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Semantic approaches present an efficient, detailed and easily understandable representation of knowledge from documents. Al-Quran contains a vast amount of knowledge that needs appropriate knowledge extraction. A semantic based approach can help in designing an efficient and explainable knowledge representation model for Al-Quran. This research aims to propose a semantic-graph knowledge representation model for verses of Al-Quran based on word dependencies. These features are used in the proposed knowledge representation model allowing the semantic graph matching to improve Al-Quran search applications' accuracy. The proposed knowledge representation model is essentially a formalism for generating a semantic graph representation of Quranic verses, which can be applied for knowledge base construction for other applications such as information retrieval system. A set of rules called Semantic Dependency Triple Rules are defined to be mapped into the semantic graph representing the verse's logic. The rules translate word dependencies and other NLP metadata into a triple form that holds logical information. The proposed model has been tested with English translation of Al-Quran on a document retrieval prototype The basic system has been enhanced with anaphoric pronouns correction, which has shown improvement in retrieval performance. The results have been compared with a closely related system and evaluated on the accuracy of the document retrieval in Precision, Recall and F-score measurements. The proposed model has achieved 65%, 60% and 62.4% for the measurements, respectively. It has also improved the overall accuracy of previous system by 43.8%.

The needed time to send and receive a message among two nodes in an interconnection network has a fundamental role in determining the performance of this network. Therefore, taking a short period of time to send a packet between a source and destination nodes indicates a good performance network with less congestion and latency. Besides, processing data in short-term help in providing fast solutions for many complex problems. Thus, various designs of hierarchical interconnection networks (HINs) for the massively parallel computer (MPC) systems have been presented recently; the main goal of these networks is to replace the conventional ones which showed poor performance in scaling the network size. A Shifted Completely Connected Network (SCCN) proposed as a new HIN topology. Several basic modules (BMs) interconnected hierarchically to create advanced levels networks based on this topology. The structural design and a proposed routing protocol of SCCN discussed in this paper. However, the foremost focus of this work is to evaluate the time cost-effectiveness factor (TCEF) of SCCN in different levels in order to examine the effect of expanding the size of the network on the TCEF. Therefore, the TCEF for the higher levels of SCCN from level (1) to level (3) will be assessed to examine whether SCCN is an effective network in term of time. In addition, the obtained results from each level will be compared to other networks to prove the preeminence of the proposed topology.

Contextual retrieval is a critical component for efficient usage of knowledge hidden behind the data. It is also among the most important factors for user satisfaction. It essentially comprise of two equally important parts – the retrieval mechanism and the knowledge base from which the information is retrieved. Despite the importance, context aware knowledge bases have not received much attention and thereby, limiting the efficiency of precise context aware retrieval. Such knowledge bases would not only contain information that has been efficiently stored but the knowledge contained would be context based. In other words, machines would understand the knowledge and its context rather than just storing data. This would help in efficient and context aware retrieval. The current paper proposes rules and methodologies for construction of such context aware knowledge bases. A case study to demonstrate the application of the methodology and test the efficiency of the proposed methodology has also been presented. The results indicate that knowledge bases built on these principles tend to generate more efficient and better context aware retrieval results.

It is critical to have a knowledge base model for efficient storage of extracted knowledge. This ensures that the knowledge is stored in a meaningful way to be used for different applications. The efficiency of the knowledge base model depends largely on the rules of construction. Knowledge represented using logico-linguistic techniques and semantic networks lack a consistent rule based knowledge model. The current paper deals with the analysis of text from the knowledge extraction, representation and semantic network phase to formulate rules which would lay foundations of a knowledge model. The developed rules seem to be promising providing a comprehensive coverage of different scenarios. The extensive coverage is an indication that the knowledge model will cater to the entire domain knowledge, thereby laying the foundations of automatic construction of efficient knowledge bases.

A Symmetric Midimew Mesh connected network (SMMN) is a hierarchical interconnection networks (HIN) that capable to interconnect vast number of nodes that could reach up to millions of nodes in the network. SMMN has multiple basic modules of 2D-mesh networks that are recursively interconnected by Midimew network to create higher-level networks. In this paper, we explain the architectural details of SMMN,we also present the a deadlock-free routing algorithm for SMMN using four virtual channels and evaluate the performance of dynamic communication of SMMN network using proposed routing algorithm under uniform traffic pattern .We also evaluate the performance of dynamic communication of TESH network using topaz simulator. It is shown that the SMMN network has high throughput and low latency, which yield higher performance of dynamic communication compare to other Hierarchical networks.

