Search results for: text representation

Authors: Érica Lima

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In the digital era, in which we have an avalanche of information, it is not new that the Internet has brought new modes of communication and knowledge access. Characterized by the multiplicity of discourses, opinions, beliefs and cultures, the web is a space of political-ideological dimensions where people (who often do not know each other) interact and create representations, deconstruct stereotypes, and redefine identities. Currently, the translator needs to be able to deal with digital spaces ranging from specific software to social media, which inevitably impact on his professional life. One of the most impactful ways of being seen in cyberspace is the participation in social networking groups. In addition to its ability to disseminate information among participants, social networking groups allow a significant personal and social exposure. Such exposure is due to the visibility of each participant achieved not only on its personal profile page, but also in each comment or post the person makes in the groups. The objective of this paper is to study the representations of translators and translation process on the Internet, more specifically in publications in two Brazilian groups of great influence on the Facebook: "Translators/Interpreters" and "Translators, Interpreters and Curious". These chosen groups represent the changes the network has brought to the profession, including the way translators are seen and see themselves. The analyzed posts allowed a reading of what common sense seems to think about the translator as opposed to what the translators seem to think about themselves as a professional class. The results of the analysis lead to the conclusion that these two positions are antagonistic and sometimes represent conflict of interests: on the one hand, the society in general consider the translator’s work something easy, therefore it is not necessary to be well remunerated; on the other hand, the translators who know how complex a translation process is and how much it takes to be a good professional. The results also reveal that social networking sites such as Facebook provide more visibility, but it takes a more active role from the translator to achieve a greater appreciation of the profession and more recognition of the role of the translator, especially in face of increasingly development of automatic translation programs.

Keywords: Facebook, social representation, translation, translator

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Authors: Mahmoud Abualsoud

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The era of Thutmosis III represents a transitional period between the art of the Thutmoside art and the Amarna period, so we intend to declare that it serves as the cradle of Amarna art. The study will examine the Statues of king Thutmose III that was discovered in Luxor by an Egyptian mission. These Statues have been transferred to the Conservation Center of the Grand Egyptian Museum (GEM) to be conserved and made ready to be displayed at the new museum (the project of the century). We focus on three Statues chosen because they relate to different years of the king's reign. These Statues were all made of granite. The first one is a Kneeling statue representing the god Amun showing king Thutmose III offering to the goddess Hathor. The second is decorated with king Thutmose III with the red crown, between the goddess Hathor and the royal wife, Nefertari. The third shows the king offering NW vessels and bread to the god Seker. Each statue is divided into registers containing a description and decorated with scenes of the king presenting offerings to gods. The proposed study will focus on the development which happened sequentially according to differences that occur in each statue. We will use comparative research to determine the workshops of these statues, whether one or several, and what are the distinguishing features of each one. We will examine what innovations the artisans added to royal art. The description and the texts will be translated with linguistic comments. This research focuses on text analyses and technology. Paleographic information found on these objects includes the names and titles of the king. This research focuses on text analyses and technology. The study aims to create a manual that may help in dating the artwork of Thutmosis III. This research will be beneficial and useful for heritage and ancient civilizations, particularly when we talk about opening museums like the Grand Egyptian Museum, which will exhibit a collection of statues. Indeed, this kind of study will open a new destination in order to know how to identify these collections and how to exhibit them commensurate with the nature of ancient Egyptian history and heritage.

Keywords: archaeological study, Giza, new kingdom, statues, royal art

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Authors: Valmir Moratelli

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This paper discusses the construction of the narrative of television fiction from the point of view of the invisibility of the representation of elderly black characters. Through the appointment of social and contemporary elements, we analyze why the theme of old age of black people is practically non-existent in brazilian soap operas of TV Globo. By raising characteristic aspects of the leaflet narrative, we want to discuss how the cancellation of identity discourses about elderly blacks and their relationship with aspects of social life is constructed.

Keywords: audiovisual, black, erderly, television

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Authors: Ryan Villafuerte Lansangan

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Assessing students’ understanding in the microscopic level of an abstract subject like chemistry poses a challenge to teachers. Literature reveals that the use of representations serves as an essential avenue of measuring the extent of understanding in the discipline as an alternative to traditional assessment methods. This undertaking explored the representational competence profile of high school students from the University of Santo Tomas High School in understanding selected chemical principles and correlate this with their academic profile in chemistry based on their performance in the academic achievement examination in chemistry administered by the Center for Education Measurement (CEM). The common misconceptions of the students on the selected chemistry principles based on their representations were taken into consideration as well as the students’ views regarding their understanding of the role of chemical representations in their learning. The students’ level of representation task instrument consisting of the main lessons in chemistry with a corresponding scoring guide was prepared and utilized in the study. The study revealed that most of the students under study are unanimously rated as Level 2 (symbolic level) in terms of their representational competence in understanding the selected chemical principles through the use of chemical representations. Alternative misrepresentations were most observed on the students’ representations on chemical bonding concepts while the concept of chemical equation appeared to be the most comprehensible topic in chemistry for the students. Data implies that teachers’ representations play an important role in helping the student understand the concept in a microscopic level. Results also showed that the academic achievement in the chemistry of the students based on the standardized CEM examination has a significant association with the students’ representational competence. In addition, the students’ responses on the students’ views in chemical representations questionnaire evidently showed a good understanding of what a chemical representation or a mental model is by drawing a negative response that these tools should be an exact replica. Moreover, the students confirmed a greater appreciation that chemical representations are explanatory tools.

