Dave Elliman

Examination Timetabling in British Universities: A Survey

This paper describes the results of a questionnaire on examination timetabling sent to the registrars of ninety five British Universities. The survey asked questions in three specific categories. Firstly, universities were asked about the nature of their examination timetabling problem: how many people, rooms, periods are involved and what difficulties are associated with the problem? Secondly, we asked about how the problem is solved at their institution and whether a manual or automated system is used. Lastly, we asked what qualities are required in a good timetable. We conclude by making some comments, based on the survey replies, as to what sort of criteria a general automated timetabling system must meet.

A University Timetabling System Based on Graph Colouring and Constraint Manipulation

AbstractThe problem of constructing an automated system for use with timetabling is particularly well known. Many programs exist for this task, but they perform well only in particular, isolated environments. Currently being developed is a general system that will be able to cope with the ever-changing requirements of large educational institutions. This article presents a description of the methods and techniques behind such a system. Graph colouring and room allocation algorithms are presented, and ways of combining the two to provide a basis for a flexible and widely applicable timetabling system are shown. This article also describes how several common timetabling features can be handled within the system. The problems of intractability are overcome by producing a spreadsheet-type system that the user can guide in an informed and useful way. This gives the user control of the search and offers the possibility of backtracking where no reasonable solution is found, while still letting the heuristic algo...

Off-line Recognition of Handwritten Arabic Words Using Multiple Hidden Markov Models

Hidden Markov Models (HMM) have been used with some success in recognising printed Arabic words. In this paper, a complete scheme for unconstrained Arabic handwritten word recognition based on a Multiple discriminant Hidden Markov Models is presented and discussed. The overall engine of this combination of a global feature scheme with an HMM module, is a system able to classify Arabic-Handwritten words and has been tested on one hundred different writers. The system first attempts to remove some of the variation in the images that do not affect the identity of the handwritten word. Next, the system codes the skeleton and edge of the word such that feature information about the strokes in the skeleton is extracted. Then, a classification process based on a rule based classifier is used as that a global recognition engine to classify words into eight groups. Finally, for each group, the HMM approach is used for trial classification. The output is a word in the lexicon. A detailed experiment has been carried out, and successful recognition results are reported.

A data base for Arabic handwritten text recognition research

In this paper we present a new database for off-line Arabic handwriting recognition, together with associated preprocessing procedures. We have developed a new database for the collection, storage and retrieval of Arabic handwritten text (AHDB). This is an advance both in terms of the size of the database as well as the number of different writers involved. We further designed an innovative, simple yet powerful, in place tagging procedure for our database. It enables us to easily extract the bitmaps of words. We also constructed a preprocessing class, which contains some useful preprocessing operations. In this paper the most popular words in Arabic writing were identified for the first time, using an associated program.

Recognition of off-line handwritten Arabic words using hidden Markov model approach

Hidden Markov models (HMM) have been used with some success in recognizing printed Arabic words. In this paper, a complete scheme for totally unconstrained Arabic handwritten word recognition based on a model discriminant HMM is presented. A complete system able to classify Arabic handwritten words of one hundred different writers is proposed and discussed. The system first attempts to remove some of variation in the images that do not affect the identity of the handwritten word. Next, the system codes the skeleton and edge of the word so that feature information about the lines in the skeleton is extracted. Then a classification process based on the HMM approach is used. The output is a word in the dictionary. A detailed experiment is carried out and successful recognition results are reported.

Specialised Recombinative Operators for Timetabling Problems

This paper discusses a series of recombination operators for the timetabling problem. These operators act upon a direct representation of the timetable and maintain the property of feasibility. That is that there are no conflicts and no overfilled rooms. Various approaches to solving the timetabling problem using evolutionary computing methods are first compared. The recombination operators are then presented and various alternatives for incorporating heuristic knowledge in the search are described. Finally, results are presented comparing the operators on a real timetabling problem.

A general framework for the evaluation of symbol recognition methods

Performance evaluation is receiving increasing interest in graphics recognition. In this paper, we discuss some questions regarding the definition of a general framework for evaluation of symbol recognition methods. The discussion is centered on three key elements in performance evaluation: test data, evaluation metrics and protocols of evaluation. As a result of this discussion we state some general principles to be taken into account for the definition of such a framework. Finally, we describe the application of this framework to the organization of the first contest on symbol recognition in GREC’03, along with the results obtained by the participants.

Near-Duplicate Image Recognition and Content-based Image Retrieval using Adaptive Hierarchical Geometric Centroids

In this paper, we present a new feature extraction method that simultaneously captures the global and local characteristics of an image by adaptively computing hierarchical geometric centroids of the image. We show that these hierarchical centroids have some very interesting properties such as illumination invariant and insensitive to scaling. We have applied the method for near-duplicate image recognition and for content-based image retrieval. We present experimental results to show that our method works effectively in both applications

TIF2VEC, An Algorithm for Arc Segmentation in Engineering Drawings

This paper describes a method for the recognition of arcs and circles in engineering drawings and other scanned images containing linework. The approach is based on vectorizing a binary image, smoothing the vectors to a sequence of small straight lines, and then attempting to fit arcs. The software was successful in winning first prize in the arc segmentation contest held at GREC 2001, and the results are presented in the context of this evaluation.

The Automation of the Timetabling Process in Higher Education

The task of creating a university timetable has always been a difficult one. In the United Kingdom, the recent growth in student numbers and the adoption of modular degree structures by many institutions has made the scheduling of university courses and exams an even bigger problem than it used to be. In this article we will discuss automatic timetable generation. We will consider the use of traditional methods such as graph coloring and of advanced modern methods such as the application of genetic algorithms.