Cpascoe pimms or2012_

In this talk I would like to explore on how to apply the scientific method to in silico experiments. How can we design these experiments, so that they are independent of the software tool that gave rise to them? Over the past decade we have seen the rise of model exchange formats such as the Systems Biology Markup Language (SBML), that enable us to share the models readily with colleagues and between applications. Here I present the Simulation Experiment Description Markup Language (SED-ML) that aims to do the same thing for in silico experiments. After detailing its history, and where it currently stands, I will give a short overview of the growing tool support.

A 5-minute presentation at University of Edinburgh for UK Ontology Workshop 2013-04-11. The animals demonstrate that ontologies can be simple and lament the lack og good ontologies in most of physical science, especially computational chemistry. Blog at http://blogs.ch.cam.ac.uk/pmr

1 Project 2 Introduction - the SeaPort Project series For this set of projects for the course, we wish to simulate some of the aspects of a number of Sea Ports. Here are the classes and their instance variables we wish to define:  SeaPortProgram extends JFrame o variables used by the GUI interface o world: World  Thing implement Comparable <Thing> o index: int o name: String o parent: int  World extends Thing o ports: ArrayList <SeaPort> o time: PortTime  SeaPort extends Thing o docks: ArrayList <Dock> o que: ArrayList <Ship> // the list of ships waiting to dock o ships: ArrayList <Ship> // a list of all the ships at this port o persons: ArrayList <Person> // people with skills at this port  Dock extends Thing o ship: Ship  Ship extends Thing o arrivalTime, dockTime: PortTime o draft, length, weight, width: double o jobs: ArrayList <Job>  PassengerShip extends Ship o numberOfOccupiedRooms: int o numberOfPassengers: int o numberOfRooms: int  CargoShip extends Ship o cargoValue: double o cargoVolume: double o cargoWeight: double  Person extends Thing o skill: String  Job extends Thing - optional till Projects 3 and 4 o duration: double o requirements: ArrayList <String> // should be some of the skills of the persons  PortTime o time: int Eventually, in Projects 3 and 4, you will be asked to show the progress of the jobs using JProgressBar's. 2 Here's a very quick overview of all projects: 1. Read a data file, create the internal data structure, create a GUI to display the structure, and let the user search the structure. 2. Sort the structure, use hash maps to create the structure more efficiently. 3. Create a thread for each job, cannot run until a ship has a dock, create a GUI to show the progress of each job. 4. Simulate competing for resources (persons with particular skills) for each job. Project 2 General Objectives Project 2 - Map class, Comparator, sorting  Use the JDK Map class to write more efficient code when constructing the internal data structures from the data file.  Implement SORTING using the Comparator interface together with the JDK support for sorting data structures, thus sorting on different fields of the classes from Project 1.  Extend the GUI from Project 1 to let the user sort the data at run-time. Documentation Requirements: You should start working on a documentation file before you do anything else with these projects, and fill in items as you go along. Leaving the documentation until the project is finished is not a good idea for any number of reasons. The documentation should include the following (graded) elements:  Cover page (including name, date, project, your class information)  Design o including a UML class diagram o classes, variables and methods: what they mean and why they are there o tied to the requirements of the project  User's Guide o how would a user start and run your pro ...

Quick intro and demo session on what you need to know to launch your ChatGPT clone in own Kubernetes cluster.

The document discusses key concepts related to memory models in C#, including: 1. The compilation process involves lexical analysis, parsing, semantic analysis, optimization, and code generation. 2. Value types are stored on the stack while reference types are stored on the heap. 3. The garbage collector performs memory management by freeing up unused memory on the heap.

This document summarizes a workshop on the Tulipp project, which aims to develop ubiquitous low-power image processing platforms. The workshop covered shortcomings of existing platforms, introduced the Maestro real-time operating system as the reference platform, and described the concept of the Tulipp project to provide an operating system and tools to support heterogeneous architectures including FPGA and multi-core processors. Attendees participated in hands-on labs demonstrating how to build applications with Maestro, leverage OpenMP for parallelism, and use SDSoC tools to automatically accelerate functions in FPGA hardware.

