Search results for: word meaning retrieval

Authors: Chen Wu, Xiaohua Hu

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This paper proposes rough set models with three different level knowledge granules in incomplete information system under tolerance relation by similarity between objects according to their attribute values. Through introducing dominance relation on the discourse to decompose similarity classes into three subclasses: little better subclass, little worse subclass and vague subclass, it dismantles lower and upper approximations into three components. By using these components, retrieving information to find naturally hierarchical expansions to queries and constructing answers to elaborative queries can be effective. It illustrates the approach in applying rough set models in the design of information retrieval system to access different granular expanded documents. The proposed method enhances rough set model application in the flexibility of expansions and elaborative queries in information retrieval.

Keywords: Incomplete information system, Rough set model, tolerance relation, dominance relation, approximation, decomposition, elaborative query.

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Authors: M. Garcia-Alsina, J. Cobarsí

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The role of controlled vocabularies in information retrieval is broadly recognized as a relevant feature. Besides, there is a standing demand that editors and databases should consider the effective introduction of controlled vocabularies in their procedures to index scientific literature. That is especially important because information retrieval is pointed out as a significant point to drive systematic literature review. Hence, a first question emerges: Are the controlled vocabularies at this moment considered? On the other hand, subject searching in the catalogs is complex mainly due to the dichotomy between keywords from authors versus keywords based on controlled vocabularies. Finally, there is some demand to unify the terminology related to health to make easier the medical history exploitation and research. Considering these features, this paper focuses on controlled vocabularies related to the health field and their role for storing, classifying, and retrieving relevant literature. The objective is knowing which role plays the controlled vocabularies related to the health field to index and retrieve research literature in data bases such as Web of Science (WoS) and Scopus. So, this exploratory research is grounded over two research questions: 1) Which are the terms considered in specific controlled vocabularies of the health field; and 2) How papers are indexed in relevant databases to be easily retrieved, considering keywords vs specific health’ controlled vocabularies? This research takes as fieldwork the controlled vocabularies related to health and the scientific interest for 1918 flu pandemic, also known equivocally as ‘Spanish flu’. This interest has been fostered by the emergence in the early 21st of epidemics of pneumonic diseases caused by virus. Searches about and with controlled vocabularies on WoS and Scopus databases are conducted. First results of this work in progress are surprising. There are different controlled vocabularies for the health field, into which the terms collected and preferred related to ‘1918 pandemic’ are identified. To summarize, ‘Spanish influenza epidemic’ or ‘Spanish flu’ are collected as not preferred terms. The preferred terms are: ‘influenza’ or ‘influenza pandemic, 1918-1919’. Although the controlled vocabularies are clear in their election, most of the literature about ‘1918 pandemic’ is retrievable either by ‘Spanish’ or by ‘1918’ disjunct, and the dominant word to retrieve literature is ‘Spanish’ rather than ‘1918’. This is surprising considering the existence of suitable controlled vocabularies related to health topics, and the modern guidelines of World Health Organization concerning naming of diseases that point out to other preferred terms. A first conclusion is the failure of using controlled vocabularies for a field such as health, and in consequence for WoS and Scopus. This research opens further research questions about which is the role that controlled vocabularies play in the instructions to authors that journals deliver to documents’ authors.

Keywords: Controlled vocabularies, indexing, 1918 influenza, information retrieval, keywords, 1918 pandemic, scientific databases.

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Authors: Salim Ouchtati, Jean Sequeira, Mouldi Bedda

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In the context of the handwriting recognition, we propose an off line system for the recognition of the Arabic handwritten words of the Algerian departments. The study is based mainly on the evaluation of neural network performances, trained with the gradient back propagation algorithm. The used parameters to form the input vector of the neural network are extracted on the binary images of the handwritten word by several methods. The Distribution parameters, the centered moments of the different projections of the different segments, the centered moments of the word image coding according to the directions of Freeman, and the Barr features applied binary image of the word and on its different segments. The classification is achieved by a multi layers perceptron. A detailed experiment is carried and satisfactory recognition results are reported.

