GHIRS: integration of hotel management systems by web services

Nowadays web services technology is widely used to integrate heterogeneous systems and develop new applications. In this paper, an application of integration of hotel management systems by web services technology is presented. The Group Hotel Integration Reservation System (GHIRS) integrates lots of systems of hotel industry such as Front Office system, Property Management system, Enterprise Information System (EIS), Enterprise Information Portal system (EIP), Customer Relationship Management system (CRM) and Supply Chain Management system (SCM) together. This integration solution can add or expand hotel software system in any size of hotel chains environment.

A new approach for reducing blocking artefacts using linear filter for block based transform coded images

This paper presents a new approach to filtering the reconstructed image of block based transform coded images.

A simulation model for video traffic performance via ATM over TCP/IP

Although TCP has emerged as the standard in data communication, the introduction of ATM technology has raised numerous problems regarding the effectiveness of using TCP over A TM networks, especially when video traffic performance is considered. This paper presents a simulation model for transmission performance of video traffic via ATM over TCP/IP. The interactivity between TCP/IP and ATM, generation of MPEG traffic and evaluation of traffic performance are implemented in the model. The design and implementation details of the model are carefully described. The experiments conducted using the model and experimental results are briefly introduced, revealing the capability of our model in simulating network events and in evaluating potential solutions to performance issues.

MPEG Traffic Performance via TCP over ATM

A large volume of TCP/IP traffic is currently, and in the future will be, carried over ATM networks. A major part of the traffic, which is produced by multimedia sources, is encoded using the MPEG standard. For the performance analysis of transferring MPEG video sequence via TCP/IP over A TM networks, there is a need for appropriate simulation models. This paper describes one such simulation model that we have constructed. A sct of preliminary simulation experiments have been conducted with the mode to assess the impact of different network configurations on the MPEG traffic transmission performance. Our simulation model is able to simulate many of the potential performance issues regarding video traffic via TCPIIP and A TM and can be used to evaluate any potential solutions.

Reducing blocking artefacts in MPEG video coded images using entropic methods

In this paper investigation is made of the. use of entropic methods to identify smooth image blocks in order to filter the reconstructed image of block based transform coded images. We know that blocking artefact is Visually more prominent in the smooth region of a block rather than in the textured region. The entropic methods are employed to distinguish between smooth and textured blocks in a reconstructed image. The linear filtering is then carried out on the smooth region of the image to reduce the blocking artefact. The en tropic criteria investigated in this paper are: Shannon's (Logarithmic) Entropy, Exponential Entropy, and Quadratic Entropy.

The major drawbacks to the use of wireless communication products in education

This paper considers the use of wireless devices as an educational facilitator both in the classroom and in a business environment.  There are many characteristics of such devices which are favourable to their use in such settings.  But there are also problems.  We identify the main problematic areas as being security, low speed and reliability, and the lack of interoperability.  In our opinion, the use of wireless devices for educational purposes will grow quickly, and the problems of reliability, speed and standards will be overcome.  However, the issue of security will remain a major problem into the distant future.

Quality-of-service routing for web-based multimedia servers

Quality-of-Service is an important issue in multimedia applications; so far most of the research focuses on bandwidth guarantee, few pays attention to the server performance guarantee. In this paper we pay more attention to the server performance guarantee under the prerequisite of guaranteed bandwidth quality. We take advantage of anycast to find the "best" multimedia server among a distributed server group in terms of bandwidth, the request will be submitted to the selected server, moreover, the selected server's neighbours' (all the servers with feasible paths) addresses are delivered to the selected server simultaneously. If the selected server can not guarantee the QoS for the request in terms of server performance, then a proposed QoS-Aware Server Load Deviation (QASLD) mechanism wiII be employed, which will deliver the request to one of its neighbours until there exists a suitable server that can guarantee the server performance for the request. Our experiments show that the proposed QASLD algorithm works well.

Filtering mobile spam by support vector machine

Currently mobile spam has been a major menace to the development of wireless networks. In this paper, the mobile spam problem and its countermeasures are analysed. In particular, we propose a Support Vector Machine to filter mobile spam. This mobile spam filtering system can be deployed in current wireless networks and achieve good performance in protecting end users and operators from mobile spam. Legislation issues and challenges to defend mobile spam are also discussed in the latter part of this paper.

Performance of statistical inference for block classification in reducing blocking artefact in video coded images

This paper presents a performance study of four statistical test algorithms used to identify smooth image blocks in order to filter the reconstructed image of a video coded image. The four algorithms considered are the Coefficient of Variation (CV), Exponential Entropy of Pal and Pal (E), Shannon's (Logarithmic) Entropy (H), and Quadratic Entropy (Q). These statistical algorithms are employed to distinguish between smooth and textured blocks in a reconstructed image. The linear filtering is carried out on the smooth blocks of the image to reduce the blocking artefact. The rationale behind applying the filter on the smooth blocks only is that the blocking artefact is visually more prominent in the smooth region of an image rather than in the textured region.

Performance analysis of algorithms for frequent pattern generation

Data mining refers to extracting or "mining" knowledge from large amounts of data. It is also called a method of "knowledge presentation" where visualization and knowledge representation techniques are used to present the mined knowledge to the user. Efficient algorithms to mine frequent patterns are crucial to many tasks in data mining. Since the Apriori algorithm was proposed in 1994, there have been several methods proposed to improve its performance. However, most still adopt its candidate set generation-and-test approach. In addition, many methods do not generate all frequent patterns, making them inadequate to derive association rules. The Pattern Decomposition (PD) algorithm that can significantly reduce the size of the dataset on each pass makes it more efficient to mine all frequent patterns in a large dataset. This algorithm avoids the costly process of candidate set generation and saves a large amount of counting time to evaluate support with reduced datasets. In this paper, some existing frequent pattern generation algorithms are explored and their comparisons are discussed. The results show that the PD algorithm outperforms an improved version of Apriori named Direct Count of candidates & Prune transactions (DCP) by one order of magnitude and is faster than an improved FP-tree named as Predictive Item Pruning (PIP). Further, PD is also more scalable than both DCP and PIP.

Medical image classification using an efficient data mining technique

Data mining refers to extracting or "mining" knowledge from large amounts of data. It is an increasingly popular field that uses statistical, visualization, machine learning, and other data manipulation and knowledge extraction techniques aimed at gaining an insight into the relationships and patterns hidden in the data. Availability of digital data within picture archiving and communication systems raises a possibility of health care and research enhancement associated with manipulation, processing and handling of data by computers.That is the basis for computer-assisted radiology development. Further development of computer-assisted radiology is associated with the use of new intelligent capabilities such as multimedia support and data mining in order to discover the relevant knowledge for diagnosis. It is very useful if results of data mining can be communicated to humans in an understandable way. In this paper, we present our work on data mining in medical image archiving systems. We investigate the use of a very efficient data mining technique, a decision tree, in order to learn the knowledge for computer-assisted image analysis. We apply our method to the classification of x-ray images for lung cancer diagnosis. The proposed technique is based on an inductive decision tree learning algorithm that has low complexity with high transparency and accuracy. The results show that the proposed algorithm is robust, accurate, fast, and it produces a comprehensible structure, summarizing the knowledge it induces.