The goal of this study was to predict visual acuity (VA) and contrast sensitivity function (CSF) with tissue redness grading after pterygium surgery.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.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 (p0.01) and VA (p0.01). The redness grading was able to predict 25% and 23% of the variance in the CSF and the VA, respectively.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.

This paper discussed the idea of the computer system capable of simulating understanding with respect to reading a text document. The research is concerned with the problem of generating sophisticated knowledge representation for the purpose of understanding the natural language. Due to that, a simplification form of logical-oriented model of knowledge representation called Pragmatic Skolem Clauses (PSC) is proposed to represent the semantic formalism for the computational linguistic. Each set of pragmatic skolem clauses containing at least one skolem constant, which shows the thematic role relationship between clauses. Semantically and pragmatically-accented approach will be discussed in this paper in the context of formal grammar and linguistic semantic.

This paper presents our work on Subject-Action-Object (SAO) extraction as one component needed on patent discovery system development for Islamic Finance and Banking. There are some processes done in order to conduct SAO extraction. They are covering retrieving patents and transforming patents into structured data. We used several patent databases such as USPTO, MyIPO, WIPO, and EPO to collect patents. In patent searching, we used keywords, which were derived from Islamic Finance and Banking phrase, book's title, of which its content is related to Islamic Finance and Banking, and all concepts on Islamic Finance and Banking ontology. Result on SAO extraction will be utilized on the next component on the system i.e. analyzing patents trend using TRIZ evolution trend model.

Hierarchical Interconnection Network (HIN) is indispensable for the practical implementation of future generation massively parallel computer systems which consists of hundred thousands nodes or even millions of nodes. Because it yields good performance with low cost due to reduction of communication links and by exploring the locality in the communication & traffic patterns. A Midimew connected Mesh Network (MMN) is an HIN comprised of numerous basic modules, where the basic modules are 2D-mesh networks and they are hierarchically interconnected using midimew network to construct the higher level networks. In this paper, we present the architecture of a MMN and evaluate the time-cost effective factor of MMN, TESH, mesh, and torus networks. It is found that the proposed MMN yields slightly high time-cost effectiveness factor with small diameter and average distance as compared to other networks. Overall, performance with respect to time-cost effectiveness factor with small diameter and average distance suggests that the proposed MMN will be a indispensable choice for the next generation massively parallel computer systems.

Objectives: This paper describes work in constructing two models of knowledge representation in order to increase the performance of retrieving information on English Quran domain. Due to many approaches available to construct knowledge representation, this paper only focused on ontology-based and graph database-based knowledge representation. Methods: Quranic Arabic Corpus that available at http://www.corpus.quran.com is used as a source to build the knowledge representation. This paper extracted several data from it which include English token, token location, and token Part Of Speech (POS). Protege is used to construct the ontology and Neo4j is utilized in developing the graph database. Findings: This paper has presented a construction process of two models of Knowledge Representation(KR)which are ontology and graph database based KR. These models will be used in developing of an English Quran question answering system in order to discover which model exhibit the best achievement in increasing question answering system performance. Improvements/Applications: The authors hope there will be useful information gained from the question answering system experiments when using both of those models.

A Midimew connected Mesh Network (MMN) is a proposed hierarchical interconnection network in which numerous basic modules are interconnected in a hierarchical fashion to construct a massively parallel computer. Here, the basic module is the first level of the network which is connected by mesh network while higher level network is connected by a midimew network. In this study, we have evaluated a dynamic communication performance of a variety of MMN using the TOPAZ simulator using a deadlock free routing algorithm with uniform traffic patterns, whereby the dimension order routing and virtual cut-through flow control are used. It is found that the saturation throughput of the Virtual MMN (VMMN) is higher than that of Horizontal MMN (HMMN), Symmetric MMN (SMMN), and Tori connected mESH network (TESH).

The knowledge behind the gigantic pool of data remains largely unextracted. Techniques such as ontology design, RDF representations, hpernym extraction, etc. have been used to represent the knowledge. However, the area of logic (FOPL) and linguistics (Semantics) has not been explored in depth for this purpose. Search engines suffer in extraction of specific answers to queries because of the absence of structured domain knowledge. The current paper deals with the design of formalism to extract and represent knowledge from the data in a consistent format. The application of logic and linguistics combined greatly eases and increases the precision of knowledge translation from natural language. The results clearly indicate the effectiveness of the knowledge extraction and representation methodology developed providing intelligence to machines for efficient analysis of data. The methodology helps machines to retrieve precise results in an efficient manner.