Keywords: Handwritten word recognition, neural networks, image processing, pattern recognition, features extraction.

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Authors: Sameh H. Ghwanmeh

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In this study a clustering technique has been implemented which is K-Means like with hierarchical initial set (HKM). The goal of this study is to prove that clustering document sets do enhancement precision on information retrieval systems, since it was proved by Bellot & El-Beze on French language. A comparison is made between the traditional information retrieval system and the clustered one. Also the effect of increasing number of clusters on precision is studied. The indexing technique is Term Frequency * Inverse Document Frequency (TF * IDF). It has been found that the effect of Hierarchical K-Means Like clustering (HKM) with 3 clusters over 242 Arabic abstract documents from the Saudi Arabian National Computer Conference has significant results compared with traditional information retrieval system without clustering. Additionally it has been found that it is not necessary to increase the number of clusters to improve precision more.

Keywords: Hierarchical K-mean like clustering (HKM), Kmeans, cluster centroids, initial partition, and document distances

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Authors: K. Sakthivel, R. Nallusamy, C. Kavitha

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The system is designed to show images which are related to the query image. Extracting color, texture, and shape features from an image plays a vital role in content-based image retrieval (CBIR). Initially RGB image is converted into HSV color space due to its perceptual uniformity. From the HSV image, Color features are extracted using block color histogram, texture features using Haar transform and shape feature using Fuzzy C-means Algorithm. Then, the characteristics of the global and local color histogram, texture features through co-occurrence matrix and Haar wavelet transform and shape are compared and analyzed for CBIR. Finally, the best method of each feature is fused during similarity measure to improve image retrieval effectiveness and accuracy.

Keywords: Color Histogram, Haar Wavelet Transform, Fuzzy C-means, Co-occurrence matrix; Similarity measure.

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Authors: Hager Kammoun, Jean Charles Lamirel, Mohamed Ben Ahmed

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In this paper, a model for an information retrieval system is proposed which takes into account that knowledge about documents and information need of users are dynamic. Two methods are combined, one qualitative or symbolic and the other quantitative or numeric, which are deemed suitable for many clustering contexts, data analysis, concept exploring and knowledge discovery. These two methods may be classified as inductive learning techniques. In this model, they are introduced to build “long term" knowledge about past queries and concepts in a collection of documents. The “long term" knowledge can guide and assist the user to formulate an initial query and can be exploited in the process of retrieving relevant information. The different kinds of knowledge are organized in different points of view. This may be considered an enrichment of the exploration level which is coherent with the concept of document/query structure.

Keywords: Information Retrieval Systems, machine learning, classification, Galois lattices, Self Organizing Map.

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Authors: Kehinde K. Agbele, Kehinde Daniel Aruleba, Eniafe F. Ayetiran

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When using Information Retrieval Systems (IRS), users often present search queries made of ad-hoc keywords. It is then up to the IRS to obtain a precise representation of the user’s information need and the context of the information. This paper investigates optimization of IRS to individual information needs in order of relevance. The study addressed development of algorithms that optimize the ranking of documents retrieved from IRS. This study discusses and describes a Document Ranking Optimization (DROPT) algorithm for information retrieval (IR) in an Internet-based or designated databases environment. Conversely, as the volume of information available online and in designated databases is growing continuously, ranking algorithms can play a major role in the context of search results. In this paper, a DROPT technique for documents retrieved from a corpus is developed with respect to document index keywords and the query vectors. This is based on calculating the weight (

Keywords: Internet ranking,

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Authors: C. Yesubai Rubavathi, R. Ravi

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This paper presents the local mesh co-occurrence patterns (LMCoP) using HSV color space for image retrieval system. HSV color space is used in this method to utilize color, intensity and brightness of images. Local mesh patterns are applied to define the local information of image and gray level co-occurrence is used to obtain the co-occurrence of LMeP pixels. Local mesh co-occurrence pattern extracts the local directional information from local mesh pattern and converts it into a well-mannered feature vector using gray level co-occurrence matrix. The proposed method is tested on three different databases called MIT VisTex, Corel, and STex. Also, this algorithm is compared with existing methods, and results in terms of precision and recall are shown in this paper.

