Search results for: document structures

Authors: Abhijit Mitra

Abstract:

An effective approach for extracting document images from a noisy background is introduced. The entire scheme is divided into three sub- stechniques – the initial preprocessing operations for noise cluster tightening, introduction of a new thresholding method by maximizing the ratio of stan- dard deviations of the combined effect on the image to the sum of weighted classes and finally the image restoration phase by image binarization utiliz- ing the proposed optimum threshold level. The proposed method is found to be efficient compared to the existing schemes in terms of computational complexity as well as speed with better noise rejection.

Keywords: Document image extraction, Preprocessing, Ratio of stan-dard deviations, Bi-level adaptive thresholding.

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Authors: Boontee Kruatrachue, Narongchai Moongfangklang, Kritawan Siriboon

Abstract:

This paper describes fast and efficient method for page segmentation of document containing nonrectangular block. The segmentation is based on edge following algorithm using small window of 16 by 32 pixels. This segmentation is very fast since only border pixels of paragraph are used without scanning the whole page. Still, the segmentation may contain error if the space between them is smaller than the window used in edge following. Consequently, this paper reduce this error by first identify the missed segmentation point using direction information in edge following then, using X-Y cut at the missed segmentation point to separate the connected columns. The advantage of the proposed method is the fast identification of missed segmentation point. This methodology is faster with fewer overheads than other algorithms that need to access much more pixel of a document.

Keywords: Contour Direction Technique, Missed SegmentationPoints, Page Segmentation, Recursive X-Y Cut Technique

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Authors: Yi Yu, Gaoxi Xiao

Abstract:

Community structures widely exist in almost all real-life networks. Extensive researches have been carried out on detecting community structures in complex networks. However, many aspects of how community structures may affect the dynamics and properties of complex networks still remain unclear. In this work, we examine the impacts of community structures on the epidemic spreading and detection in complex networks. Extensive simulation results show that community structures may not help decrease the infection size at steady state, yet they could indeed help slow down the infection spreading. Also, networks with strong community structures may expect to have a smaller average infection size when equipped with a number of sparsely deployed monitors.

Keywords: Complex network, epidemic spreading, infection size, infection monitoring.

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Authors: Takahiro Nishigaki, Takashi Onoda

Abstract:

In recent years, the number of document data has been increasing since the spread of the Internet. Many methods have been studied for extracting topics from large document data. We proposed Independent Topic Analysis (ITA) to extract topics independent of each other from large document data such as newspaper data. ITA is a method for extracting the independent topics from the document data by using the Independent Component Analysis. The topic represented by ITA is represented by a set of words. However, the set of words is quite different from the topics the user imagines. For example, the top five words with high independence of a topic are as follows. Topic1 = {"scor", "game", "lead", "quarter", "rebound"}. This Topic 1 is considered to represent the topic of "SPORTS". This topic name "SPORTS" has to be attached by the user. ITA cannot name topics. Therefore, in this research, we propose a method to obtain topics easy for people to understand by using the web search engine, topics given by the set of words given by independent topic analysis. In particular, we search a set of topical words, and the title of the homepage of the search result is taken as the topic name. And we also use the proposed method for some data and verify its effectiveness.

Keywords: Independent topic analysis, topic extraction, topic naming, web search engine.

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Authors: Mussarat Abdullah, Fazal Wahab

Abstract:

Data hiding into text documents itself involves pretty complexities due to the nature of text documents. A robust text watermarking scheme targeting an object based environment is presented in this research. The heart of the proposed solution describes the concept of watermarking an object based text document where each and every text string is entertained as a separate object having its own set of properties. Taking advantage of the z-ordering of objects watermark is applied with the z-axis letting zero fidelity disturbances to the text. Watermark sequence of bits generated against user key is hashed with selected properties of given document, to determine the bit sequence to embed. Bits are embedded along z-axis and the document has no fidelity issues when printed, scanned or photocopied.

Keywords: Digital Watermarking, Object Based Environment, Watermark, z-ordering.

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Authors: Azlin M. Azmi, T. Zhou, A. Rinoshika, L. Cheng

Abstract:

The turbulent structures in the wake (x/d =10 to 60) of a screen cylinder have been educed to understand the roles of the various structures as evolving downstream by comparing with those obtained in a solid circular cylinder wake at Reynolds number, Re of 7000. Using a wavelet multiresolution technique, the flow structures are decomposed into a number of wavelet components based on their central frequencies. It is observed that in the solid cylinder wake, large-scale structures (of frequencyf₀ and 1.2 f₀) make the largest contribution to the Reynolds stresses although they start to lose their roles significantly at x/d> 20. In the screen cylinder wake, the intermediate-scale structures (2f₀ and 4f₀) contribute the most to the Reynolds stresses atx/d =10 before being taken over by the large-scale structures (f₀) further downstream.