The document discusses object-oriented programming (OOP) concepts like abstraction, encapsulation, inheritance, and polymorphism. It then covers design patterns, the Unified Modeling Language (UML), and provides an example case study of developing a student information system using Java and related technologies. The key topics are introduced at a high-level with the goal of demonstrating practical OOP through the case study example.

Atomate and matminer are open-source Python libraries for high-throughput materials data generation and data mining. Atomate makes it easy to automatically generate large datasets by running standardized computational workflows with different simulation packages. Matminer contains tools for featurizing materials data and integrating it with machine learning algorithms and data visualization methods. Both aim to accelerate materials discovery by automating and standardizing computational workflows and data analysis tasks.

(1) The authors present an approach for using FPGAs in high-performance computing (HPC) that involves using functional descriptions, vector type-transformations, and cost-modeling. (2) Their approach uses type transformations to generate design variants from a functional program and develops an intermediate language and cost model. (3) The cost model provides fast, lightweight estimates of performance and resource usage for different design variants to enable automated design space exploration for FPGA-based HPC applications.

This talks explains the motivations for the Co-op technology: what are the challenges it addresses, in particular focusing on reducing accidental complexity, where it comes from, and a general vision on how to resolve it. Then we continue to show practical application of Co-op, including experience figures from large-scale application of a previous generation of this technology. Show a little bit about its realization, and conclude with an evaluation of the technology.

The document discusses design patterns and how they can be taught through refactoring exercises and case studies. It provides an overview of common design patterns such as creational, structural, and behavioral patterns. Examples are given to illustrate how patterns like factory method, builder, strategy, and decorator can be used to solve common object-oriented design problems by varying implementations independently and adding new functionalities through composition instead of inheritance. The talk emphasizes applying principles like open-closed principle and encapsulating variations when refactoring code using patterns.

This document presents a comparative evaluation of Galaxy and Ruffus-based scripting workflows for DNA sequencing analysis pipelines. The research aims to identify the optimal workflow system by implementing DNA-seq analysis pipelines in both Galaxy and Ruffus and benchmarking their performance. Literature on existing workflow systems is reviewed. The document outlines the research objectives, design, methodology, and requirements for the DNA-seq analysis pipeline use case. Preliminary results indicate pros and cons of each approach, with further analysis of performance metrics still needed.

This document discusses model-driven approaches for cloud data storage. It outlines objectives to 1) characterize cloud data storage requirements using conceptual models, 2) select appropriate cloud data storage implementations and providers based on requirements, and 3) manage artifacts for working with different storage solutions. Existing solutions are limited and the proposed approach uses model-driven engineering with multiple levels of modeling and transformation to map between requirements and storage solutions.

The document provides an overview of distance learning standards and specifications, with a focus on the Sharable Content Object Reference Model (SCORM). It describes the key components of SCORM, including the Content Aggregation Model, Runtime Environment, and Sequencing and Navigation specifications. The document also summarizes the evolution of SCORM and related standards organizations involved in e-learning technologies.

This document provides an overview of a talk on advanced Zemax Programming Language (ZPL) macro programming. It introduces the speakers and describes the structure of the talk, which will cover what ZPL is, examples of using ZPL for specific tasks like calculating ray angles of incidence across a pupil, and tips for writing macros. The document outlines several example macros that will be discussed in detail during the talk, including automating repetitive tasks and creating custom operands. It encourages participants to provide feedback and suggestions for additional topics.

This document discusses the development of executable models of fissile reactor systems for hardware simulation and design. The models are converted from DESIRE simulation models to C++ code using an automatic conversion process. This allows the models to be run on Windows computers and used for engineering design and training simulations. The conversion process and numerical integration engine are described. The document also outlines the engineering design interface and simulator backend that have been developed to utilize the executable models.

Python bindings for SAF-AIS APIs offer many advantages to middleware developers, application developers, tool developers and testers. The bindings help to speed up the software development lifecycle and enable rapid deployment of architecture-independent components and services. This session will describe main principles guiding Python bindings implementation, and will have extensive in-depth application Python code examples using SAF-AIS services.

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