Keywords: Content-based image retrieval system, HSV color space, gray level co-occurrence matrix, local mesh pattern.

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Authors: Maha Sliti, Walid Abdallah, Noureddine Boudriga

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In the frame of this work, we present an optical multicasting approach based on optical code-words. Our approach associates, in the edge node, an optical code-word to a group multicast address. In the core node, a set of tunable decoders are used to send a traffic data to multiple destinations based on the received code-word. The use of code-words, which correspond to the combination of an input port and a set of output ports, allows the implementation of an optical switching matrix. At the reception of a burst, it will be delayed in an optical memory. And, the received optical code-word is split to a set of tunable optical decoders. When it matches a configured code-word, the delayed burst is switched to a set of output ports.

Keywords: Optical multicast, optical burst switching networks, optical code-words, tunable decoder, virtual optical memory.

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Authors: Maha Sliti, Walid Abdallah, Noureddine Boudriga

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In the frame of this work, we present an optical multicasting approach based on optical code-words. Our approach associates, in the edge node, an optical code-word to a group multicast address. In the core node, a set of tunable decoders are used to send a traffic data to multiple destinations based on the received code-word. The use of code-words, which correspond to the combination of an input port and a set of output ports, allows the implementation of an optical switching matrix. At the reception of a burst, it will be delayed in an optical memory. And, the received optical code-word is split to a set of tunable optical decoders. When it matches a configured code-word, the delayed burst is switched to a set of output ports.

Keywords: Optical multicast, optical burst switching networks, optical code-words, tunable decoder, virtual optical memory.

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Authors: Anitha Narasimhan, Aarthy Anandan, Madhan Karky, C. N. Subalalitha

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Games can be the excellent tools for teaching a language. There are few e-learning games in Indian languages like word scrabble, cross word, quiz games etc., which were developed mainly for educational purposes. This paper proposes a Tamil word game called, “Porul”, which focuses on education as well as on players’ thinking and decision-making skills. Porul is a multiple choice based quiz game, in which the players attempt to answer questions correctly from the given multiple options that are generated using a unique algorithm called the Option Selection algorithm which explores the semantics of the question in various dimensions namely, synonym, rhyme and Universal Networking Language semantic category. This kind of semantic exploration of the question not only increases the complexity of the game but also makes it more interesting. The paper also proposes a Scoring Algorithm which allots a score based on the popularity score of the question word. The proposed game has been tested using 20,000 Tamil words.

Keywords: Porul game, Tamil word game, option selection, flash card, scoring, algorithm.

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Authors: H. Benjamin Fredrick David, R. Balasubramanian, A. Anbarasa Pandian

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Image retrieval is the most interesting technique which is being used today in our digital world. CBIR, commonly expanded as Content Based Image Retrieval is an image processing technique which identifies the relevant images and retrieves them based on the patterns that are extracted from the digital images. In this paper, two research works have been presented using CBIR. The first work provides an automated and interactive approach to the analysis of CBIR techniques. CBIR works on the principle of supervised machine learning which involves feature selection followed by training and testing phase applied on a classifier in order to perform prediction. By using feature extraction, the image transforms such as Contourlet, Ridgelet and Shearlet could be utilized to retrieve the texture features from the images. The features extracted are used to train and build a classifier using the classification algorithms such as Naïve Bayes, K-Nearest Neighbour and Multi-class Support Vector Machine. Further the testing phase involves prediction which predicts the new input image using the trained classifier and label them from one of the four classes namely 1- Normal brain, 2- Benign tumour, 3- Malignant tumour and 4- Severe tumour. The second research work includes developing a tool which is used for tumour stage identification using the best feature extraction and classifier identified from the first work. Finally, the tool will be used to predict tumour stage and provide suggestions based on the stage of tumour identified by the system. This paper presents these two approaches which is a contribution to the medical field for giving better retrieval performance and for tumour stages identification.

Keywords: Brain tumour detection, content based image retrieval, classification of tumours, image retrieval.