Keywords: chemical representations, representational competence, academic profile in chemistry, secondary students

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Authors: Jayanti De

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Users of any urban road infrastructure may be classified into various categories. The current paper intends to see whether the opinions on different environmental and transportation criteria vary significantly among different types of road users or not. The paper addresses this issue by using a unique survey data that has been collected from Kolkata, a highly populated city in India. Multiple criteria should be taken into account while planning on infrastructure development programs. Given limited resources, a welfare maximizing government typically resorts to public opinion by designing surveys for prioritization of one project over another. Designing such surveys can be challenging and costly. Deciding upon whom to include in a survey and how to represent each group of consumers/road-users depend crucially on how opinion for different criteria vary across consumer groups. A unique dataset has been collected from various parts of Kolkata to statistically test (using Kolmogorov-Smirnov test) whether assigning of weights to rank the transportation criteria like congestion, air pollution, noise pollution, and morning/evening delay vary significantly across the various groups of users of such infrastructure. The different consumer/user groups in the dataset include pedestrian, private car owner, para-transit (taxi /auto rickshaw) user, public transport (bus) user and freight transporter among others. Very little evidence has been found that ranking of different criteria among these groups vary significantly. This also supports the hypothesis that road- users/consumers form their opinion by using their long-run rather than immediate experience. As a policy prescription, this implies that under-representation or over-representation of a specific consumer group in a survey may not necessarily distort the overall opinion, since opinions across different consumer groups are highly correlated as evident from this particular case study.

Keywords: multi criteria analysis, project-prioritization, road- users, survey designing

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Authors: Jeonghwan Jeon

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With the advent of IPTV in the fierce competition with existing broadcasting system, it is emerged as an important issue to predict how much the adoption of IPTV service will be. This paper aims to suggest a prediction model for adopting IPTV using classification and Ranking Belief Simplex (CaRBS). A simplex plot method of representing data allows a clear visual representation to the degree of interaction of the support from the variables to the prediction of the objects. CaRBS is applied to the survey data on the IPTV adoption.

Keywords: prediction, adoption, IPTV, CaRBS

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Authors: Jia-Jane Shuai

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Purpose of this research aims to improve understanding of the nature of online religion by examining the religious social websites. What motivates individual users to use the online religious social websites, and which factors affect those motivations. We survey various online religious social websites provided by different religions, especially the Taiwanese folk religion. Based on the theory of the Content Analysis and Social Network Analysis, religious social websites and religious web activities are examined. This research examined the folk religion websites’ presentation and contents that promote the religious use of the Internet in Taiwan. The difference among different religions and religious websites also be compared. First, this study used keywords to examine what types of messages gained the most clicks of “Like”, “Share” and comments on Facebook. Dividing the messages into four media types, namely, text, link, video, and photo, reveal which category receive more likes and comments than the others. Meanwhile, this study analyzed the five dialogic principles of religious websites accessed from mobile phones and also assessed their mobile readiness. Using the five principles of dialogic theory as a basis, do a general survey on the websites with elements of online religion. Second, the project analyzed the characteristics of Taiwanese participants for online religious activities. Grounded by social network analysis and text mining, this study comparatively explores the network structure, interaction pattern, and geographic distribution of users involved in communication networks of the folk religion in social websites and mobile sites. We studied the linkage preference of different religious groups. The difference among different religions and religious websites also be compared. We examined the reasons for the success of these websites, as well as reasons why young users accept new religious media. The outcome of the research will be useful for online religious service providers and non-profit organizations to manage social websites and internet marketing.

Keywords: content analysis, online religion, social network analysis, social websites

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Authors: Mehrnaz Mostafavi

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The assessment and categorization of incidental lung nodules present a considerable challenge in healthcare, often necessitating resource-intensive multiple computed tomography (CT) scans for growth confirmation. This research addresses this issue by introducing a distinct computational approach leveraging radiomics and deep-learning methods. However, understanding local services is essential before implementing these advancements. With diverse tracking methods in place, there is a need for efficient and accurate identification approaches, especially in the context of managing lung nodules alongside pre-existing cancer scenarios. This study explores the integration of text-based algorithms in medical data curation, indicating their efficacy in conjunction with machine learning and deep-learning models for identifying lung nodules. Combining medical images with text data has demonstrated superior data retrieval compared to using each modality independently. While deep learning and text analysis show potential in detecting previously missed nodules, challenges persist, such as increased false positives. The presented research introduces a Structured-Query-Language (SQL) algorithm designed for identifying pulmonary nodules in a tertiary cancer center, externally validated at another hospital. Leveraging natural language processing (NLP) and machine learning, the algorithm categorizes lung nodule reports based on sentence features, aiming to facilitate research and assess clinical pathways. The hypothesis posits that the algorithm can accurately identify lung nodule CT scans and predict concerning nodule features using machine-learning classifiers. Through a retrospective observational study spanning a decade, CT scan reports were collected, and an algorithm was developed to extract and classify data. Results underscore the complexity of lung nodule cohorts in cancer centers, emphasizing the importance of careful evaluation before assuming a metastatic origin. The SQL and NLP algorithms demonstrated high accuracy in identifying lung nodule sentences, indicating potential for local service evaluation and research dataset creation. Machine-learning models exhibited strong accuracy in predicting concerning changes in lung nodule scan reports. While limitations include variability in disease group attribution, the potential for correlation rather than causality in clinical findings, and the need for further external validation, the algorithm's accuracy and potential to support clinical decision-making and healthcare automation represent a significant stride in lung nodule management and research.

Keywords: lung cancer diagnosis, structured-query-language (SQL), natural language processing (NLP), machine learning, CT scans

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Authors: Hsiao-Yung Wang

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This essay aims to examine how the transgender imagery has been constructed in the Taiwanese news media and its evolution from 1953 to 2016. It also explores the discourse patterns and rhetorical strategies in the transgender-related issues which contributed to levels of evaluation in forming ‘social deviance.’ Samples for analysis were selected from mainstream newspapers, including China Times, United Daily and Apple Daily. The time frame for sample selection is from August 1953 (when the first transgender case was reported in Taiwan) to June 2016. To enhance understanding of media representation as nominalistic-based, the author refers to the representative of critical rhetoric Raymie McKerrow for his study on remembrance and forgetfulness in public discourse (especially in his model of ‘critique of domination’); thereby categorizing the 64 years of transgender discourse into five periods: (1) transgender as ‘intersex’ of surgical-reparative medical treatment; (2) transgender as ‘freak gender-bender’ with criminal behaviors; (3) transgender as ‘ladyboy’ (‘katoey in a Thai term) of bar girls or sex workers; (4) transgender as ‘cross dresser’ of transvestite performance; and (5) transgender as ‘life-style or human right’ of spontaneous gender identification. Based on the research findings, this essay argues that the characterization of transgender reporting as a site for the production of compulsory sexism and gender stereotype by the specific forms of name-calling. Besides, the evolution of word-image addressing to transgender issues also pinpoints media as a reflection of fashion of the day. While the transgender imagery might be crystallized as ‘still social problems’ or ‘gender transgression’ in insidious rhetoric; and while the so-called ‘phobia’ persistently embodies in media discourse to exercise name-calling in an ambiguous (rather than in a bullying) way or under the cover of humanist-liberalist rationales, these emergent rhetorical dilemma should be resolved without any delay.

