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Following the implementation of 2018’s laws on the rights of persons with disabilities (PWDs) in Egypt, students with disabilities (SWDs) have both legal and moral rights to meaningful learning opportunities and inclusive education. Despite that, SWDs still have very limited education resources which limit their career aspirations and quality of life. In this respect, education whether as part of formal education or lifelong learning is central to the museum’s mission. Museums, as part of non-formal education, are being acknowledged for their educative powers and investments in the development of quality formal, non-formal, and informal learning experiences. Further, phrases such as “inclusivity,” “accessibility,” and “diversity” were notably included in the newly approved museum definition by ICOM (2022) emphasizing museums’ obligations to embrace societal issues and shape a cultural attitude concerning disability rights, diversity, and equality together with overcoming exclusionary educational practices. The study seeks to investigate the existing resources and inclusive practices in Egyptian museums to achieve non-formal education for SWDs. Qualitative research approaches have been employed to answer a specific question: How can Egyptian museums work within their governing systems to support the learning of SWDs beyond their formal education system? The study aims to assess the potential of Egyptian museums in facilitating learning for SWDs. Further, it examines the capability of Egyptian museums in contributing to informal and non-formal learning for SWDs and striving for inclusive education inspired by the social model of disability that fosters inclusive educational programs and adopts a human rights-based approach. The results revealed that Egyptian museums contributed to the learning of SWDs, yet small-scale programs and individual efforts, but they are already engaged in active inclusive practices that address the learning of SWDs. The study suggests that they need to be acknowledged and supported by the government as state instruments and direct actors in advancing inclusive education and implementing appropriate pedagogies in favor of SWDs.
Observing the Digital Self
(2021)
Facebook, Instagram, Twitter & Co. Social media have become an essential part of everyday life for many people in recent years, and as such, it is impossible to imagine a life without them. It seems self-evident to operate as an active prosumer in the net via various end devices. We create personal profiles in various social networks, exchange ideas, and connect with others. We take part in virtual events, and above all: we actively shape the web.
The photo and video platform Instagram is one of the most popular social networking sites. Since 2010, the online service has offered its users the opportunity for personal development and space for creativity. Therefore, the personal profiles serve not only participatory reasons but also facilitate acts of self-representation.
In addition to apparently visible aspects, questions about self-perception arise: How do users experience and evaluate their activities in virtual space? How do they perceive their actions between the offline and online world, and how intertwined are these spheres? Through an ethnographical approach, this work represents the attempt to look beyond the self-evident aspects of the digital self. For this purpose, two Instagram users were accompanied for more than a year.
Texts, Animals, Environments. Zoopoetics and Ecopoetics probes the multiple links between ecocriticism and animal studies, assessing the relations between animals, environments and poetics. While ecocriticism usually relies on a relational approach to explore phenomena related to the environment or ecology more broadly, animal studies tends to examine individual or species-specific aspects. As a consequence, ecocriticism concentrates on ecopoetical, animal studies on zoopoetical elements and modes of representation in literature (and the arts more generally). Bringing key concepts of ecocriticism and animal studies into dialogue, the volume explores new ways of thinking about and reading texts, animals, and environments – not as separate entities but as part of the same collective.
Language and literary studies have studied style for centuries, and even since the advent of ›stylistics‹ as a discipline at the beginning of the twentieth century, definitions of ›style‹ have varied heavily across time, space and fields. Today, with increasingly large collections of literary texts being made available in digital form, computational approaches to literary style are proliferating. New methods from disciplines such as corpus linguistics and computer science are being adopted and adapted in interrelated fields such as computational stylistics and corpus stylistics, and are facilitating new approaches to literary style.
The relation between definitions of style in established linguistic or literary stylistics, and definitions of style in computational or corpus stylistics has not, however, been systematically assessed. This contribution aims to respond to the need to redefine style in the light of this new situation and to establish a clearer perception of both the overlap and the boundaries between ›mainstream‹ and ›computational‹ and/or ›empirical‹ literary stylistics. While stylistic studies of non-literary texts are currently flourishing, our contribution deliberately centers on those approaches relevant to ›literary stylistics‹. It concludes by proposing an operational definition of style that we hope can act as a common ground for diverse approaches to literary style, fostering transdisciplinary research.