Ontology information extraction has gain popularity due to the increasing amount of ontologies developed over the years. World Wide Web Consortium (W3C) has introduced SPARQL query language to extract information. However SPARQL query language follow a specific pattern in order to find the triple through subgraph matching. The keywords used in the SPARQL query have to be exactly same as the existing keywords in the RDF data in-order to extract the required information. The paper introduced a method to ease the job of the user by generating SPARQL query from the query entered by the user. The method uses the object property list generated from the ontology and word's synonym to aid in SPARQL query generation. The result has shown that the proposed method clearly eases the need of the user to learn SPARQL syntax.

In this paper, we present a derivative of Midimew connected Mesh Network (MMN) by reassigning the free links for higher level interconnection for the optimum performance of the MMN; called Derived MMN (DMMN). We present the architecture of DMMN, addressing of nodes, routing of message and evaluate the static network performance. It is shown that the proposed DMMN possesses several attractive features, including constant degree, small diameter, low cost, small average distance, moderate bisection width, and same fault tolerant performance than that of other conventional and hierarchical interconnection networks. With the same node degree, arc connectivity, bisection width, and wiring complexity, the average distance of the DMMN is lower than that of other networks.

Midimew connected Mesh Network (MMN) is a Minimal DIstance MEsh with Wrap-around links (midimew) network. In this paper, we present the architecture of MMN and evaluate the total wire length of MMN, TESH, mesh, and torus networks. It is shown that the proposed MMN possesses simple structure and moderate wire length. The total wire length of MMN is slightly higher than that of mesh network and lower than that of 2-D torus network. Overall performance suggests that, MMN is an optimal network among these networks.

We are in the information intensive environment in which various forms of digital contents have been growing exponentially. In this era of digital data, knowledge representation has been considered as a crucial component of any information retrieval system. It is also considered as a major problem especially in representing the content of unstructured text in an effective way. Although the mission remains impossible to achieve 100% accuracy, many researchers are indulging themselves in documenting these data in many different techniques so that it can be communicated effectively and easily. Indexing is an important element that determines the success of retrieval. Since we are dealing with multiple documents, preprocessing of data is needed before the data gets indexed. Thus, this paper presents an approach on the preprocessing technique. The semantic data which have been represented in skolem clauses will be preprocessed with the help of automatic lexicon generator output and WordNet. This preprocessing plays an important role in getting rid of redundant data before it gets indexed into the semantic matrix. Besides redundancy, it also helps in dealing with common problem that exists in indexing multiple documents in which similar sentences with more or less the same meaning but have been constructed by using different sets of words. As a conclusion, the integration of WordNet and lexicon leads to better result in terms of building effective knowledge representation.

The representation of document content is very important factors in retrieval process. The failure to create a good knowledge representation will definitely lead to failure in terms of its retrieval no matter how good the retrieval engine is. Therefore, this research focused on creating a reliable knowledge representation for our retrieval engine. We are using skolem to capture the information conveyed by multiple text documents and used skolem as an index language. This research also focuses on utilizing the skolem index as its knowledge representation in its question answering system. The system is capable of retrieving the answer as well as states the exact document in which the answer is derived from.

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.

Performance on a question answering system is reflected by the number of correct answers that is produce from a list of alternate choices. However, many answers would appear in documents and passages laden with terms from the query. It becomes more difficult and eventually impossible to make a precise answer to a query. The aim of this study is to determine the keyword of the precise answer to a specific query and illustrate the answer in visual expression. In this paper we propose a method to translate text into visual expression, closest to the correct answer. To achieve a significant illustration capability it is necessary to develop methods of dealing with knowledge base. Firstly, we must consider the real world and the visual expression of key information that can be extracted from the words. The proposed system will analyse and match them using visual semantic simplification description based on logical representation.