Keywords: critical rhetoric, media representation, McKerrow, nominalistic, social deviance, transgender

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Authors: Ali S. Gargoum

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Graphical modeling plays an important role in providing efficient probability calculations in high dimensional problems (computational efficiency). In this paper, we address one of such problems where we discuss fragmenting puff models and some distributional assumptions concerning models for the instantaneous, emission readings and for the fragmenting process. A graphical representation in terms of a junction tree of the conditional probability breakdown of puffs and puff fragments is proposed.

Keywords: graphical models, influence diagrams, junction trees, Bayesian nets

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Authors: Julia Ive, Lucia Specia

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Understanding and detecting toxicity is an important problem to support safer human interactions online. Our work focuses on the important problem of contextual toxicity detection, where automated classifiers are tasked with determining whether a short textual segment (usually a sentence) is toxic within its conversational context. We use “toxicity” as an umbrella term to denote a number of variants commonly named in the literature, including hate, abuse, offence, among others. Detecting toxicity in context is a non-trivial problem and has been addressed by very few previous studies. These previous studies have analysed the influence of conversational context in human perception of toxicity in controlled experiments and concluded that humans rarely change their judgements in the presence of context. They have also evaluated contextual detection models based on state-of-the-art Deep Learning and Natural Language Processing (NLP) techniques. Counterintuitively, they reached the general conclusion that computational models tend to suffer performance degradation in the presence of context. We challenge these empirical observations by devising better contextual predictive models that also rely on NLP data augmentation techniques to create larger and better data. In our study, we start by further analysing the human perception of toxicity in conversational data (i.e., tweets), in the absence versus presence of context, in this case, previous tweets in the same conversational thread. We observed that the conclusions of previous work on human perception are mainly due to data issues: The contextual data available does not provide sufficient evidence that context is indeed important (even for humans). The data problem is common in current toxicity datasets: cases labelled as toxic are either obviously toxic (i.e., overt toxicity with swear, racist, etc. words), and thus context does is not needed for a decision, or are ambiguous, vague or unclear even in the presence of context; in addition, the data contains labeling inconsistencies. To address this problem, we propose to automatically generate contextual samples where toxicity is not obvious (i.e., covert cases) without context or where different contexts can lead to different toxicity judgements for the same tweet. We generate toxic and non-toxic utterances conditioned on the context or on target tweets using a range of techniques for controlled text generation(e.g., Generative Adversarial Networks and steering techniques). On the contextual detection models, we posit that their poor performance is due to limitations on both of the data they are trained on (same problems stated above) and the architectures they use, which are not able to leverage context in effective ways. To improve on that, we propose text classification architectures that take the hierarchy of conversational utterances into account. In experiments benchmarking ours against previous models on existing and automatically generated data, we show that both data and architectural choices are very important. Our model achieves substantial performance improvements as compared to the baselines that are non-contextual or contextual but agnostic of the conversation structure.

Keywords: contextual toxicity detection, data augmentation, hierarchical text classification models, natural language processing

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Authors: Shankaran Sitarama

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New Product Development (NPD) is invariably a team effort and involves effective teamwork. NPD team has members from different disciplines coming together and working through the different phases all the way from conceptual design phase till the production and product roll out. Creativity and Innovation are some of the key factors of successful NPD. Team members going through the different phases of NPD interact and work closely yet challenge each other during the design phases to brainstorm on ideas and later converge to work together. These two traits require the teams to have a divergent and a convergent thinking simultaneously. There needs to be a good balance. The team dynamics invariably result in conflicts among team members. While some amount of conflict (ideational conflict) is desirable in NPD teams to be creative as a group, relational conflicts (or discords among members) could be detrimental to teamwork. Team communication truly reflect these tensions and team dynamics. In this research, team communication (emails) between the members of the NPD teams is considered for analysis. The email communication is processed through a semantic analysis algorithm (LSA) to analyze the content of communication and a semantic similarity analysis to arrive at a social network graph that depicts the communication amongst team members based on the content of communication. The amount of communication (content and not frequency of communication) defines the interaction strength between the members. Social network adjacency matrix is thus obtained for the team. Standard social network analysis techniques based on the Adjacency Matrix (AM) and Dichotomized Adjacency Matrix (DAM) based on network density yield network graphs and network metrics like centrality. The social network graphs are then rendered for visual representation using a Metric Multi-Dimensional Scaling (MMDS) algorithm for node placements and arcs connecting the nodes (representing team members) are drawn. The distance of the nodes in the placement represents the tie-strength between the members. Stronger tie-strengths render nodes closer. Overall visual representation of the social network graph provides a clear picture of the team’s interactions. This research reveals four distinct patterns of team interaction that are clearly identifiable in the visual representation of the social network graph and have a clearly defined computational scheme. The four computational patterns of team interaction defined are Central Member Pattern (CMP), Subgroup and Aloof member Pattern (SAP), Isolate Member Pattern (IMP), and Pendant Member Pattern (PMP). Each of these patterns has a team dynamics implication in terms of the conflict level in the team. For instance, Isolate member pattern, clearly points to a near break-down in communication with the member and hence a possible high conflict level, whereas the subgroup or aloof member pattern points to a non-uniform information flow in the team and some moderate level of conflict. These pattern classifications of teams are then compared and correlated to the real level of conflict in the teams as indicated by the team members through an elaborate self-evaluation, team reflection, feedback form and results show a good correlation.