The focus of this contribution is on literary style in linguistics and literary studies (rather than in art history, musicology or fashion), on textual aspects of style (rather than production- or reception-oriented theories of style), and on a descriptive perspective (rather than a prescriptive or didactic one). Even within these limits, however, it appears necessary to build on a broad understanding of the various perspectives on style that have been adopted at different times and in different traditions. For this reason, the contribution first traces the development of the notion of style in three different traditions, those of German, Dutch and French language and literary studies. Despite the numerous links between each other, and between each of them to the British and American traditions, these three traditions each have their proper dynamics, especially with regard to the convergence and/or confrontation between mainstream and computational stylistics. For reasons of space and coherence, the contribution is limited to theoretical developments occurring since 1945.
The contribution begins by briefly outlining the range of definitions of style that can be encountered across traditions today: style as revealing a higher-order aesthetic value, as the holistic ›gestalt‹ of single texts, as an expression of the individuality of an author, as an artifact presupposing choice among alternatives, as a deviation from a norm or reference, or as any formal property of a text. The contribution then traces the development of definitions of style in each of the three traditions mentioned, with the aim of giving a concise account of how, in each tradition, definitions of style have evolved over time, with special regard to the way such definitions relate to empirical, quantitative or otherwise computational approaches to style in literary texts. It will become apparent how, in each of the three traditions, foundational texts continue to influence current discussions on literary style, but also how stylistics has continuously reacted to broader developments in cultural and literary theory, and how empirical, quantitative or computational approaches have long existed, usually in parallel to or at the margins of mainstream stylistics. The review will also reflect the lines of discussion around style as a property of literary texts – or of any textual entity in general.
The perspective on three stylistic traditions is accompanied by a more systematic perspective. The rationale is to work towards a common ground for literary scholars and linguists when talking about (literary) style, across traditions of stylistics, with respect for established definitions of style, but also in light of the digital paradigm. Here, we first show to what extent, at similar or different moments in time, the three traditions have developed comparable positions on style, and which definitions out of the range of possible definitions have been proposed or promoted by which authors in each of the three traditions.
On the basis of this synthesis, we then conclude by proposing an operational definition of style that is an attempt to provide a common ground for both mainstream and computational literary stylistics. This definition is discussed in some detail in order to explain not only what is meant by each term in the definition, but also how it relates to computational analyses of style – and how this definition aims to avoid some of the pitfalls that can be perceived in earlier definitions of style. Our definition, we hope, will be put to use by a new generation of computational, quantitative, and empirical studies of style in literary texts.
Based on the results of a 3-day workshop at the Brown University (2012) this white paper tries to sum up important topics and problems which came up in the presentations and discussions and to outline some general aspects of data modeling in digital humanities. Starting with an attempt to define data modeling it introduces distinctions like curation-driven vs. research-driven for a more general description of data modeling. The second part discusses specific problems and challenges of data modeling in the Humanities, while the third part outlines practical aspects, like the creation of data models or their evaluation.
In Yaşar Kemal‘s The Pomegranate on the Knoll, the environment of the Çukurova peasants is depicted meticulously in their daily struggle for survival; however, Kemal transcends purely realist representations whenever the characters try either to make sense of or to gain control over their hostile environment. By using magical realist strategies in his text as well, he gives a voice to the suffering of the Çukurova peasants and engages in a form of political writing different from social realism or village literature. He helps to raise public awareness for the traumatic consequences of the changing social reality in rural Turkey not only by describing it, but also by using magical realist writing strategies which let readers feel it for themselves.
In this research, an attempt to create a knowledge-based learning system for the Quranic text has been performed. The knowledge base is made up of the Quranic text along with detailed information about each chapter and verse, and some rules. The system offers the possibility to study the Quran through web-based interfaces, implementing novel visualization techniques for browsing, querying, consulting, and testing the acquired knowledge. Additionally the system possesses knowledge acquisition facilities for maintaining the knowledge base.