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Authors: Minyoung Eom, Yoonsik Choe

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In these days, multimedia data is transmitted and processed in compressed format. Due to the decoding procedure and filtering for edge detection, the feature extraction process of MPEG-7 Edge Histogram Descriptor is time-consuming as well as computationally expensive. To improve efficiency of compressed image retrieval, we propose a new edge histogram generation algorithm in DCT domain in this paper. Using the edge information provided by only two AC coefficients of DCT coefficients, we can get edge directions and strengths directly in DCT domain. The experimental results demonstrate that our system has good performance in terms of retrieval efficiency and effectiveness.

Keywords: DCT, Descriptor, EHD, MPEG7.

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Authors: C. Sheng, Y. Xin

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Retrieval image by shape similarity, given a template shape is particularly challenging, owning to the difficulty to derive a similarity measurement that closely conforms to the common perception of similarity by humans. In this paper, a new method for the representation and comparison of shapes is present which is based on the shape matrix and snake model. It is scaling, rotation, translation invariant. And it can retrieve the shape images with some missing or occluded parts. In the method, the deformation spent by the template to match the shape images and the matching degree is used to evaluate the similarity between them.

Keywords: shape representation, shape matching, shape matrix, deformation

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Authors: S. R. Nikhashemi, L. Haj Paim, Ali Khatibi

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Structural Equation Modeling (SEM) was used to test a hypothesized model explaining Malaysian hypermarket customers’ perceptions of brand trust (BT), customer perceived value (CPV) and perceived service quality (PSQ) on building their brand loyalty (CBL) and generating positive word-of-mouth communication (WOM). Self-administered questionnaires were used to collect data from 374 Malaysian hypermarket customers from Mydin, Tesco, Aeon Big and Giant in Kuala Lumpur, a metropolitan city of Malaysia. The data strongly supported the model exhibiting that BT, CPV and PSQ are prerequisite factors in building customer brand loyalty, while PSQ has the strongest effect on prediction of customer brand loyalty compared to other factors. Besides, the present study suggests the effect of the aforementioned factors via customer brand loyalty strongly contributes to generate positive word of mouth communication.

Keywords: Brand trust, perceived value, perceived service quality, brand loyalty, positive word of mouth communication.

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Authors: Abraham Varghese, Kannan Balakrishnan, Reji R. Varghese, Joseph S. Paul

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Magnetic Resonance Imaging play a vital role in the decision-diagnosis process of brain MR images. For an accurate diagnosis of brain related problems, the experts mostly compares both T1 and T2 weighted images as the information presented in these two images are complementary. In this paper, rotational and translational invariant form of Local binary Pattern (LBP) with additional gray scale information is used to retrieve similar slices of T1 weighted images from T2 weighted images or vice versa. The incorporation of additional gray scale information on LBP can extract more local texture information. The accuracy of retrieval can be improved by extracting moment features of LBP and reweighting the features based on users feedback. Here retrieval is done in a single subject scenario where similar images of a particular subject at a particular level are retrieved, and multiple subjects scenario where relevant images at a particular level across the subjects are retrieved.

Keywords: Local Binary pattern (LBP), Modified Local Binary pattern (MOD-LBP), T1 and T2 weighted images, Moment features.

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Authors: El-Sayed Atlam, Masao Fuketa, Kazuhiro Morita, Jun-ichi Aoe

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Field Association (FA) terms are a limited set of discriminating terms that give us the knowledge to identify document fields which are effective in document classification, similar file retrieval and passage retrieval. But the problem lies in the lack of an effective method to extract automatically relevant Arabic FA Terms to build a comprehensive dictionary. Moreover, all previous studies are based on FA terms in English and Japanese, and the extension of FA terms to other language such Arabic could be definitely strengthen further researches. This paper presents a new method to extract, Arabic FA Terms from domain-specific corpora using part-of-speech (POS) pattern rules and corpora comparison. Experimental evaluation is carried out for 14 different fields using 251 MB of domain-specific corpora obtained from Arabic Wikipedia dumps and Alhyah news selected average of 2,825 FA Terms (single and compound) per field. From the experimental results, recall and precision are 84% and 79% respectively. Therefore, this method selects higher number of relevant Arabic FA Terms at high precision and recall.