Keywords: Turbulent structure, screen cylinder, vortex, wavelet multiresolution analysis.

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Authors: Manish Kumar

Abstract:

Reinforced cement concrete is getting extensively used for construction of different type of structures for the last one century. During this period, we have constructed many structures like buildings, bridges, industrial structures, pavement, water tanks etc. using this construction material. These structures have been created with huge investment of resources. It is essential to maintain those structures in functional condition. Since deterioration in RCC Structures is a common and natural phenomenon it is required to have a detailed plan, methodology for structural repair and rehabilitation shall be in place for dealing such issues. It is important to know exact reason of distress, type of distress and correct method of repair concrete structures. The different methods of repair are described in paper according to distress category which can be refereed for repair. Major finding of the study is that to protect our structure we need to have maintenance frequency and correct material to be chosen for repair. Also workmanship during repair needs to be taken utmost care for quality repair.

Keywords: Deterioration, functional condition, reinforced cement concrete, resources.

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Authors: Ali Hemmati, Ali Kheyroddin

Abstract:

Semnan is a city in semnan province, northern Iran with a population estimated at 119,778 inhabitants. It is the provincial capital of semnan province. Iran is a developing country and construction is a basic factor of developing too. Hence, Semnan city needs to a special programming for construction of buildings, structures and infrastructures. Semnan municipality tries to begin this program. In addition to, city has some historical monuments which can be interesting for tourists. Hence, Semnan inhabitants can benefit from tourist industry. Optimization of Energy in construction industry is another activity of this municipality and the inhabitants who execute these regulations receive some discounts. Many parts of Iran such as semnan are located in highly seismic zones and structures must be constructed safe e.g., according to recent seismic codes. In this paper opportunities of IT in construction industry of Iran are investigated in three categories. Pre-construction phase, construction phase and earthquake disaster mitigation are studied. Studies show that information technology can be used in these items for reducing the losses and increasing the benefits. Both government and private sectors must contribute to this strategic project for obtaining the best result.

Keywords: approval, building, construction, document, industry, IT, Semnan

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Authors: Panchalee Sukjit, Herwig Unger

Abstract:

IT infrastructures are becoming more and more difficult. Therefore, in the first industrial IT systems, the P2P paradigm has replaced the traditional client server and methods of self-organization are gaining more and more importance. From the past it is known that especially regular structures like grids may significantly improve the system behavior and performance. This contribution introduces a new algorithm based on a biologic analogue, which may provide the growth of several regular structures on top of anarchic grown P2P- or social network structures.

Keywords: P2P, Pattern generation, Grid, Social network, Inheritance, Reproduction

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Authors: Sameh H. Ghwanmeh

Abstract:

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: Chothmal, Basant Agarwal

Abstract:

Sentiment analysis means to classify a given review document into positive or negative polar document. Sentiment analysis research has been increased tremendously in recent times due to its large number of applications in the industry and academia. Sentiment analysis models can be used to determine the opinion of the user towards any entity or product. E-commerce companies can use sentiment analysis model to improve their products on the basis of users’ opinion. In this paper, we propose a new One-class Support Vector Machine (One-class SVM) based sentiment analysis model for movie review documents. In the proposed approach, we initially extract features from one class of documents, and further test the given documents with the one-class SVM model if a given new test document lies in the model or it is an outlier. Experimental results show the effectiveness of the proposed sentiment analysis model.

Keywords: Feature selection methods, Machine learning, NB, One-class SVM, Sentiment Analysis, Support Vector Machine.

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Authors: Masahiro Ohmura, Koh Kakusho, Takeshi Okadome

Abstract:

This paper presents a regression model with autocorrelated errors in which the inputs are social moods obtained by analyzing the adjectives in Twitter posts using a document topic model, where document topics are extracted using LDA. The regression model predicts Dow Jones Industrial Average (DJIA) more precisely than autoregressive moving-average models.

Keywords: Regression model, social mood, stock market prediction, Twitter.