Given a collection of diverging documents about some lost original text, any person interested in the text would try reconstructing it from the diverging documents. Whether it is eclecticism, stemmatics, or copy-text, one is expected to explicitly or indirectly select one of the documents as a starting point or as a base text, which could be emended through comparison with remaining documents, so that a text that could be designated as the original document is generated. Unfortunately the process of giving priority to one of the documents also known as witnesses is a subjective approach. In fact even Cladistics, which could be considered as a computer-based approach of implementing stemmatics, does not present or recommend users to select a certain witness as a starting point for the process of reconstructing the original document. In this study, a computational method using a rule-based Bayesian classifier is used, to assist text scholars in their attempts of reconstructing a non-existing document from some available witnesses. The method developed in this study consists of selecting a base text successively and collating it with remaining documents. Each completed collation cycle stores the selected base text and its closest witness, along with a weighted score of their similarities and differences. At the end of the collation process, a witness selected more often by majority of base texts is considered as the probable base text of the collection. Witnesses’ scores are weighted using a weighting system, based on effects of types of textual modifications on the process of reconstructing original documents. Users have the possibility to select between baseless and base text collation. If a base text is selected, the task is reduced to ranking the witnesses with respect to the base text, otherwise a base text as well as ranking of the witnesses with respect to the base text are computed and displayed on a histogram.
Learning a book in general involves reading it, underlining important words, adding comments, summarizing some passages, and marking up some text or concepts. Once deeper understanding is achieved, one would like to organize and manage her/his knowledge in such a way that, it could be easily remembered and efficiently transmitted to others. In this paper, books organized in terms of chapters consisting of verses, are considered as the source of knowledge to be modeled. The knowledge model consists of verses with their metadata and semantic annotations. The metadata represent the multiple perspectives of knowledge modeling. Verses with their metadata and annotations form a meta-model, which will be published on a web Mashup. The meta-model with linking between its elements constitute a knowledge base. An XML-based annotation system breaking down the learning process into specific tasks, helps constructing the desired meta-model. The system is made up of user interfaces for creating metadata, annotating chapters’ contents according to user selected semantics, and templates for publishing the generated knowledge on the Internet. The proposed software system improves comprehension and retention of knowledge contained in religious texts through modeling and visualization. The system has been applied to the Quran, and the result obtained shows that multiple perspectives of information modeling can be successfully applied to religious texts. It is expected that this short ongoing study would motivate others to engage in devising and offering software systems for cross-religions learning.
Design and Implementation of Architectures for Interactive Textual Documents Collation Systems
(2011)
One of the main purposes of textual documents collation is to identify a base text or closest witness to the base text, by analyzing and interpreting differences also known as types of changes that might exist between those documents. Based on this fact, it is reasonable to argue that, explicit identification of types of changes such as deletions, additions, transpositions, and mutations should be part of the collation process. The identification could be carried out by an interpretation module after alignment has taken place. Unfortunately existing collation software such as CollateX1 and Juxta2’s collation engine do not have interpretation modules. In fact they implement the Gothenburg model [1] for collation process which does not include an interpretation unit. Currently both CollateX and Juxta’s collation engine do not distinguish in their critical apparatus between the types of changes, and do not offer statistics about those changes. This paper presents a model for both integrated and distributed collation processes that improves the Gothenburg model. The model introduces an interpretation component for computing and distinguishing between the types of changes that documents could have undergone. Moreover two architectures implementing the model in order to solve the problem of interactive collation are discussed as well. Each architecture uses CollateX library, and provides on the one hand preprocessing functions for transforming input documents into CollateX input format, and on the other hand a post-processing module for enabling interactive collation. Finally simple algorithms for distinguishing between types of changes, and linking collated source documents with the collation results are also introduced.
The Quran is the holy book of Islam consisting of 6236 verses divided into 114 chapters called suras. Many verses are similar and even identical. Searching for similar texts (e.g verses) could return thousands of verses, that when displayed completely or partly as textual list would make analysis and understanding difficult and confusing. Moreover it would be visually impossible to instantly figure out the overall distribution of the retrieved verses in the Quran. As consequence reading and analyzing the verses would be tedious and unintuitive. In this study a combination of interactive scatter plots and tables has been developed to assist analysis and understanding of the search result. Retrieved verses are clustered by chapters, and a weight is assigned to each cluster according to number of verses it contains, so that users could visually identify most relevant areas, and figure out the places of revelation of the verses. Users visualize the complete result and can select a region of the plot to zoom in, click on a marker to display a table containing verses with English translation side by side.