Keywords: Arabic Field Association Terms, information extraction, document classification, information retrieval.

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Authors: K. Oh, J. P. Hwang, E. Kim, H. Lee

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This paper presents an algorithm which extends the rapidly-exploring random tree (RRT) framework to deal with change of the task environments. This algorithm called the Retrieval RRT Strategy (RRS) combines a support vector machine (SVM) and RRT and plans the robot motion in the presence of the change of the surrounding environment. This algorithm consists of two levels. At the first level, the SVM is built and selects a proper path from the bank of RRTs for a given environment. At the second level, a real path is planned by the RRT planners for the given environment. The suggested method is applied to the control of KUKA™,, a commercial 6 DOF robot manipulator, and its feasibility and efficiency are demonstrated via the cosimulatation of MatLab™, and RecurDyn™,.

Keywords: Path planning, RRT, 6 DOF manipulator, SVM.

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Authors: Smain M. Bekhti, Nada T. Matta

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Knowledge sharing in general and the contextual access to knowledge in particular, still represent a key challenge in the knowledge management framework. Researchers on semantic web and human machine interface study techniques to enhance this access. For instance, in semantic web, the information retrieval is based on domain ontology. In human machine interface, keeping track of user's activity provides some elements of the context that can guide the access to information. We suggest an approach based on these two key guidelines, whilst avoiding some of their weaknesses. The approach permits a representation of both the context and the design rationale of a project for an efficient access to knowledge. In fact, the method consists of an information retrieval environment that, in the one hand, can infer knowledge, modeled as a semantic network, and on the other hand, is based on the context and the objectives of a specific activity (the design). The environment we defined can also be used to gather similar project elements in order to build classifications of tasks, problems, arguments, etc. produced in a company. These classifications can show the evolution of design strategies in the company.

Keywords: Project Memory, Knowledge re-use, Design rationale, Knowledge representation.

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Authors: Hai Nguyen Tien

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On the basis of the structure of alluvial sediments explained by echo sounding data and remote sensing images, the following results can be given: The estuary of Lam river from Ben Thuy Bridge (original word: Bến Thủy) to Cua Hoi (original word: Cửa Hội) is divided into three channels (location is calculated according to the river bank on the Nghe An Province, original word: Nghệ An): i) channel I (from Ben Thuy Bridge to Hung Hoa, original word: Hưng Hòa) is the branching river; ii) channel II (from Hung Hoa to Nghi Thai, original word: Nghi Thái)is a channel develops in a meandering direction with a concave side toward Ha Tinh Province (Hà Tĩnh); iii) channel III (from Nghi Thai to Cua Hoi)is a channel develops in a meandering direction with a concave side toward Nghe An province.This estuary area is formed in the period from after the sea level dropped below 0m (current water level) to the present: i) Channel II developed moving towards Ha Tinh Province; ii) Channel III developed moving towards Nghe An Province; iii) In channel I, a second river branch is formed because the flow of river cuts through the Hong Lam- Hong Nhat mudflat (original word: Hồng Lam -Hồng Nhất),at the same time creating an island.Morphological characteristics of the estuary area of Lam River are the main result of erosion and deposition activities corresponding to two water levels: the water level is about 2 m lower than the current water level and the current water level.Characteristics of the sediment layers on the riverbed in the estuary can be used to determine the sea levels in Late Holocene to the present.