Keywords: team dynamics, team communication, team interactions, social network analysis, sna, new product development, latent semantic analysis, LSA, NPD teams

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Authors: Carolyn Scott, Rachel Nugent

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The agricultural industry in Ireland and worldwide is one of the most dangerous occupations with respect to occupational health and safety accidents and fatalities. Many accident causation models have been developed in safety research to understand the underlying and contributory factors that lead to the occurrence of an accident. Due to the uniqueness of the agricultural sector, current accident causation theories cannot be applied. This paper presents an accident causation model named the Irish Farm Accident Causation Model (IFACM) which has been specifically tailored to the needs of Irish farms. The IFACM is a theoretical and practical model of accident causation that arranges the causal factors into a graphic representation of originating, shaping, and contributory factors that lead to accidents when unsafe acts and conditions are created that are not rectified by control measures. Causes of farm accidents were assimilated by means of a thorough literature review and were collated to form a graphical representation of the underlying causes of a farm accident. The IFACM was validated retrospectively through case study analysis and peer review. Participants in the case study (n=10) identified causes that led to a farm accident in which they were involved. A root cause analysis was conducted to understand the contributory factors surrounding the farm accident, traced back to the ‘root cause’. Experts relevant to farm safety accident causation in the agricultural industry have peer reviewed the IFACM. The accident causation process is complex. Accident prevention requires a comprehensive understanding of this complex process because to prevent the occurrence of accidents, the causes of accidents must be known. There is little research on the key causes and contributory factors of unsafe behaviours and accidents on Irish farms. The focus of this research is to gain a deep understanding of the causality of accidents on Irish farms. The results suggest that the IFACM framework is helpful for the analysis of the causes of accidents within the agricultural industry in Ireland. The research also suggests that there may be international applicability if further research is carried out. Furthermore, significant learning can be obtained from considering the underlying causes of accidents.

Keywords: farm safety, farm accidents, accident causation, root cause analysis

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Authors: Feyzan Tuzkaya, Nihan S. Soylu, Caglar Solak, Mehmet Peker, Hilal Peker, Kemal Ozeralp, Ceren Mete, Ezgi Mehmetoglu, Mehmet Karasu, Cihan Elci, Ece Akca, Melek Goregenli

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Perception, evaluation and representation of the environment have been the subject of many disciplines including psychology, geography and architecture. In environmental and social psychology literature there are several evidences which suggest that cognitive representations about a place consisted of not only geographic items but also social and cultural. Mental representations of residence area or a country is influenced and determined by social-demographics, the physical and social context. Thus, all mental representations of a given place are also social representations. Cognitive maps are the main and common instruments that are used to identify spatial images and the difference between physical and subjective environments. The aim of the current study is investigating the mental and social representations of Turkey in university students’ minds. Data was collected from 249 university students from different departments (i.e. psychology, geography, history, tourism departments) of Ege University. Participants were requested to reflect Turkey in their mind onto the paper drawing sketch maps. According to the results, cognitive maps showed geographic aspects of Turkey as well as the context of symbolic, cultural and political reality of Turkey. That is to say, these maps had many symbolic and verbal items related to critics on social and cultural problems, ongoing ethnic and political conflicts, and actual political agenda of Turkey. Additionally, one of main differentiations in these representations appeared in terms of the East and West side of the Turkey, and the representations of the East and West was varied correspondingly participants’ cultural background, their ethnic values, and where they have born. The results of the study were discussed in environmental and social psychological perspective considering cultural and social values of Turkey and current political circumstances of the country.

Keywords: cognitive maps, East, West, politics, social representations, Turkey

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Authors: Mahmoud B. Rokaya

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The study of opinion mining and sentiment analysis includes analysis of opinions, sentiments, evaluations, attitudes, and emotions. The rapid growth of social media, social networks, reviews, forum discussions, microblogs, and Twitter, leads to a parallel growth in the field of sentiment analysis. The field of sentiment analysis tries to develop effective tools to make it possible to capture the trends of people. There are two approaches in the field, lexicon-based and corpus-based methods. A lexicon-based method uses a sentiment lexicon which includes sentiment words and phrases with assigned numeric scores. These scores reveal if sentiment phrases are positive or negative, their intensity, and/or their emotional orientations. Creation of manual lexicons is hard. This brings the need for adaptive automated methods for generating a lexicon. The proposed method generates dynamic lexicons based on the corpus and then classifies text using these lexicons. In the proposed method, different approaches are combined to generate lexicons from text. The proposed method classifies the tweets into 5 classes instead of +ve or –ve classes. The sentiment classification problem is written as an optimization problem, finding optimum sentiment lexicons are the goal of the optimization process. The solution was produced based on mathematical programming approaches to find the best lexicon to classify texts. A genetic algorithm was written to find the optimal lexicon. Then, extraction of a meta-level feature was done based on the optimal lexicon. The experiments were conducted on several datasets. Results, in terms of accuracy, recall and F measure, outperformed the state-of-the-art methods proposed in the literature in some of the datasets. A better understanding of the Arabic language and culture of Arab Twitter users and sentiment orientation of words in different contexts can be achieved based on the sentiment lexicons proposed by the algorithm.

Keywords: social media, Twitter sentiment, sentiment analysis, lexicon, genetic algorithm, evolutionary computation