A Knowledge-based Hybrid Statistical Classifier for Reconstructing the Chronology of the Quran
(2011)
Computationally categorizing Quran’s chapters has been mainly confined to the determination of chapters’ revelation places. However this broad classification is not sufficient to effectively and thoroughly understand and interpret the Quran. The chronology of revelation would not only improve comprehending the philosophy of Islam, but also the easiness of implementing and memorizing its laws and recommendations. This paper attempts estimating possible chapters’ dates of revelation through their lexical frequency profiles. A hybrid statistical classifier consisting of stemming and clustering algorithms for comparing lexical frequency profiles of chapters, and deriving dates of revelation has been developed. The classifier is trained using some chapters with known dates of revelation. Then it classifies chapters with uncertain dates of revelation by computing their proximity to the training ones. The results reported here indicate that the proposed methodology yields usable results in estimating dates of revelation of the Quran’s chapters based on their lexical contents.
This paper discusses the categorization of Quranic chapters by major phases of Prophet Mohammad’s messengership using machine learning algorithms. First, the chapters were categorized by places of revelation using Support Vector Machine and naïve Bayesian classifiers separately, and their results were compared to each other, as well as to the existing traditional Islamic and western orientalists classifications. The chapters were categorized into Meccan (revealed in Mecca) and Medinan (revealed in Medina). After that, chapters of each category were clustered using a kind of fuzzy-single linkage clustering approach, in order to correspond to the major phases of Prophet Mohammad’s life. The major phases of the Prophet’s life were manually derived from the Quranic text, as well as from the secondary Islamic literature e.g hadiths, exegesis. Previous studies on computing the places of revelation of Quranic chapters relied heavily on features extracted from existing background knowledge of the chapters. For instance, it is known that Meccan chapters contain mostly verses about faith and related problems, while Medinan ones encompass verses dealing with social issues, battles…etc. These features are by themselves insufficient as a basis for assigning the chapters to their respective places of revelation. In fact, there are exceptions, since some chapters do contain both Meccan and Medinan features. In this study, features of each category were automatically created from very few chapters, whose places of revelation have been determined through identification of historical facts and events such as battles, migration to Medina…etc. Chapters having unanimously agreed places of revelation were used as the initial training set, while the remaining chapters formed the testing set. The classification process was made recursive by regularly augmenting the training set with correctly classified chapters, in order to classify the whole testing set. Each chapter was preprocessed by removing unimportant words, stemming, and representation with vector space model. The result of this study shows that, the two classifiers have produced useable results, with an outperformance of the support vector machine classifier. This study indicates that, the proposed methodology yields encouraging results for arranging Quranic chapters by phases of Prophet Mohammad’s messengership.
Computing Generic Causes of Revelation of the Quranic Verses Using Machine Learning Techniques
(2011)
Because many verses of the holy Quran are similar, there is high probability that, similar verses addressing same issues share same generic causes of revelation. In this study, machine learning techniques have been employed in order to automatically derive causes of revelation of Quranic verses. The derivation of the causes of revelation is viewed as a classification problem. Initially the categories are based on the verses with known causes of revelation, and the testing set consists of the remaining verses. Based on a computed threshold value, a naïve Bayesian classifier is used to categorize some verses. After that, using a decision tree classifier the remaining uncategorized verses are separated into verses that contain indicators (resultative connectors, causative expressions…), and those that do not. As for those verses having indicators, each one is segmented into its constituent clauses by identification of the linking indicators. Then a dominant clause is extracted and considered either as the cause of revelation, or post-processed by adding or subtracting some terms to form a causal clause that constitutes the cause of revelation. Concerning remaining unclassified verses without indicators, a naive Bayesian classifier is again used to assign each one of them to one of the existing classes based on features and topics similarity. As for verses that could not be classified so far, manual classification was made by considering each verse as a category on its own. The result obtained in this study is encouraging, and shows that automatic derivation of Quranic verses’ generic causes of revelation is achievable, and reasonably reliable for understanding and implementing the teachings of the Quran.
