi materials. A case study is presented to validate the developed methodology. The manufactured hybrid prototype’s reproduces the main functionalities of the MPV modular seat, namely its three key positions: normal, stored and table.Mechanical Engineerin

A new module system for prolog

It is now widely accepted that separating programs into modules has proven very useful in program development and maintenance. While many Prolog implementations include useful module systems, we feel that these systems can be improved in a number of ways, such as, for example, being more amenable to effective global analysis and allowing sepárate compilation or sensible creation of standalone executables. We discuss a number of issues related to the design of such an improved module system for Prolog. Based on this, we present the choices made in the Ciao module system, which has been designed to meet a number of objectives: allowing sepárate compilation, extensibility in features and in syntax, amenability to modular global analysis, etc

Towards MKM in the Large: Modular Representation and Scalable Software Architecture

MKM has been defined as the quest for technologies to manage mathematical knowledge. MKM "in the small" is well-studied, so the real problem is to scale up to large, highly interconnected corpora: "MKM in the large". We contend that advances in two areas are needed to reach this goal. We need representation languages that support incremental processing of all primitive MKM operations, and we need software architectures and implementations that implement these operations scalably on large knowledge bases. We present instances of both in this paper: the MMT framework for modular theory-graphs that integrates meta-logical foundations, which forms the base of the next OMDoc version; and TNTBase, a versioned storage system for XML-based document formats. TNTBase becomes an MMT database by instantiating it with special MKM operations for MMT.Comment: To appear in The 9th International Conference on Mathematical Knowledge Management: MKM 201