Keywords: Lam River, development, Cua Hoi, river morphology

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Authors: Khan Farhan Rafat, M. Junaid Hussain

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Seamless modification of an entity for the purpose of hiding a message of significance inside its substance in a manner that the embedding remains oblivious to an observer is known as steganography. Together with today's pervasive registering frameworks, steganography has developed into a science that offers an assortment of strategies for stealth correspondence over the globe that must, however, need a critical appraisal from security breach standpoint. Microsoft Word is amongst the preferably used word processing software, which comes as a part of the Microsoft Office suite. With a user-friendly graphical interface, the richness of text editing, and formatting topographies, the documents produced through this software are also most suitable for stealth communication. This research aimed not only to epitomize the fundamental concepts of steganography but also to expound on the utilization of Microsoft Word document as a carrier for furtive message exchange. The exertion is to examine contemporary message hiding schemes from security aspect so as to present the explorative discoveries and suggest enhancements which may serve a wellspring of information to encourage such futuristic research endeavors.

Keywords: Hiding information in plain sight, stealth communication, oblivious information exchange, conceal, steganography.

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Authors: Alan C. Lin, Ricky N. Joevan

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This paper focuses on developing a system to transfer mold base plates and standard parts faster during the stage of injection mold design. This system not only provides a way to compare the file version, but also it utilizes Siemens NX 10 to isolate the updated information into a single executable file (.dll), and then, the file can be transferred without the need of transferring the whole file. By this way, the system can help the user to download only necessary mold base plates and standard parts, and those parts downloaded are only the updated portions.

Keywords: CAD, injection molding, mold base, data retrieval.

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Authors: Mahnaz Movahedi

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Slang argot plays a fundamental role in Burgess’ teenage special sociolect in his novel A Clockwork Orange, offered a wide variety of instances to be analyzed. Consequently, translation of the notions and keeping the effect would be of great importance. Burgess named his interesting RussiAnglicized^©-slang word as Nadsat, stands for –teen, mostly derived from Russian and Cockney rhyming. The paper discusses the lexical origin and Persian translation of his weird slang words illustrating a teenage-gang argot. The product depicts creativity but mistranslation that leads to the loss of slang meaning load and atmosphere in the target text.

Keywords: Argot, mistranslation, slang, sociolect.

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Authors: T. Suresh Kumar, M. Arthanari, N. Shanthi

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Nowadays, the Web has become one of the most pervasive platforms for information change and retrieval. It collects the suitable and perfectly fitting information from websites that one requires. Data mining is the form of extracting data’s available in the internet. Web mining is one of the elements of data mining Technique, which relates to various research communities such as information recovery, folder managing system and simulated intellects. In this Paper we have discussed the concepts of Web mining. We contain generally focused on one of the categories of Web mining, specifically the Web Content Mining and its various farm duties. The mining tools are imperative to scanning the many images, text, and HTML documents and then, the result is used by the various search engines. We conclude by presenting a comparative table of these tools based on some pertinent criteria.

Keywords: Data Mining, Web Mining, Web Content Mining, Mining Tools, Information retrieval.

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Authors: Hanh Huu Hoang, Tho Manh Nguyen

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Ever increasing capacities of contemporary storage devices inspire the vision to accumulate (personal) information without the need of deleting old data over a long time-span. Hence the target of SemanticLIFE project is to create a Personal Information Management system for a human lifetime data. One of the most important characteristics of the system is its dedication to retrieve information in a very efficient way. By adopting user demands regarding the reduction of ambiguities, our approach aims at a user-oriented and yet powerful enough system with a satisfactory query performance. We introduce the query system of SemanticLIFE, the Virtual Query System, which uses emerging Semantic Web technologies to fulfill users- requirements.

Keywords: Ontology-based Information Retrieval, Digital Memories, SemanticLIFE.

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Authors: Pardeep Singh, Sanjay Sharma

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Content-Based Image Retrieval (CBIR) has been one on the most vivid research areas in the field of computer vision over the last 10 years. Many programs and tools have been developed to formulate and execute queries based on the visual or audio content and to help browsing large multimedia repositories. Still, no general breakthrough has been achieved with respect to large varied databases with documents of difering sorts and with varying characteristics. Answers to many questions with respect to speed, semantic descriptors or objective image interpretations are still unanswered. In the medical field, images, and especially digital images, are produced in ever increasing quantities and used for diagnostics and therapy. In several articles, content based access to medical images for supporting clinical decision making has been proposed that would ease the management of clinical data and scenarios for the integration of content-based access methods into Picture Archiving and Communication Systems (PACS) have been created. This paper gives an overview of soft computing techniques. New research directions are being defined that can prove to be useful. Still, there are very few systems that seem to be used in clinical practice. It needs to be stated as well that the goal is not, in general, to replace text based retrieval methods as they exist at the moment.