Learning a book in general involves reading it, underlining important words, adding comments, summarizing some passages, and marking up some text or concepts. Once deeper understanding is achieved, one would like to organize and manage her/his knowledge in such a way that, it could be easily remembered and efficiently transmitted to others. This paper discusses about modeling religious texts using semantic XML markup based on frame-based knowledge representation, with the purpose of assisting understanding, retention, and sharing of knowledge they contain. In this study, books organized in terms of chapters made up of verses are considered as the source of knowledge to model. Some metadata representing the multiple perspectives of knowledge modeling are assigned to each chapter and verse. Chapters and verses with their metadata form a meta-model, which is represented using frames, and published on a web mashup. An XML-based annotation and visualization system equipped with user interfaces for creating static and dynamic metadata, annotating chapters’ contents according to user selected semantics, and templates for publishing generated knowledge on the Internet, has been developed. The system has been applied to the Quran, and the result obtained shows that multiple perspectives of information modeling can be successfully applied to religious texts, in order to support analysis, understanding, and retention of the texts.
Given a collection of diverging documents about some lost original text, any person interested in the text would try reconstructing it from the diverging documents. Whether it is eclecticism, stemmatics, or copy-text, one is expected to explicitly or indirectly select one of the documents as a starting point or as a base text, which could be emended through comparison with remaining documents, so that a text that could be designated as the original document is generated. Unfortunately the process of giving priority to one of the documents also known as witnesses is a subjective approach. In fact even Cladistics, which could be considered as a computer-based approach of implementing stemmatics, does not present or recommend users to select a certain witness as a starting point for the process of reconstructing the original document. In this study, a computational method using a rule-based Bayesian classifier is used, to assist text scholars in their attempts of reconstructing a non-existing document from some available witnesses. The method developed in this study consists of selecting a base text successively and collating it with remaining documents. Each completed collation cycle stores the selected base text and its closest witness, along with a weighted score of their similarities and differences. At the end of the collation process, a witness selected more often by majority of base texts is considered as the probable base text of the collection. Witnesses’ scores are weighted using a weighting system, based on effects of types of textual modifications on the process of reconstructing original documents. Users have the possibility to select between baseless and base text collation. If a base text is selected, the task is reduced to ranking the witnesses with respect to the base text, otherwise a base text as well as ranking of the witnesses with respect to the base text are computed and displayed on a bar diagram. Additionally this study includes a recursive algorithm for automatically reconstructing the original text from the identified base text and ranked witnesses.
The question of why the Quran structure does not follow its chronology of revelation is a recurring one. Some Islamic scholars such as [1] have answered the question using hadiths, as well as other philosophical reasons based on internal evidences of the Quran itself. Unfortunately till today many are still wondering about this issue. Muslims believe that the Quran is a summary and a copy of the content of a preserved tablet called Lawhul-Mahfuz located in the heaven. Logically speaking, this suggests that the arrangement of the verses and chapters is expected to be similar to that of the Lawhul-Mahfuz. As for the arrangement of the verses in each chapter, there is unanimity that it was carried out by the Prophet himself under the guidance of Angel Gabriel with the recommendation of God. But concerning the ordering of the chapters, there are reports about some divergences [3] among the Prophet’s companions as to which chapter should precede which one. This paper argues that Quranic chapters might have been arranged according to months and seasons of revelation. In fact, based on some verses of the Quran, it is defendable that the Lawhul-Mahfuz itself is understood to have been structured in terms of the months of the year. In this study, philosophical and mathematical arguments for computing chapters’ months of revelation are discussed, and the result is displayed on an interactive scatter plot.
Overlapping is a common word used to describe documents whose structural dimensions cannot be adequately represented using tree structure. For instance a quotation that starts in one verse and ends in another verse. The problem of overlapping hierarchies is a recurring one, which has been addressed by a variety of approaches. There are XML based solutions as well as Non-XML ones. The XML-based solutions are: multiple documents, empty elements, fragmentation, out-of-line markup, JITT and BUVH. And the Non-XML approaches comprise CONCUR/XCONCUR, MECS, LMNL ...etc. This paper presents shortly state-of-the-art in overlapping hierarchies, and introduces two variations on the TEI fragmentation markup that have several advantages.