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Authors: Carmen Noheda

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This text provides a reflection on the way of thinking about the study of the history of music by examining the production of historiography in Spain at the turn of the century. Based on concepts developed by the historical theorist Jörn Rüsen, the article focuses on the following aspects: the theoretical artifacts that structure the interpretation of the limits of writing the history of music, the narrative patterns used to give meaning to the discourse of history, and the orientation context that functions as a source of criteria of significance for both interpretation and representation. This analysis intends to show that historical music theory is not only a means to abstractly explore the complex questions connected to the production of historical knowledge, but also a tool for obtaining concrete images about the intellectual practice of professional musicologists. Writing about the historiography of contemporary Spanish music is a task that requires both a knowledge of the history that is being written and investigated, as well as a familiarity with current theoretical trends and methodologies that allow for the recognition and definition of the different tendencies that have arisen in recent decades. With the objective of carrying out these premises, this project takes as its point of departure the 'immediate historiography' in relation to Spanish music at the beginning of the 21st century. The hesitation that Spanish musicology has shown in opening itself to new anthropological and sociological approaches, along with its rigidity in the face of the multiple shifts in dynamic forms of thinking about history, have produced a standstill whose consequences can be seen in the delayed reception of the historiographical revolutions that have emerged in the last century. Methodologically, this essay is underpinned by Rüsen’s notion of the disciplinary matrix, which is an important contribution to the understanding of historiography. Combined with his parallel conception of differing paradigms of historiography, it is useful for analyzing the present-day forms of thinking about the history of music. Following these theories, the article will in the first place address the characteristics and identification of present historiographical currents in Spanish musicology to thereby carry out an analysis based on the theories of Rüsen. Finally, it will establish some considerations for the future of musical historiography, whose atrophy has not only fostered the maintenance of an ingrained positivist tradition, but has also implied, in the case of Spain, an absence of methodological schools and an insufficient participation in international theoretical debates. An update of fundamental concepts has become necessary in order to understand that thinking historically about music demands that we remember that subjects are always linked by reciprocal interdependencies that structure and define what it is possible to create. In this sense, the fundamental aim of this research departs from the recognition that the history of music is embedded in the conditions that make it conceivable, communicable and comprehensible within a society.

Keywords: historiography, Jörn Rüssen, Spanish musicology, theory of history of music

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Authors: Su-Lin Yu

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In recent years, we have witnessed the growing scholarship on transnational theorizing and activism within disability. In particular, the universalizing discourses of disability formulated in the Global North seem inadequate in engaging the vast diversity of discourses of disability that emerge in global and local policies as well as the everyday experiences of disabled people in the Global South. This study will further consider the future possibilities of how Taiwanese and global disability studies might interchange disability knowledge. First, this study will determine how a local literature of disability can be formed in Taiwan by examining life writings written by Taiwanese disabled women. Both the texts and the personal experiences are treated as social products which can, through their discourses, offer insight into the socio-cultural practices and norms of disability and womanhood in Taiwan. This paper argues that more than by the impairment in itself, the experiences of disabled women are shaped by the social and cultural discourses and practices that define disability and womanhood as well as the normative roles, places, and contexts associated with them. Simultaneous analysis of disability and womanhood exemplifies the way in which disability operates in a complex interaction with the socio-cultural discourses and practices of womanhood, thus producing gender-differentiated disabling obstacles for disabled women. Another purpose of this study is to gain an understanding of the transformative experience of women with disabilities and their perceptions of the self. Designed to provide positive, realistic pictures of the lives of women with disabilities and the social, economic, and political issues they face, their life writings demonstrate how they as disabled women simultaneously struggle with writing a new identity and creating an ethical narrative. These strong and articulate women construct narratives that attempt to recount the remarkable journey that transformed them from dependent women to community activists and writers who speak forcefully about the needs of people with disabilities. More than a story of one woman's struggle for independence, their writing, then, is a testimony to the importance of community building and organizing to enable local people with disabilities to live fulfilling lives.

Keywords: gender, disability, representation, agency

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Authors: Yunus Onur Yildiz, Mesut Kirca

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In this study, mechanical properties of a nanoporous metal coated with a different metallic material are studied through a new atomistic modelling technique and molecular dynamics (MD) simulations. This new atomistic modelling technique is based on the Voronoi tessellation method for the purpose of geometric representation of the ligaments. With the proposed technique, atomistic models of nanoporous metals which have randomly oriented ligaments with non-uniform mass distribution along the ligament axis can be generated by enabling researchers to control both ligament length and diameter. Furthermore, by the utilization of this technique, atomistic models of coated nanoporous materials can be numerically obtained for further mechanical or thermal characterization. In general, this study consists of two stages. At the first stage, we use algorithms developed for generating atomic coordinates of the coated nanoporous material. In this regard, coordinates of randomly distributed points are determined in a controlled way to be employed in the establishment of the Voronoi tessellation, which results in randomly oriented and intersected line segments. Then, line segment representation of the Voronoi tessellation is transformed to atomic structure by a special process. This special process includes generation of non-uniform volumetric core region in which atoms can be generated based on a specific crystal structure. As an extension, this technique can be used for coating of nanoporous structures by creating another volumetric region encapsulating the core region in which atoms for the coating material are generated. The ultimate goal of the study at this stage is to generate atomic coordinates that can be employed in the MD simulations of randomly organized coated nanoporous structures. At the second stage of the study, mechanical behavior of the coated nanoporous models is investigated by examining deformation mechanisms through MD simulations. In this way, the effect of coating on the mechanical behavior of the selected material couple is investigated.

Keywords: atomistic modelling, molecular dynamic, nanoporous metals, voronoi tessellation

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Authors: Umberto Di Staso, Marco Soave, Alessio Giori, Federico Prandi, Raffaele De Amicis

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The increasing availability of information about earth surface elevation (Digital Elevation Models DEM) generated from different sources (remote sensing, Aerial Images, Lidar) poses the question about how to integrate and make available to the most than possible audience this huge amount of data. In order to exploit the potential of 3D elevation representation the quality of data management plays a fundamental role. Due to the high acquisition costs and the huge amount of generated data, highresolution terrain surveys tend to be small or medium sized and available on limited portion of earth. Here comes the need to merge large-scale height maps that typically are made available for free at worldwide level, with very specific high resolute datasets. One the other hand, the third dimension increases the user experience and the data representation quality, unlocking new possibilities in data analysis for civil protection, real estate, urban planning, environment monitoring, etc. The open-source 3D virtual globes, which are trending topics in Geovisual Analytics, aim at improving the visualization of geographical data provided by standard web services or with proprietary formats. Typically, 3D Virtual globes like do not offer an open-source tool that allows the generation of a terrain elevation data structure starting from heterogeneous-resolution terrain datasets. This paper describes a technological solution aimed to set up a so-called “Terrain Builder”. This tool is able to merge heterogeneous-resolution datasets, and to provide a multi-resolution worldwide terrain services fully compatible with CesiumJS and therefore accessible via web using traditional browser without any additional plug-in.