Keywords: CBIR, GA, Rough sets, CBMIR

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Authors: Tomyslav Sledevič, Artūras Serackis, Gintautas Tamulevičius, Dalius Navakauskas

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Paper presents an comparative evaluation of features extraction algorithm for a real-time isolated word recognition system based on FPGA. The Mel-frequency cepstral, linear frequency cepstral, linear predictive and their cepstral coefficients were implemented in hardware/software design. The proposed system was investigated in speaker dependent mode for 100 different Lithuanian words. The robustness of features extraction algorithms was tested recognizing the speech records at different signal to noise rates. The experiments on clean records show highest accuracy for Mel-frequency cepstral and linear frequency cepstral coefficients. For records with 15 dB signal to noise rate the linear predictive cepstral coefficients gives best result. The hard and soft part of the system is clocked on 50 MHz and 100 MHz accordingly. For the classification purpose the pipelined dynamic time warping core was implemented. The proposed word recognition system satisfy the real-time requirements and is suitable for applications in embedded systems.

Keywords: Isolated word recognition, features extraction, MFCC, LFCC, LPCC, LPC, FPGA, DTW.

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Authors: Meaghan Bowman

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Microblogging has become increasingly popular for commenting on current events, spreading gossip, and encouraging individualism--which favors its low-context communication channel. These social media (SM) platforms allow users to express opinions while interacting with a wide range of populations. Hashtags allow immediate identification of like-minded individuals worldwide on a vast array of topics. The output of the analytic tool, Linguistic Inquiry and Word Count (LIWC)--a program that associates psychological meaning with the frequency of use of specific words--may suggest the nature of individuals’ internal states and general sentiments. When applied to groupings of SM posts unified by a hashtag, such information can be helpful to community leaders during periods in which the forming of public opinion happens in parallel with the unfolding of political, economic, or social events. This is especially true when outcomes stand to impact the well-being of the group. Here, we applied the online tools, Google Translate and the University of Texas’s LIWC, to a 90-posting sample from a corpus of Colombian Spanish microblogs. On translated disjoint sets, identified by hashtag as being authored by advocates of voting “No,” advocates voting “Yes,” and entities refraining from hashtag use, we observed the value of LIWC’s Tone feature as distinguishing among the categories and the word “peace,” as carrying particular significance, due to its frequency of use in the data.

Keywords: Colombia peace referendum, FARC, hashtags, linguistics, microblogging, social media.

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Authors: Anindya Roy, Goutam Saha

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Rapid progress in audio compression technology has contributed to the explosive growth of music available in digital form today. In a reversal of ideas, this work makes use of a recently proposed efficient audio compression scheme to develop three important applications in the context of Music Information Retrieval (MIR) for the effective manipulation of large music databases, namely automatic music recommendation (AMR), digital rights management (DRM) and audio finger-printing for song identification. The performance of these three applications has been evaluated with respect to a database of songs collected from a diverse set of genres.

Keywords: Audio compression, Music Information Retrieval, Digital Rights Management, Audio Fingerprinting.

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Authors: Pardeep Singh, Sanjay Sharma

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With increasing data in medical databases, medical data retrieval is growing in popularity. Some of this analysis including inducing propositional rules from databases using many soft techniques, and then using these rules in an expert system. Diagnostic rules and information on features are extracted from clinical databases on diseases of congenital anomaly. This paper explain the latest soft computing techniques and some of the adaptive techniques encompasses an extensive group of methods that have been applied in the medical domain and that are used for the discovery of data dependencies, importance of features, patterns in sample data, and feature space dimensionality reduction. These approaches pave the way for new and interesting avenues of research in medical imaging and represent an important challenge for researchers.

Keywords: CBIR, GA, Rough sets, CBMIR, SVM.

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