Vol. 35 · No. 1

There have been several challenges in summarization of Thai multiple documents since Thai language itself lacks of explicit word/phrase/sentence boundaries. This paper gives definition of Thai Elementary Discourse Unit (TEDU) and then presents our three-stage summarization process. Towards implementation of this process, we propose unit segmentation using TEDUs and their derivatives, unit-graph formation using iterative unit weighting and cosine similarity, and unit selection using highest-weight priority, redundancy removal, and post-selection weight recalculation. To examine performance of the proposed methods, a number of experiments are conducted using fifty sets of Thai news articles with their manually constructed reference summary. By three common evaluation measures of ROUGE-1, ROUGE-2, and ROUGE-SU4, the results evidence that (1) our TEDU-based summarization outperforms paragraph-based summarization, (2) our iterative weighting is superior to traditional TF-IDF, (3) the highest-weight priority without centroid preference and unit redundancy consideration helps improving summary quality, and (4) post-selection weight recalculation tends to raise summarization performance under some certain circumstances.

Information services on the Internet are being used as an important tool to facilitate discovery of the information that is of user interests. Many approaches have been proposed to discover the information on the Internet, while the search engines are the most common ones. However, most of the current approaches of information discovery can discover the keyword-matching information only but cannot recommend the most recent and relative information to users automatically. Sometimes users can give only a fuzzy keyword instead of an accurate one. Thus, some desired information would be ignored by the search engines. Moreover, the current search engines cannot discover the latent but logically relevant information or services for users. This paper measures the semantic-similarity and link-similarity between keywords. Based on that, it introduces the concept of similarity of web pages, and presents a method for information recommendation. The experimental evaluation and comparisons with the existing studies are finally performed.

Formal modelling languages range from strictly textual ones like process algebra scripts to visual modelling languages based on hierarchical graphs like coloured Petri nets. Approaches equipped with visual modelling capabilities make developing process easier and help users to cope with more complex systems. Alvis is a modelling language that combines possibilities of formal models verification with flexibility and simplicity of practical programming languages. The paper deals with hierarchical communication diagrams – the visual layer of the Alvis modelling language. It provides all necessary information to model system structure with Alvis, to manipulate a model hierarchy and to understand a model semantics. All considered concepts are discussed using illustrative examples.

Programming languages greatly influence the way how programs are created and evolved. This means that the use of appropriate language for solved problem can greatly increase developer productivity. Composition of languages can provide great help in construction of a new language from existing components and for integration of several languages that may be needed to effectively solve a complex problem. In this paper we analyze the composition problem on the two levels: composition of languages and composition of concepts in a language. Possibilities of transition from language composition to concepts composition are also presented. Based on that, we propose a framework of languages construction based on concept composition that aims to support reusability of language elements and tools. It uses common host syntax for developed languages. Their semantics is defined in a general-purpose language. Proposed approach is demonstrated on example languages developed using prototype implementation.

In this paper, we apply both supervised and unsupervised machine learning techniques to predict the trend of financial time series based on trading rules. These techniques are K-means for clustering the similar group of data and support vector machine for training and testing historical data to perform a one-day-ahead trend prediction. To evaluate the method, we compare the proposed method with traditional back-propagation neural network and a standalone support vector machine. In addition, to implement this combination method, we use the financial time series data obtained from Yahoo Finance website and the experimental results also validate the effectiveness of the method.

Central authority free multi-authority attribute based encryption scheme for short messages will be presented. Several multi-authority attribute based encryption schemes were recently proposed. We can divide these schemes into two groups, one of them are the ciphertext-policy attribute based encryption schemes (CP-ABE), the another one are the key-policy attribute based encryption schemes (KP-ABE). In our new multi-authority attribute based encryption scheme we combine them: the access structure will be given by authorities and the encryptor in conjunction. The authorities will be able to decide who is able to decrypt a ciphertext under their names, but the encryptor will choose the authorities whom he would involve in the encryption. In addition, our scheme is free of any central authority. The security of our new scheme relies on the decisional 3-party Diffie-Hellman assumption.

We develop a process algebraic framework SVPA for the formal specification and analysis of IEEE 1800 mathrmTM SV designs. The formal semantics of SVPA is defined by means of deduction rules that associate a time transition system with a SVPA process. A set of properties of SVPA is presented for a notion of bisimilarity. SVPA may be regarded as the formal language of a significant subset of IEEE 1800 mathrmTM SV. To show that SVPA is useful for the formal specification and analysis of IEEE 1800 mathrmTM SV designs, we illustrate the use of SVPA with a multiplexer, a synchronous reset D flip-flop and an arbiter.

In heterogeneous networks, network selection by nature is a multi-dimensional problem. Many parameters need to be considered for handover decision making. Apart from handover accuracy and efficiency, an important consideration is the scalability and signaling overhead of such handover algorithms. In this article we propose to break down a Simple Additive Weighting (SAW) based heterogeneous handover algorithm in two parts. The execution of the first part is carried out in an independent and proactive manner prior to the actual handover, assuming three different handover architectures. The handover architectures are differentiated based upon the level of the distribution of the handover algorithm among multiple network components. The Media Independent Handover (MIH) and its different services are used to retrieve and share information among MIH enabled nodes and for conformity among heterogeneous network standards. The proposed algorithm is evaluated with respect to handover accuracy, handover delay efficiency and signaling overhead. The evaluation is carried out for all three handover architectures using simulations. Only handovers between Wi-Fi (IEEE 802.11) and WiMAX (IEEE 802.16) networks are considered. But the handover framework is general and can be extended to consider other wireless and mobile communication networks.

With the creation of BU-3DFE database the research on 3D facial expression recognition has been fostered; however, it is limited by the development of 3D algorithms. Range image is the strategy for solving the problems of 3D recognition based on 2D algorithms. Recently, there are some methods to capture range images, but they are always combined with the preprocess, registration, etc. stages, so it is hard to tell which of these generated range images is of higher quality. This paper introduces two kinds of range images and selects different kinds of features based on different levels of expressions to validate the performances of proposed range images; two other kinds of range images based on previously used nose tip detection methods are applied to compare the quality of generated range images; and finally some recently published works on 3D facial expression recognition are listed for comparison. With the experimental results, we can see that the performances of two proposed range images with different kinds of features are all higher than 88

In the last decades, heuristic algorithms are widely used in solving problems in different fields of science and engineering. Most of these methods are inspired by natural phenomena, such as biological behaviours or physical principles. In this paper, a new optimization method based on the dynamic of sliding motion along a frictionless inclined plane is introduced. In the proposed algorithm, a collection of agents cooperate with each other and move toward better positions in the search space by employing Newton's second law and equations of motion. Our method is compared with other popular optimization algorithms and the results on 23 standard benchmark functions show its effectiveness in most cases.