Keywords: Terrain Builder, WebGL, Virtual Globe, CesiumJS, Tiled Map Service, TMS, Height-Map, Regular Grid, Geovisual Analytics, DTM

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Authors: Sadeq Al Yaari, Muhammad Alkhunayn, Adham Al Yaari, Aayah Al Yaari, Montaha Al Yaari, Ayman Al Yaari, Sajedah Al Yaari, Fatehi Eissa

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The recent rise of smart educational aids and the move away from traditional listening aids are leading to a fundamental shift in the way in which individuals with attention and listening problems (ALP) manipulate listening inputs and/or act appropriately to the spoken information presented to them. A total sample of twenty-six ALP pupils (m=20 and f=6) between 7-12 years old was selected from different strata based on gender, region and school. In the sample size, thirteen (10 males and 3 females) received the treatment in terms of smart classes provided with smart educational aids in a listening course that lasted for four months, while others did not (they studied the same course by the same instructor but in ordinary class). A pretest was administered to assess participants’ levels, and a posttest was given to evaluate their attention and listening comprehension performance, namely in phonetic and phonological tests with sociolinguistic themes that have been designed for this purpose. Test results were analyzed both psychoneurolinguistically and statistically. Results reveal a remarkable change in pupils’ behavioral listening where scores witnessed a significant difference in the performance of the experimental ALP group in the pretest compared to the posttest (Pupils performed better at the pretest-posttest on phonetics than at the two tests on phonology). It is concluded that smart educational aids designed for listening skills help not only increase the listening command of pupils with ALP to understand what they listen to but also develop their interactive listening capability and, at the same rate, are responsible for increasing concentrated and in-depth listening capacity. Plus, ALP pupils become able to grasp the audio content of text recordings, including educational audio recordings, news, oral stories and tales, views, spiritual/religious text and general knowledge. However, the pupils have not experienced individual smart audio-visual aids that connect listening to other language receptive and productive skills, which could be the future area of research.

Keywords: smart aids, attention, listening, problems

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Authors: Ahmed Mamdouh

Abstract:

Introduction: The era of Thutmosis III represents a transitional period between the art of the Thutmoside art and the Amarna period, so we intend to declare that it serves as the cradle of Amarna art. The study will examine the Statues of king Thutmose III that was discovered in Luxor by an Egyptian mission. These Statues have been transferred to the Conservation Center of the Grand Egyptian Museum (GEM) to be conserved and made ready to bedisplayed at the new museum (the project of the century). We focus upon three Statues (GEM numbers 45863, 45864, 45865), chosen because they relate to different years of the king's reign. These Statues were all made of granite. The first one is a Kneeling statue representing the god Amun showing king Thutmose III offering to the goddess Hathor. The second is decorated with king Thutmose III with the red crown, between the goddess Hathor and the royal wife, Nefertari. The third shows the king offering NW vessels and bread to the god Seker. Each Statue is divided into registers containing a description and decorated with scenes of the king presenting offerings to gods. Methodology: The proposed study will focus on the development which happened sequentially according to differences that occur in each Statue. We will use comparative research to determine the workshops of these statues, whether one or several, and what are the distinguishing features of each one. We will examine what innovations the artisans added to royal art. The description and the texts will be translated with linguistic comments. This research focuses on text analyses and technology. Paleographic information found on these objects includes the names and titles of the king. Conclusion: This research focuses on text analyses and technology. The study aims to create a manual that may help in dating the artwork of Thutmosis III. This research will be beneficial and useful for heritage and ancient civilizations, particularly when we talk about opening museums like the Grand Egyptian museum, which will exhibit a collection of statues. Indeed this kind of study will open a new destination in order to know how to identify these collections and how to exhibit them commensurate with the nature of ancient Egyptian history and heritage.

Keywords: archaeological study, Giza, new kingdom, statues, royal art

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Authors: Parveen Kumar

Abstract:

This article discusses institute information resources. Information, in its most restricted technical sense, is a sequence of symbols that can be interpreted as message information can be recorded as signs, or transmitted as signals. Information is any kind of event that affects the state of a dynamic system. Conceptually, information is the message being conveyed. This concept has numerous other meanings in different contexts. Moreover, the concept of information is closely related to notions of constraint, communication, control, data, form, instruction, knowledge, meaning, mental stimulus, pattern, perception, representation, and especially entropy.

Keywords: institutions, information institutions, information services for mission-oriented institute, pattern

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Authors: Shrabani Ghosh

Abstract:

Automatic offensive language detection in social media has become a stirring task in today's NLP. Manual Offensive language detection is tedious and laborious work where automatic methods based on machine learning are only alternatives. Previous works have done sentiment analysis over social media in different ways such as supervised, semi-supervised, and unsupervised manner. Domain adaptation in a semi-supervised way has also been explored in NLP, where the source domain and the target domain are different. In domain adaptation, the source domain usually has a large amount of labeled data, while only a limited amount of labeled data is available in the target domain. Pretrained transformers like BERT, RoBERTa models are fine-tuned to perform text classification in an unsupervised manner to perform further pre-train masked language modeling (MLM) tasks. In previous work, hate speech detection has been explored in Gab.ai, which is a free speech platform described as a platform of extremist in varying degrees in online social media. In domain adaptation process, Twitter data is used as the source domain, and Gab data is used as the target domain. The performance of domain adaptation also depends on the cross-domain similarity. Different distance measure methods such as L2 distance, cosine distance, Maximum Mean Discrepancy (MMD), Fisher Linear Discriminant (FLD), and CORAL have been used to estimate domain similarity. Certainly, in-domain distances are small, and between-domain distances are expected to be large. The previous work finding shows that pretrain masked language model (MLM) fine-tuned with a mixture of posts of source and target domain gives higher accuracy. However, in-domain performance of the hate classifier on Twitter data accuracy is 71.78%, and out-of-domain performance of the hate classifier on Gab data goes down to 56.53%. Recently self-supervised learning got a lot of attention as it is more applicable when labeled data are scarce. Few works have already been explored to apply self-supervised learning on NLP tasks such as sentiment classification. Self-supervised language representation model ALBERTA focuses on modeling inter-sentence coherence and helps downstream tasks with multi-sentence inputs. Self-supervised attention learning approach shows better performance as it exploits extracted context word in the training process. In this work, a self-supervised attention mechanism has been proposed to detect hate speech on Gab.ai. This framework initially classifies the Gab dataset in an attention-based self-supervised manner. On the next step, a semi-supervised classifier trained on the combination of labeled data from the first step and unlabeled data. The performance of the proposed framework will be compared with the results described earlier and also with optimized outcomes obtained from different optimization techniques.

