Adaptive business intelligence for an open negotiation environment

Engineering of negotiation model allows to develop effective heuristic for business intelligence. Digital ecosystems demand open negotiation models. To define in advance effective heuristics is not compliant with the requirement of openness. The new challenge is to develop business intelligence in advance exploiting an adaptive approach. The idea is to learn business strategy once new negotiation model rise in the e-market arena. In this paper we present how recommendation technology may be deployed in an open negotiation environment where the interaction protocol models are not known in advance. The solution we propose is delivered as part of the ONE Platform, open source software that implements a fully distributed open environment for business negotiation

Embedding objects into Matlab/Simulink for process supervision

This paper introduces how artificial intelligence technologies can be integrated into a known computer aided control system design (CACSD) framework, Matlab/Simulink, using an object oriented approach. The aim is to build a framework to aid supervisory systems analysis, design and implementation. The idea is to take advantage of an existing CACSD framework, Matlab/Simulink, so that engineers can proceed: first to design a control system, and then to design a straightforward supervisory system of the control system in the same framework. Thus, expert systems and qualitative reasoning tools are incorporated into this popular CACSD framework to develop a computer aided supervisory system design (CASSD) framework. Object-variables an introduced into Matlab/Simulink for sharing information between tools

Assignment on Matlab

Considers sampling, quantisation, filters and lines of best fit.

Introduction to Matlab - a self-study tutorial

Matlab is a high level language that is very easy to use and very powerful. It comes with a wealth of libraries and toolboxes, that you can use directly, so that you don't need to program low level functions. It enables you to display results very easily on graphs and images. To get started with it, you need to understand how to manipulate and represent data, and how to find information about the available functions. During this self-study tutorial, you will learn: 1- How to start Matlab. 2- How you can find out all the information you need. 3- How to create simple vectors and matrices. 4- What functions are available and how to find them. 5- How to plot graphs of functions. 6- How to write a script. After this (should take about an hour), you will know most of what you need to know about Matlab and should definitely know how to go on learning about it on your own…

Matlab self study tutorial - Graphing

These resources are designed to support students in gaining more confidence with using Matlab. The PDFs provide guidance and information; Objectives: Introduce basic syntax and data preparation for graphing with Matlab by providing some data, examples of code and some background documents. Outcomes: -how to write an m file script -the importance of syntax -how to load files -how to produce simple graphs -where to get help and further examples There are also some data files to provide example data for students to work with in producing Matlab resources.

Assignment on Matlab

Considers systems of linear equations, steepest ascent optimisation and Monte Carlo simulation.

Laboratory on Matlab

Considers various basic features of Matlab

Laboratory on Matlab

Considers function handles, matrix manipulation, 3D plots and programming

Matlab Code for Modulators

Considers Sampling, Pulse Amplitude Modulation, Multiple Access, Quantisation, Pulse Coded Modulation, Manchester Line Coding, Amplitude Modulation, Double SideBand Suppressed Carrier Modulation, Quadrature Amplitude Modulation and M-ary Shift Keying.

Matlab Code for Entropy Coding

Considers Huffman coding and arithmetic coding

Overview of the Southampton Learning Environment and EdShare

Created to inform the university on current progress on building the SLE and to encourage more use of EdShare

A User-Centric Approach to eCertificate for Electronic Identities (eIDs) Management in Mobile Environment

The use of electronic documents is constantly growing and the necessity to implement an ad-hoc eCertificate which manages access to private information is not only required but also necessary. This paper presents a protocol for the management of electronic identities (eIDs), meant as a substitute for the paper-based IDs, in a mobile environment with a user-centric approach. Mobile devices have been chosen because they provide mobility, personal use and high computational complexity. The inherent user-centricity also allows the user to personally manage the ID information and to display only what is required. The chosen path to develop the protocol is to migrate the existing eCert technologies implemented by the Learning Societies Laboratory in Southampton. By comparing this protocol with the analysis of the eID problem domain, a new solution has been derived which is compatible with both systems without loss of features.

Personal Learning Environments? or Society’s Learning Environment?

Keynote Presentation at PLE2011. What kind of Web have we got? What kind of Web does a Learning Individual need? What kind of Web does a Learning Society need?

Southampton Learning Environment

This interactive diagram provides an overview of the SLE at the start of 2015 - this vision is likely to evolve and further versions of the diagram will follow.

Intro to Matlab for Oceanography: Micro-lectures

This is a collection of 12 micro-lectures, to be used by students in advance of practical sessions. Durations range for 3 min to 10 min. Topics include: ****** 1. Introduction ****** 2. Data classes ****** 3. Matrices ****** 4. Getting help ****** 5. Index notation ****** 6. 1- and 2-dimensional data ****** 7. 3-dimensional data ****** 8. Booleans (True/False) ****** 9. Designing a programme (Algorithms) ****** 10. Flow control: If-then statements ****** 11. Flow control: For-do loops ****** 12. Making nicer figures ******