The Visual Editor for XML (Vex)[1] used by TextGrid [2]and other applications has got rendering and layout engines. The layout engine is well documented but the rendering engine is not. This lack of documenting the rendering engine has made refactoring and extending the editor hard and tedious. For instance many CSS2.1 and upcoming CSS3 properties have not been implemented. Software developers in different projects such as TextGrid using Vex would like to update its CSS rendering engine in order to provide advanced user interfaces as well as support different document types. In order to minimize the effort of extending Vex functionality, I found it beneficial to write a basic documentation about Vex software architecture in general and its CSS rendering engine in particular. The documentation is mainly based on the idea of architectural layered diagrams. In fact layered diagrams can help developers understand software’s source code faster and easier in order to alter it, and fix errors. This paper is written for the purpose of providing direct support for exploration in the comprehension process of Vex source code. It discusses Vex software architecture. The organization of packages that make up the software, the architecture of its CSS rendering engine, an algorithm explaining the working principle of its rendering engine are described.
The technique of using Cascading Style Sheets (CSS) to format and present structured data is called CSS processing model. For instance a CSS processing model for XML documents describes steps involved in formatting and presenting XML documents on screens or papers. Many software applications such as browsers and XML editors have their own CSS processing models which are part of their rendering engines. For instance each browser based on its CSS processing model renders CSS layout differently, as a result an inconsistency in the support of CSS features arises. Some browsers support more CSS features than others, and the rendering itself varies. Moreover the W3C standards are not even adhered by some browsers such as Internet Explorer. Test suites and other hacks and filters cannot definitely solve these problems, because these solutions are temporary and fragile. To palliate this inconsistency and browser compatibility issues with respect to CSS, a reference CSS processing model is needed. By extension it could even allow interoperability across CSS rendering engines. A reference architecture would provide common software architecture and interfaces, and facilitate refactoring, reuse, and automated unit testing. In [2] a reference architecture for browsers has been proposed. However this reference architecture is a macro reference model which does not consider separately individual components of rendering and layout engines. In this paper an attempt to develop a reference architecture for CSS processing models is discussed. In addition the Vex editor [3] rendering and layout engines, as well as an extended version of the editor used in TextGrid project [5] are also presented in order to validate the proposed reference architecture.
Empirical Study on Screen Scraping Web Service Creation: Case of Rhein-Main-Verkehrsverbund (RMV)
(2010)
Internet is the biggest database that science and technology have ever produced. The world wide web is a large repository of information that cannot be used for automation by many applications due to its limited target audience. One of the solutions to the automation problem is to develop wrappers. Wrapping is a process whereby unstructured extracted information is transformed into a more structured one such as XML, which could be provided as webservice to other applications. A web service is a web page whose content is well structured so that a computer program can consume it automatically. This paper describes steps involved in constructing wrappers manually in order to automatically generate web services.
This article discusses web frameworks that are available to a software developer in Java language. It introduces MVC paradigm and some frameworks that implement it. The article presents an overview of Struts, Spring MVC, JSF Frameworks, as well as guidelines for selecting one of them as development environment.
Webservices composition is traditionally carried out using composition technologies such as Business Process Execution Language (BPEL) [1] and Web Service Choreography Interface (WSCI) [2]. The composition technology involves the process of web service discovery, invocation, and composition. However these technologies are not easy and flexible enough because they are mainly developer-centric. Moreover majority of websites have not yet embarked into the world of web service, although they have very important and useful information to offer. Is it because they have not understood the usefulness of web services or is it because of the costs? Whatever might be the answers to these questions, time and money are definitely required in order to create and offer web services. To avoid these expenditures, wrappers [7] to automatically generate webservices from websites would be a cheaper and easier solution. Mashups offer a different way of doing webservices composition. In web environment a Mashup is a web application that brings together data from several sources using webservices, APIs, wrappers and so on, in order to create entirely a new application that was not provided before. This paper presents first an overview of Mashups and the process of web service invocation and composition based on Mashup, then describes an example of a web-based simulator for navigation system in Germany.