KES International
Format Instructions for Conference Papers
Text Format
 Margins: 1” or 2.54cm top, bottom, left and right.
 Paper size: A4
 Font: Times New Roman throughout
 Heading: 14 point, bold, centred
 Authors: 10 point, bold, centred
 Affiliations (university or company): 10 point, italic, centred
 Affiliations may be numbered with a superscript index (see example).
 Text of abstract: 10 point, justified
 Sub-headings: 10 point, left justified, bold.
 Use only one or two levels of sub-headings.
Spacing
 One blank line between title and authors (10 point)
 One blank line between authors and affiliations (10 point)
 Two blank lines between affiliations and start of abstract text
 One blank line (10 point) before and after each sub-heading
Columns
 The paper should be in single column format throughout (i.e. not two-column style as required by, for
example, the IEEE)
Length of paper
 As specified on the conference website.
Sections in the Paper
The contents of the paper should be as expected for an academic publication.
The following sections are suggested for guidance: Abstract/Summary
 Introduction including aims
 Background
 Body, practical work, theoretical contribution, etc
 Results
 Discussion
 Conclusions
 References
Example
An example of a paper in the above format is provided on the next two pages.
Condition Monitoring Capability Developed Through a Knowledge
Transfer Partnership between a Small Company and a University
Robert Howlett1, Gareth Davies1 and Terry MacKay2
1
Smart Systems Research Group, University of Brighton, Moulsecoomb, Brighton, BN2 4GJ, United Kingdom
R.J.Howlett@brighton.ac.uk
2
Powertree Ltd, Imperial Way, Crooksdown, North Sussex, NS10 11RZ, United Kingdom
Abstract
This paper describes the benefits that small companies can obtain from the United Kingdom Department of
Trade and Industry Knowledge Transfer Partnerships business support product. The support measure provides
funding for collaborations between universities and companies in order that knowledge and technology transfer
between the partners can occur. Knowledge Transfer Partnerships can support a wide range of commercial
activities, proving there is a solid business case to show that the government support will lead to improvements
in the profitability of the company. This paper describes the Knowledge Transfer Partnerships product. It then
goes on to present a case study of a business collaboration under the scheme between Powertree Ltd, a
manufacturer of laser systems, and the University of Brighton, to implement intelligent condition monitoring in
the Company’s products.
1. Introduction
Developments in how information is searched for and expectations on how information should be presented are
changing rapidly. Customer support is a major department within any successful company, but with the
emergence of the Internet can customers only be expected to receive week day, working hours support in a world
no longer constrained by time and location? This paper looks at the implementation of a web-based customer
support knowledge base system to diagnose customer problems 24 hours a day via the WWW.
The strength of a knowledge base system in its concentrated knowledge within a specific subject domain allows
any potential user access to its valuable ‘expert’ information at all times. For such a system, the incorporation of
concentrated information gathered from a single, or, multiple experts allows the system to outperform many
human experts, with the added attribute of continual accessibility.
The design and implementation of the web support system was gradually implemented into the host company
over a 12 month period. The company requesting the system provide accounting software to their clients
throughout the UK and were in need of a diagnostic web facility to enable them to provide an interactive out-ofhours service.
2. Web-based Customer Support Systems
Online diagnostic support is an area that continues to grow as the need for access to support information at all
times of the day becomes a necessity [1]. The advent of the ever accessible 24 hour knowledge factory [2] will
become a necessity for any business with a customer-base, not just an advantage over competitors.
Giant companies with huge online presence, such as Microsoft or Apple for example, have built online customer
support facilities in order to provide relief to their call centre staff and offer a form of support to their customers
at all times. Indeed even local authorities, funded by UK government, continue to encourage customers to use
the WWW to access information, pay taxes and even diagnose problems.
The National Health Service has a simplified version of their decision support telephone system available via
their website. The diagnostic tool enables a user to help diagnose common health problems through a variety of
multiple choice questions. In it’s first year, 1998, NHS Direct took more than 100,000 calls from patients
seeking advice on medical problems with that number increasing to in excess of six million during 2003 and
2004 [3]. This growth in awareness coincides with NHS Directs figures for their interactive web service
activated during 2001.
6. Conclusions
The web support system provides a real-time solution to customer software support. From a first time user
through to an informed user, the system provides each of its members with a fast, scalable and accessible
platform for knowledge. The primary goal is to provide results to user queries over the WWW. Web support
maintains this process with the added functionality of real time issue tracking, issue logging and financial
information view.
Through the systems seamless integration with financial and CRM applications it is able to capture knowledge
without the requirement of cultural change for the company experts. This can be expected to continue allowing
the system to increase in size. Problems caused by an expected increase in the size of the system have been
anticipated with the incorporation of a duplication check as an entry is uploaded with the opportunity of
amending or rejecting the entry.
The system could be easily adapted for a range of support uses on the WWW. Each of the components of the
system could be deployed individually, for instance if a company required the capacity to provide its customers
with the ability to see outstanding financial information or to facilitate customer access to current issues. The
real strength of the system is within the range of services offered to help the user and encourage re-use and
interaction.
Future work encompasses increased interaction between the host company’s in-house systems and the user
through Web support, and the upgrade of the system’s user interface to accommodate system growth. Further
interaction between user and system will be continually assessed through feedback requests and user suggestion.
System awareness will be developed to ensure all new contract holders are granted access immediately, with
consultants demonstrating the system during the sales presentations and implementation process.
7. References
1.
Rodgers, W. and Negash, S. The effects of web-based technologies on knowledge transfer, Communications
of the ACM, ACM Press. Vol 50:7, pp. 117-122 (2007)
2. Gupta, A. and Seshasai, S. 24-hour knowledge factory: Using Internet technology to leverage spatial and
temporal separations, ACM Transactions on Internet Technology (TOIT), ACM Press. Vol 7:3 (2007)
3. Ghose, S. and Dou, W. Interactive functions and their impacts on the appeal of Internet presence sites.
Journal of Advertising Research. Vol 38, pp. 29–43 (1998)
4. Englard, B. et al. Expert systems in accounting. The CPA journal, April, pp58-62 (1989)
5. Eppinette, M. and Inman, R. A. Expert systems and the implementation of quality customer service,
Industrial Management & Data Systems, MCB University Press. Vol 97: 2, pp. 63-68 (1997)
6. Hui, S. C. et al. A web-based intelligent fault diagnosis system for customer service support. Engineering
Applications of Artificial Intelligent, Elsevier Science Ltd. Vol 14: pp. 537-548 (2001)
7. Brin, S. & Page, L. The Anatomy of a Large-Scale Hypertextual Web Search Engine, Computer Science
Department, Stanford (1998)
8. Lin, J. et al, The Role of Context in Question Answering Systems, CHI 2003 (Extended Abstracts), pp.
1006-1007 (2003)
9. Minsky, M. Steps toward artificial intelligence.Proc. Inst. Radio Eng., 49:8-30 (1961)
10. Lederberg, J. How DENDRAL was conceived & born, ACM Symposium on the history of medical
informatics, National Library of Medicine (1987)
11. Sagheb-Tehrani, M. The design process of expert systems development: some concerns, Expert Systems,
Blackwell Publishing Inc. Vol. 23: 2, pp. 116-125 (2006)
12. Khalifa, M. and Lam. R. 2002. Web-Based Learning: effects on learning process and outcome. IEEE
Transactions on Education, Vol 46:4, pp. 350-356