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Authors: Hassan Haghighi, Seyedeh Zahra Hosseini, Seyedeh Elahe Jalambadani

Abstract:

One of the most important aspects expected from an ERP system is to mange user\administrator manual documents dynamically. Since an ERP package is frequently changed during its implementation in customer sites, it is often needed to add new documents and/or apply required changes to existing documents in order to cover new or changed capabilities. The worse is that since these changes occur continuously, the corresponding documents should be updated dynamically; otherwise, implementing the ERP package in the organization encounters serious risks. In this paper, we propose a new architecture which is based on the agent oriented vision and supplies the dynamic document generation expected from ERP systems using several independent but cooperative agents. Beside the dynamic document generation which is the main issue of this paper, the presented architecture will address some aspects of intelligence and learning capabilities existing in ERP.

Keywords: enterprise resource planning, dynamic documentgeneration, software architecture, agent oriented architecture, learning, intelligence

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Authors: Lu Zhang, Chunping Li, Jun Liu, Hui Wang

Abstract:

Text similarity measurement is a fundamental issue in many textual applications such as document clustering, classification, summarization and question answering. However, prevailing approaches based on Vector Space Model (VSM) more or less suffer from the limitation of Bag of Words (BOW), which ignores the semantic relationship among words. Enriching document representation with background knowledge from Wikipedia is proven to be an effective way to solve this problem, but most existing methods still cannot avoid similar flaws of BOW in a new vector space. In this paper, we propose a novel text similarity measurement which goes beyond VSM and can find semantic affinity between documents. Specifically, it is a unified graph model that exploits Wikipedia as background knowledge and synthesizes both document representation and similarity computation. The experimental results on two different datasets show that our approach significantly improves VSM-based methods in both text clustering and classification.

Keywords: Text classification, Text clustering, Text similarity, Wikipedia

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Authors: Matthias Dehmer, Frank Emmert Streib, Alexander Mehler, Jürgen Kilian

Abstract:

Most known methods for measuring the structural similarity of document structures are based on, e.g., tag measures, path metrics and tree measures in terms of their DOM-Trees. Other methods measures the similarity in the framework of the well known vector space model. In contrast to these we present a new approach to measuring the structural similarity of web-based documents represented by so called generalized trees which are more general than DOM-Trees which represent only directed rooted trees.We will design a new similarity measure for graphs representing web-based hypertext structures. Our similarity measure is mainly based on a novel representation of a graph as strings of linear integers, whose components represent structural properties of the graph. The similarity of two graphs is then defined as the optimal alignment of the underlying property strings. In this paper we apply the well known technique of sequence alignments to solve a novel and challenging problem: Measuring the structural similarity of generalized trees. More precisely, we first transform our graphs considered as high dimensional objects in linear structures. Then we derive similarity values from the alignments of the property strings in order to measure the structural similarity of generalized trees. Hence, we transform a graph similarity problem to a string similarity problem. We demonstrate that our similarity measure captures important structural information by applying it to two different test sets consisting of graphs representing web-based documents.

Keywords: Graph similarity, hierarchical and directed graphs, hypertext, generalized trees, web structure mining.

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Authors: Mohamed Ben Aouicha, Mohamed Tmar, Mohand Boughanem, Mohamed Abid

Abstract:

This paper presents an information retrieval model on XML documents based on tree matching. Queries and documents are represented by extended trees. An extended tree is built starting from the original tree, with additional weighted virtual links between each node and its indirect descendants allowing to directly reach each descendant. Therefore only one level separates between each node and its indirect descendants. This allows to compare the user query and the document with flexibility and with respect to the structural constraints of the query. The content of each node is very important to decide weither a document element is relevant or not, thus the content should be taken into account in the retrieval process. We separate between the structure-based and the content-based retrieval processes. The content-based score of each node is commonly based on the well-known Tf × Idf criteria. In this paper, we compare between this criteria and another one we call Tf × Ief. The comparison is based on some experiments into a dataset provided by INEX1 to show the effectiveness of our approach on one hand and those of both weighting functions on the other.

Keywords: XML retrieval, INEX, Tf × Idf, Tf × Ief

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Authors: Nandini N., Srikanta Murthy K., G. Hemantha Kumar

Abstract:

This paper includes two novel techniques for skew estimation of binary document images. These algorithms are based on connected component analysis and Hough transform. Both these methods focus on reducing the amount of input data provided to Hough transform. In the first method, referred as word centroid approach, the centroids of selected words are used for skew detection. In the second method, referred as dilate & thin approach, the selected characters are blocked and dilated to get word blocks and later thinning is applied. The final image fed to Hough transform has the thinned coordinates of word blocks in the image. The methods have been successful in reducing the computational complexity of Hough transform based skew estimation algorithms. Promising experimental results are also provided to prove the effectiveness of the proposed methods.