Keywords: attention learning, language model, offensive language detection, self-supervised learning

Procedia PDF Downloads 105

Authors: Sadeq Al Yaari, Muhammad Alkhunayn, Adham Al Yaari, Ayah Al Yaari, Ayman Al Yaari, Montaha Al Yaari, Sajedah Al Yaari, Fatehi Eissa

Abstract:

The recent rise of smart educational aids and the move away from traditional listening aids are leading to a fundamental shift in the way in which individuals with attention and listening problems (ALP) manipulate listening inputs and/or act appropriately to the spoken information presented to them. A total sample of twenty-six ALP pupils (m=20 and f=6) between 7-12 years old was selected from different strata based on gender, region and school. In the sample size, thirteen (10 males and 3 females) received the treatment in terms of smart classes provided with smart educational aids in a listening course that lasted for four months, while others did not (they studied the same course by the same instructor but in ordinary class). A pretest was administered to assess participants’ levels, and a posttest was given to evaluate their attention and listening comprehension performance, namely in phonetic and phonological tests with sociolinguistic themes that have been designed for this purpose. Test results were analyzed both psychoneurolinguistically and statistically. Results reveal a remarkable change in pupils’ behavioral listening where scores witnessed a significant difference in the performance of the experimental ALP group in the pretest compared to the posttest (Pupils performed better at the pretest-posttest on phonetics than at the two tests on phonology). It is concluded that smart educational aids designed for listening skills help not only increase the listening command of pupils with ALP to understand what they listen to but also develop their interactive listening capability and, at the same rate, are responsible for increasing concentrated and in-depth listening capacity. Plus, ALP pupils become able to grasp the audio content of text recordings, including educational audio recordings, news, oral stories and tales, views, spiritual/religious text and general knowledge. However, the pupils have not experienced individual smart audio-visual aids that connect listening to other language receptive and productive skills, which could be the future area of research.

Keywords: smart educational aids, listening attention, pupils, problems

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Authors: Insaf Ajili, Malik Mallem, Jean-Yves Didier

Abstract:

Human motion recognition has been extensively increased in recent years due to its importance in a wide range of applications, such as human-computer interaction, intelligent surveillance, augmented reality, content-based video compression and retrieval, etc. However, it is still regarded as a challenging task especially in realistic scenarios. It can be seen as a general machine learning problem which requires an effective human motion representation and an efficient learning method. In this work, we introduce a descriptor based on Laban Movement Analysis technique, a formal and universal language for human movement, to capture both quantitative and qualitative aspects of movement. We use Discrete Hidden Markov Model (DHMM) for training and classification motions. We improve the classification algorithm by proposing two DHMMs for each motion class to process the motion sequence in two different directions, forward and backward. Such modification allows avoiding the misclassification that can happen when recognizing similar motions. Two experiments are conducted. In the first one, we evaluate our method on a public dataset, the Microsoft Research Cambridge-12 Kinect gesture data set (MSRC-12) which is a widely used dataset for evaluating action/gesture recognition methods. In the second experiment, we build a dataset composed of 10 gestures(Introduce yourself, waving, Dance, move, turn left, turn right, stop, sit down, increase velocity, decrease velocity) performed by 20 persons. The evaluation of the system includes testing the efficiency of our descriptor vector based on LMA with basic DHMM method and comparing the recognition results of the modified DHMM with the original one. Experiment results demonstrate that our method outperforms most of existing methods that used the MSRC-12 dataset, and a near perfect classification rate in our dataset.

Keywords: human motion recognition, motion representation, Laban Movement Analysis, Discrete Hidden Markov Model

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Authors: Gali Pesin, Yuliya Lipshits-Braziler, Sima Amram-Vaknin, Moshe Tatar

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The present study introduces four different patterns of seeking and providing help online among adolescents: (I) ‘Transceivers’ - adolescents who both seek as well as provide help online; (II) ‘Receivers’ - adolescents who seek help online, yet don’t provide it; (III) ‘Transmitters’ - adolescents who provide help online, yet don’t seek it; and (IV) ‘Idles’ - adolescents who refrain from seeking and providing help online. The study examined differences in seeking and providing help online between possible combinations of the four patterns, as well as gender differences within each pattern. Data was collected from 528 adolescents in Israel (59% were girls). Findings revealed that Transceivers are the largest group (45%) in this study, with higher representation of girls (65%). These adolescents seek help mainly around social difficulties, and they turn to peers who are both known and unknown to them. In addition, their preferred way to seek and provide help is through social network sites. Moreover, they often accept and give others emotional support. Receivers are the smallest group (5%) in this study. They turn to both known and unknown professionals more often than to friends and family. In addition, they seek help mostly around health and nutrition issues, and they usually receive instrumental support. For Receivers, the most important factor for seeking help online is anonymity, and the least important factor is familiarity with the help giver. Transmitters represent 16% of the adolescents in this study, with a greater representation of boys (52%). Their main reason to refrain from seeking help online is self-reliance. Nevertheless, these adolescents provide help to others online, mainly to those known to them through posting or responding to posts on social network sites. Idles represent 34% of the adolescents in this study. They refrain from seeking help online mainly due to their preference to seek help face to face, and due to their lack of trust in the internet or those using it. Idles and Transmitters are willing to seek help online mostly from friends and family. In addition, they are willing seek help online mainly regarding questions concerning military or civil service. They consider the most important facilitators for seeking help online as confidentiality and reliability. The present study’s main contribution is exploring the role of providing online help in understanding the adolescent behavior of seeking help online. In addition, the results of the present study have practical implications for the work of mental health providers, such as counseling psychologists and online mental health support.