The idea of the computer system capable of simulating understanding with respect to reading a story or passage and answering questions pertaining to it, has received increased attention within the NLP community as a means to develop and evaluate robust question answering methods. This research is concerned with the problem of generating an automated answer in the context of sophisticated knowledge representation, reasoning, and logical inferential processing. The research focused on Wh types of question to a restricted domain. External knowledge sources i.e. world knowledge (WK) and hypernyms matching procedure (HMP) were introduced. World knowledge led to the refinement of the ability of the system to extract the relevant answers. It provided a solution to the outstanding problem related to the ambiguity enclosed by anaphora and synonym words. Meanwhile, hypernyms refer to a more general or broad keywords, which was able to widen the results of the search. Thus, hypernyms matching procedure was to give a more coherent meaning of words, and eased in the process of extracting the answer based on a given question. This research found that the combined external knowledge sources on word dependencies improved the accuracy of the question answering system with respect to human performance measures.

Phrases has a long history in information retrieval, particularly in commercial systems. Implicit semantic relationship between words in a form of BaseNP have shown significant improvement in term of precision in many IR studies. Our research focuses on linguistic phrases which is language dependent. Our results show that using BaseNP can improve performance although above 62% of words formation in Malay Language based on derivational affixes and suffixes., {"references":["Atlam, E.S., Fuketa, M., Morita, K., & Aoe, J., Documents Similarity\nMeasurement Using Field Association Terms, Information Processing\nand Management Journal, 39, 2003, pp. 809-824.","Baeza-Yates, R & Ribeiro-Neto, B., Modern Information Retrieval,\nAddison-Wesley, New York, 1999.","Croft, W. B., User-specified Domain Knowledge for Document\nRetrieval, Proceedings Of The ACM Conference On Research And\nDevelopment In Information Retrieval, 1986, pp. 201-206.","Fatimah A., A Malay Language Document Retrieval System: An\nExperimental Approach And Analysis, Ph.D Thesis, Universiti\nKebangsaan Malaysia, 1995","Fagan, J. L, Experiments in Automatic Phrase Indexing for Document\nRetrieval: A Comparison of Syntactic and Non-Syntactic Methods, Ph.D.\nThesis, Department of Computing Science, Cornell University, Ithica,\nNew York, 1987.","Lewis, D.D. and Jones, K.S., Natural Language Processing for\nInformation Retrieval, Communication of the ACM, Vol 39 No. 1 , 1996,\npp. 92-100.","Sanderson, M. ,Word Sense Disambiguation and Information Retrieval,\nProceedings of the Seventeenth Annual International ACM-SIGIR\nConference on Research and Development in Information Retrieval,\n1994, pp. 142-151, Springer-Verlag.","Salton, G., A Blueprint For Automatic Indexing, ACM SIGIR Forum 16,\n2 (Fall 1981), 1981, pp. 22-38.","Salton, C.. and Lesk., M.E. Computer Evaluation Of Indexing And Text\nProcessing, Communication of the ACM, Vol 15 No. 1 , 1986, pp. 6-36.\n[10] Salton, G., Introduction to Modern Information Retrieval, McGraw-Hill,\nNew York, 1983.\n[11] Salton, G., Another Look At Automatic Text Retrieval Systems,\nCommunications of the ACM, Vol 29 No. 7, 1986, pp. 648-656.\n[12] Van Rijsbergen, C.J. Information Retrieval, 2nd edition,\nButterworth.,1979.\n[13] Yun, B. H., H. S. Lim and H.C. Rim, Analysis of Korean Compound\nNouns using Statistical Information, Proc. of the 22nd Korea\nInformation Science Society Spring Conference, 1994, pp 925-928.\n[14] Zainab Abu Bakar, Evaluation Of Retrieval Effectiveness Of Conflation\nMethods On Malay Documents, Ph.D Thesis, Universiti Kebangsaan\nMalaysia, 1999.\n[15] Zainab Abu Bakar & Nurazzah Abdul Rahman, Evaluating The\nEffectiveness Of Thesaurus And Stemming Methods In Retrieving\nMalay Translated Al-Quran Documents, Proceeding Of 6th\nInternational Conference On Asian Digital Libraries, 2003, pp. 653-\n662. Springer-verlag."]}

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.

The previous study of static network performance of a Vertical Midimew connected Mesh Network (VMMN) was shown to be good. However, its dynamic communication performance has not been evaluated yet, we have proposed a deadlock free dimension order routing algorithm using 4 virtual channels. In this paper, The TOPAZ simulator is used to evaluate the dynamic communication performance of a VMMN with virtual cut-through flow control under uniform traffic pattern. We found that the VMMN dynamic communication performance is better than that of the hierarchical TESH network and its counter rival MMN.