Keywords: Dilation, Document processing, Hough transform, Optical Character Recognition, Skew estimation, and Thinning.

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Authors: Alae El Alami, Mohamed Bahaj

Abstract:

This article discusses the passage of RDB to XML documents (schema and data) based on metadata and semantic enrichment, which makes the RDB under flattened shape and is enriched by the object concept. The integration and exploitation of the object concept in the XML uses a syntax allowing for the verification of the conformity of the document XML during the creation. The information extracted from the RDB is therefore analyzed and filtered in order to adjust according to the structure of the XML files and the associated object model. Those implemented in the XML document through a SQL query are built dynamically. A prototype was implemented to realize automatic migration, and so proves the effectiveness of this particular approach.

Keywords: RDB, XML, DTD, semantic enrichment.

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Authors: Y. Djouadi., F. Souam.

Abstract:

Most of the existing text mining approaches are proposed, keeping in mind, transaction databases model. Thus, the mined dataset is structured using just one concept: the “transaction", whereas the whole dataset is modeled using the “set" abstract type. In such cases, the structure of the whole dataset and the relationships among the transactions themselves are not modeled and consequently, not considered in the mining process. We believe that taking into account structure properties of hierarchically structured information (e.g. textual document, etc ...) in the mining process, can leads to best results. For this purpose, an hierarchical associations rule mining approach for textual documents is proposed in this paper and the classical set-oriented mining approach is reconsidered profits to a Direct Acyclic Graph (DAG) oriented approach. Natural languages processing techniques are used in order to obtain the DAG structure. Based on this graph model, an hierarchical bottom up algorithm is proposed. The main idea is that each node is mined with its parent node.

Keywords: Graph based association rules mining, Hierarchical document structure, Text mining.

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Authors: Esti Rahmawati Agustina, Is Esti Firmanesa

Abstract:

Blind Signature were introduced by Chaum. In this scheme, a signer can “sign” a document without knowing the document contain. This is particularly important in electronic voting. CryptO-0N2 is an electronic voting protocol which is development of CryptO-0N. During its development this protocol has not been furnished with the requirement of blind signature, so the choice of voters can be determined by counting center. In this paper will be presented of implementation of blind signature using RSA algorithm.

Keywords: Blind signature, electronic voting protocol, RSA algorithm.

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Authors: Ehrenstorfer Barbara, Peherstorfer Tanja, Nový Jan

Abstract:

Urbanization and regionalization are two different approaches when it comes to economical structures and development, infrastructure and mobility, quality of life and living, education, social cohesion and many other topics. At first glance, the structures associated with urbanization and regionalization seems to be contradicting. This paper discusses possibilities of transfer and cooperation between rural and urban structures. An empirical investigation contributed to reveal scenarios of supposable forms of exchange and cooperation of remote rural areas and big cities.

Keywords: Learning Regions, Quality of Life and Living, Regional and Rural Development, Social Innovation.

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Authors: Shih-Yi Chao

Abstract:

The similarity comparison of RNA secondary structures is important in studying the functions of RNAs. In recent years, most existing tools represent the secondary structures by tree-based presentation and calculate the similarity by tree alignment distance. Different to previous approaches, we propose a new method based on maximum clique detection algorithm to extract the maximum common structural elements in compared RNA secondary structures. A new graph-based similarity measurement and maximum common subgraph detection procedures for comparing purely RNA secondary structures is introduced. Given two RNA secondary structures, the proposed algorithm consists of a process to determine the score of the structural similarity, followed by comparing vertices labelling, the labelled edges and the exact degree of each vertex. The proposed algorithm also consists of a process to extract the common structural elements between compared secondary structures based on a proposed maximum clique detection of the problem. This graph-based model also can work with NC-IUB code to perform the pattern-based searching. Therefore, it can be used to identify functional RNA motifs from database or to extract common substructures between complex RNA secondary structures. We have proved the performance of this proposed algorithm by experimental results. It provides a new idea of comparing RNA secondary structures. This tool is helpful to those who are interested in structural bioinformatics.

Keywords: Clique detection, labeled vertices, RNA secondary structures, subgraph, similarity.

