Rough sets theory for travel demand analysis in Malaysia

This study integrates the rough sets theory into tourism demand analysis. Originated from the area of Artificial Intelligence, the rough sets theory was introduced to disclose important structures and to classify objects. The Rough Sets methodology provides definitions and methods for finding which attributes separates one class or classification from another. Based on this theory can propose a formal framework for the automated transformation of data into knowledge. This makes the rough sets approach a useful classification and pattern recognition technique. This study introduces a new rough sets approach for deriving rules from information table of tourist in Malaysia. The induced rules were able to forecast change in demand with certain accuracy

Grid service discovery with rough sets

Copyright [2008] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.The computational grid is evolving as a service-oriented computing infrastructure that facilitates resource sharing and large-scale problem solving over the Internet. Service discovery becomes an issue of vital importance in utilising grid facilities. This paper presents ROSSE, a Rough sets based search engine for grid service discovery. Building on Rough sets theory, ROSSE is novel in its capability to deal with uncertainty of properties when matching services. In this way, ROSSE can discover the services that are most relevant to a service query from a functional point of view. Since functionally matched services may have distinct non-functional properties related to Quality of Service (QoS), ROSSE introduces a QoS model to further filter matched services with their QoS values to maximise user satisfaction in service discovery. ROSSE is evaluated in terms of its accuracy and efficiency in discovery of computing services

An intelligent recommendation system framework for student relationship management

In order to enhance student satisfaction, many services have been provided in order to meet student needs. A recommendation system is a significant service which can be used to assist students in several ways. This paper proposes a conceptual framework of an Intelligent Recommendation System in order to support Student Relationship Management (SRM) for a Thai private university. This article proposed the system architecture of an Intelligent Recommendation System (IRS) which aims to assist students to choose an appropriate course for their studies. Moreover, this study intends to compare different data mining techniques in various recommendation systems and to determine appropriate algorithms for the proposed electronic Intelligent Recommendation System (IRS). The IRS also aims to support Student Relationship Management (SRM) in the university. The IRS has been designed using data mining and artificial intelligent techniques such as clustering, association rule and classification

Manufacturing Barriers to Biologics Competition and Innovation

As finding breakthrough small-molecule drugs gets harder, drug companies are increasingly turning to “large molecule” biologics. Although biologics represent many of the most promising new therapies for previously intractable diseases, they are extremely expensive. Moreover, the pathway for generic-type competition set up by Congress in 2010 is unlikely to yield significant cost savings. In this Article, we provide a fresh diagnosis of, and prescription for, this major public policy problem. We argue that the key cause is pervasive trade secrecy in the complex area of biologics manufacturing. Under the current regime, this trade secrecy, combined with certain features of FDA regulation, not only creates high barriers to entry of indefinite duration but also undermines efforts to advance fundamental knowledge. In sharp contrast, offering incentives for information disclosure to originator manufacturers would leverage the existing interaction of trade secrecy and the regulatory state in a positive direction. Although trade secrecy, particularly in complex areas like biologics manufacturing, often involves tacit knowledge that is difficult to codify and thus transfer, in this case regulatory requirements that originator manufacturers submit manufacturing details have already codified the relevant tacit knowledge. Incentivizing disclosure of these regulatory submissions would not only spur competition but it would provide a rich source of information upon which additional research, including fundamental research into the science of manufacturing, could build. In addition to provide fresh diagnosis and prescription in the specific area of biologics, the Article contributes to more general scholarship on trade secrecy and tacit knowledge. Prior scholarship has neglected the extent to which regulation can turn tacit knowledge not only into codified knowledge but into precisely the type of codified knowledge that is most likely to be useful and accurate. The Article also draws a link to the literature on adaptive regulation, arguing that greater regulatory flexibility is necessary and that more fundamental knowledge should spur flexibility. A vastly shortened version of the central argument that manufacturing trade secrecy hampers biosimilar development was published at 348 Science 188 (2015), available online