Tengku Mohd Tengku Sembok

Noise removal and enhancement of binary images using morphological operations

Mathematical morphological operations are commonly used as a tool in image processing for extracting image components that are useful in the representation and description of region shape. In this paper, six basic morphological operations are investigated to remove noise and enhance the appearance of binary images. Dilation, erosion, opening, closing, fill and majority operations are tested on twenty-five images and subjectively evaluated based on perceived quality of the enhanced images. Results of the experiments showed that noise can be effectively removed from binary images using combinations of erode-dilate operations. Also, the binary images are significantly enhanced using combinations of majority-close operations.

Query expansion using thesaurus in improving Malay Hadith retrieval system

Thesaurus has become another valuable structure in any Information Retrieval system. It is a list of terms and concepts that provide a controlled vocabulary of words to use in document indexing, clustering, searching and retrieval. This paper present the results of expanding users query using Malay thesaurus in the process of searching Malay documents from Malay Hadith retrieval system. The results obtained shows that the retrieval effectiveness improves by four percent when thesaurus is employed in the process of retrieving Malay translated Hadith documents, compared to when single term queries are employed.

Arabic part-of-speech tagger based Support Vectors Machines

Support vector machines (SVMs) and related kernel methods have become widely known tools for text mining tasks such as classification and regression. The Arabic part of speech (POS) based support vectors machine is designed and implemented. The NeuroSolutions software is used to adopt and learn the proposed tagger. The radial basis functions (RBFs) is used as a linear function approximator. The experiments has give an evinced that the SVMs tagger is accurate of (99.99%), has low processing time, and use a little a mount of data at training phase.

Word agreement and ordering in English-Arabic machine translation

Machine Translation has been defined as the process that utilizes computer software to translate text from one natural language to another[2].This definition involves accounting for the grammatical structure of each language and using rules and grammars to transfer the grammatical structure of the source language (SL) into the target language (TL). Agreement and Word-ordering play an important role with this structure, as MT should handle agreement between the subject and verb where the number gender, person and features of the subject are important factors in the derivation of the verb as well as the features of the verb itself. Other agreements are required between the adjective and the noun where Arabic adjectives depend on the number, gender and person as well as the definiteness and indefiniteness of the noun. Some other agreements also exist between the numbers and the countable nouns. This paper examines the agreement and word-order rules in tackling Arabic MT systems. Special attention is given to Tarjim by Sakhr Software Company which pioneered a new generation of Arabic Natural Language Processing (NLP) technologies. The approach adopted is flexible and scalable, and the main advantages are: first, it is a rule-based approach, and second, it can be applied on other languages with minor modifications. A major design goal of this system is that it can be used as a stand-alone tool and can be very well integrated with a general machine translation system for English sentence.

Architecture and Network-on-Chip Implementation of a New Hierarchical Interconnection Network

A Midimew-connected Mesh Network (MMN) is a minimal distance mesh with wrap-around links network of multiple basic modules (BMs), in which the BMs are 2D-mesh networks that are hierarchically interconnected for higher-level networks. In this paper, we present the architecture of the MMN, addressing of node, routing of message, and evaluate the static network performance of MMN, TESH, mesh and torus networks. In addition, we propose the network-on-chip (NoC) implementation of MMN. With innovative combination of diagonal and hierarchical structure, the MMN possesses several attractive features, including constant degree, small diameter, low cost, small average distance, moderate bisection width and high fault tolerant performance than that of other conventional and hierarchical interconnection networks. The simple architecture of MMN is also highly suitable for NoC implementation. To implement all the links of level-3 MMN, only four layers are needed which is feasible with current and future VLSI technologies.

Automatic Lexicon Generator for Logic Based Question Answering System

Computer science is in the more challenging era due to the digital growth and demand that we are facing today. A typical IR system will not go far enough as it uses keyword in order to retrieve the desired information. On the other hand, natural language question answering which is based on logic retrieval have proven to perform better than other methods. The most important component of question answering system is the lexicon. Researchers have identified this as the backbone of any NLP system. In this paper we present our approach on how an automatic lexicon generator has been integrated with question answering system which uses logical inference model. This paper also shows on how the automatic lexicon generator has helped in creating knowledge representation to be used by logic based question answering system. Besides that, the lexicon generated managed to reduce significant amount of time and manpower. It has also helped to make the question answering system to be more robust.

Automatic lexicon generator

Over the past decades, computer revolution has opened up many possibilities for new field of investigation. With greater accessibility to information and lowering cost of powerful computers, this has spawned new efforts towards understanding complex tasks. Lexicon in particular has long been recognized as interesting and challenging because of its complexness. It is the knowledge of individual words in the language that has been perceived as central component for all types of natural language processing system. In this paper we present an algorithm to create an automatic lexicon generator in order to generate lexicon from an input document by making use of Apple Pie Parser. The lexicon generated managed to reduce significant amount of time and manpower drastically. Psycholinguists as well as computational linguists can benefit from this automatic lexicon construction.

Long Wire Length of Midimew-Connected Mesh Network

Minimal DIstance MEsh with Wrap-around links (Midimew) connected Mesh Network (MMN) is a hierarchical interconnection network consists of several Basic Modules (BM), where the BM is a 2D-mesh network and the higher level network is a midimew network. In this paper, we present the architecture of MMN and evaluate the number of long wires, length of a long wire, and the total length for the long wire of MMN, TESH, and torus networks. It is shown that the proposed MMN possesses simple structure and moderate wire length. The long wire length of MMN is slightly higher than TESH network and far lower than that of 2D torus network. Overall performance suggests that, MMN is a good choice for future generation massively parallel computers.

Weighted Watson-Crick automata

There are tremendous works in biotechnology especially in area of DNA molecules. The computer society is attempting to develop smaller computing devices through computational models which are based on the operations performed on the DNA molecules. A Watson-Crick automaton, a theoretical model for DNA based computation, has two reading heads, and works on double-stranded sequences of the input related by a complementarity relation similar with the Watson-Crick complementarity of DNA nucleotides. Over the time, several variants of Watson-Crick automata have been introduced and investigated. However, they cannot be used as suitable DNA based computational models for molecular stochastic processes and fuzzy processes that are related to important practical problems such as molecular parsing, gene disease detection, and food authentication. In this paper we define new variants of Watson-Crick automata, called weighted Watson-Crick automata, developing theoretical models for molecular stochastic and fuzzy proce...

Prediction of Changes in Visual Acuity and Contrast Sensitivity Function by Tissue Redness after Pterygium Surgery

ABSTRACT Purpose: The goal of this study was to predict visual acuity (VA) and contrast sensitivity function (CSF) with tissue redness grading after pterygium surgery. Materials and methods: A total of 67 primary pterygium participants were selected from patients who visited an ophthalmology clinic. We developed a semi-automated computer program to measure the pterygium fibrovascular redness from digital pterygium images. The final outcome of this software is a continuous scale grading of 1 (minimum redness) to 3 (maximum redness). The region of interest (ROI) was selected manually using the software. Reliability was determined by repeat grading of all 67 images, and its association with CSF and VA was examined. Results: The mean and standard deviation of redness of the pterygium fibrovascular images was 1.88 ± 0.55. Intra-grader and inter-grader reliability estimates were high with intraclass correlation ranging from 0.97 to 0.98. The new grading was positively associated with CSF (p < 0.01) and VA (p < 0.01). The redness grading was able to predict 25% and 23% of the variance in the CSF and the VA, respectively. Conclusions: The new grading of pterygium fibrovascular redness can be reliably measured from digital images and showed a good correlation with CSF and VA. The redness grading can be used in addition to the existing pterygium grading.