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Authors: Hmway Hmway Tar, Thi Thi Soe Nyaunt

Abstract:

Documents clustering become an essential technology with the popularity of the Internet. That also means that fast and high-quality document clustering technique play core topics. Text clustering or shortly clustering is about discovering semantically related groups in an unstructured collection of documents. Clustering has been very popular for a long time because it provides unique ways of digesting and generalizing large amounts of information. One of the issues of clustering is to extract proper feature (concept) of a problem domain. The existing clustering technology mainly focuses on term weight calculation. To achieve more accurate document clustering, more informative features including concept weight are important. Feature Selection is important for clustering process because some of the irrelevant or redundant feature may misguide the clustering results. To counteract this issue, the proposed system presents the concept weight for text clustering system developed based on a k-means algorithm in accordance with the principles of ontology so that the important of words of a cluster can be identified by the weight values. To a certain extent, it has resolved the semantic problem in specific areas.

Keywords: Clustering, Concept Weight, Document clustering, Feature Selection, Ontology

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

Abstract:

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: Manole Velicanu, Emanuil Rednic

Abstract:

The paper shows the necessity to increase the security level for paper management in the cadastral field by using specific graphical watermarks. Using the graphical watermarking will increase the security in the cadastral content management; furthermore any altered document will be validated afterwards of its originality by checking the graphic watermark. If, by any reasons the document is changed for counterfeiting, it is invalidated and found that is an illegal copy due to the graphic check of the watermarking, check made at pixel level

Keywords: cadastral system, database security, security standards, content management, identity management, watermarking.

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Authors: Amin Milani Fard, Mohsen Kahani, Reza Ghaemi, Hamid Tabatabaee

Abstract:

In this paper we propose a multi-agent architecture for web information retrieval using fuzzy logic based result fusion mechanism. The model is designed in JADE framework and takes advantage of JXTA agent communication method to allow agent communication through firewalls and network address translators. This approach enables developers to build and deploy P2P applications through a unified medium to manage agent-based document retrieval from multiple sources.

Keywords: Information retrieval systems, list fusion methods, document score, multi-agent systems.

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Authors: Leo Galambos

Abstract:

The majority of today's IR systems base the IR task on two main processes: indexing and searching. There exists a special group of dynamic IR systems where both processes (indexing and searching) happen simultaneously; such a system discards obsolete information, simultaneously dealing with the insertion of new in¬formation, while still answering user queries. In these dynamic, time critical text document databases, it is often important to modify index structures quickly, as documents arrive. This paper presents a method for dynamization which may be used for this task. Experimental results show that the dynamization process is possible and that it guarantees the response time for the query operation and index actualization.

Keywords: Search engine, inverted file, index management.

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Authors: Mosseri Avraham

Abstract:

Teaching structures and structural design in architectural studies is considered a difficult mission due to complex reasons and circumstances. This article proposes a new conceptual model (HDH) for teaching structures and structural design in architectural studies. Because of its systems-thinking orientation it is also relevant and applicable to other fields and systems. The HDH model was developed in order to encourage the integration of science and art, especially in relation to structures, in architectural studies.

Keywords: Structural Thinking, Conceptual Design, Teaching Structures, Systems Thinking.

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Authors: Roelien Goede

Abstract:

Data Structures and Algorithms is a module in most Computer Science or Information Technology curricula. It is one of the modules most students identify as being difficult. This paper demonstrates how programming a solution for Sudoku can make abstract concepts more concrete. The paper relates concepts of a typical Data Structures and Algorithms module to a step by step solution for Sudoku in a human type as opposed to a computer oriented solution.

Keywords: Data Structures, Algorithms, Sudoku, ObjectOriented Programming, Programming Teaching, Education.

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Authors: Muhammad Tariq A. Chaudhary

Abstract:

The tremendous loss of life that resulted in the aftermath of recent earthquakes in developing countries is mostly due to the collapse of non-engineered and semi-engineered building structures. Such structures are used as houses, schools, primary healthcare centers and government offices. These building are classified structurally into two categories viz. non-engineered and semi-engineered. Non-engineered structures include: adobe, unreinforced masonry (URM) and wood buildings. Semi-engineered buildings are mostly low-rise (up to 3 story) light concrete frame structures or masonry bearing walls with reinforced concrete slab. This paper presents an overview of the typical damage observed in non-engineered structures and their most likely causes in the past earthquakes with specific emphasis on the performance of such structures in the 2005 Kashmir earthquake. It is demonstrated that seismic performance of these structures can be improved from life-safety viewpoint by adopting simple low-cost modifications to the existing construction practices. Incorporation of some of these practices in the reconstruction efforts after the 2005 Kashmir earthquake are examined in the last section for mitigating seismic risk hazard.

Keywords: Kashmir earthquake, non-engineered buildings, seismic hazard, structural details, structural strengthening.

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