Keywords: adolescents, counseling, online help-seeking, online help-providing

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Authors: Giovana Perini-Loureiro

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The purpose of this research was to identify whether the nominalizations terminating in -TION in the academic discourse of native English speakers contain the arguments required by their input verbs. In the perspective of functional linguistics, ideational metaphors, with nominalization as their most pervasive realization, are lexically dense, and therefore frequent in formal texts. Ideational metaphors allow the academic genre to instantiate objectification, de-personalization, and the ability to construct a chain of arguments. The valence of those nouns present in nominalizations tends to maintain the same elements of the valence from its original verbs, but these arguments are not always expressed. The initial hypothesis was that these arguments would also be present alongside the nominalizations, through anaphora or cataphora. In this study, a qualitative analysis of the occurrences of the five more frequent nominalized terminations in -TION in academic texts was accomplished, and thus a verification of the occurrences of the arguments required by the original verbs. The assembling of the concordance lines was done through COCA (Corpus of Contemporary American English). After identifying the five most frequent nominalizations (attention, action, participation, instruction, intervention), the concordance lines were selected at random to be analyzed, assuring the representativeness and reliability of the sample. It was possible to verify, in all the analyzed instances, the presence of arguments. In most instances, the arguments were not expressed, but recoverable, either in the context or in the shared knowledge among the interactants. It was concluded that the realizations of the arguments which were not expressed alongside the nominalizations are part of a continuum, starting from the immediate context with anaphora and cataphora; up to a knowledge shared outside the text, such as specific area knowledge. The study also has implications for the teaching of academic writing, especially with regards to the impact of nominalizations on the thematic and informational flow of the text. Grammatical metaphors are essential to academic writing, hence acknowledging the occurrence of its arguments is paramount to achieve linguistic awareness and the writing prestige required by the academy.

Keywords: corpus, functional linguistics, grammatical metaphors, nominalizations, academic English

Procedia PDF Downloads 146

Authors: Rachel Gough

Abstract:

In 2014, Skellig Michael, an island off Ireland’s western seaboard and UNESCO world heritage site became a major setting in Disney’s Star Wars franchise. The subsequent influx of tourists to the site has proven to be a point of contention nationally. The increased visitor numbers have uplifted certain areas of the local economy, the mainland, but have caused irreparable damage to historic monuments and to endangered bird populations who breed on the island. Recent research carried out by a state body suggests far-reaching and longterm negative impacts on the island’s culture and environment, should the association with the Star Wars franchise persist. In spite of this, the film has been widely endorsed by the Irish government as providing a vital economic boost to historically marginalised rural areas through film tourism. This paper argues quite plainly that what is taking place on Skellig is neocolonialism. Skellig Michael’s unique resources, its aesthetic qualities, its ecosystem, and its cultural currency have been sold by the state to a multinational corporation, who profit from their use. Meanwhile, locals are left to do their best to turn a market trend into sustainable business at the expense of culture ecology and community. This paper intends to be the first dedicated study into the psychogeographic and cultural impact of Skellig Michael’s deterioration as a result of film tourism. It will discuss the projected impact of this incident on Irish culture more broadly and finally will attempt to lay out a roadmap for more collaborative filmmaking and touristic approach, which allows local cultures and ecosystem’s to thrive without drastically inhibiting cultural production. This paper will ultimately find that the consequences of this representation call for a requirement to read tourism as a split concept — namely into what we might loosely call “eco-tourism” and more capital-based “profit-bottom-line tourism.”

Keywords: ecology, film tourism, neocolonialism, sustainability

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Authors: Kalyani Gandhi

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The eighteenth century in Britain saw a great burst of activity in writing (letters, journals, newspapers, essays); often these modes of writing had a public-spirited bent in-step with the prevailing intellectual atmosphere. Mary Wollstonecraft was one of the leading intellectuals of that period who utilized letter writing to convey her thoughts on the exciting political developments of the late eighteenth century. Fusing together her anxieties and concerns about humanity in general and herself in particular, Wollstonecraft’s views of the world around her are filtered through the lens of her subjectivity. Thus, Wollstonecraft’s letters covered a wide range of topics on both the personal and political level (for the two are often entwined in Wollstonecraft’s characteristic style of analysis) such as sentiment, gender, nature, peasantry, the class system, the legal system, political duties and rights of both rulers and subjects, death, immortality, religion, family and education. Therefore, this paper intends to examine the manner in which Wollstonecraft utilizes letter-writing to constitute and develop Romantic self-hood, understand the world around her and illustrate her ideas on the political and social happenings in Europe. The primary text analyzed will be Mary Wollstonecraft's Letters Written During a Short Stay in Sweden, Denmark and Norway (1796) and the analysis of this text will be supplemented by researching 18th-century British letter writing culture, with a special emphasis on the epistolary habits of women. Within this larger framework, this paper intends to examine the manner in which this hybrid of travel and epistolary writing aided Mary Wollstonecraft's expression on Romantic selfhood and how it was complicated by ideas of gender. This paper reveals Wollstonecraft's text to be wrought with anxiety about the world around her and within her; thus, the personal-public nature of the epistolary format particularly suits her characteristic point of view that looks within and without. That is to say, Wollstonecraft’s anxieties about gender and self, are as much about the women she sees in the world around her as much as they are about her young daughter and herself. Wollstonecraft constantly explores and examines this anxiety within the different but interconnected realms of politics, economics, history and society. In fact, it is her complex technique of entwining these aforementioned concerns with a closer look at interpersonal relationships among men and women (she often mentions specific anecdotes and instances) that make Wollstonecraft's Letters so engaging and insightful. Thus, Wollstonecraft’s Letters is an exemplar of British Romantic writing due to the manner in which it explores the bond between the individual and society. Mary Wollstonecraft's nuances this exploration by incorporating her concerns about women and the playing out of gender in society. Thus, Wollstonecraft’s Letters is an invaluable contribution to the field of British Romanticism, particularly as it offers crucial insight on female Romantic writing that can broaden and enrich the current academic understanding of the field.

Keywords: British romanticism, letters, feminism, travel writing

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Authors: Heichia Wang, Yalan Chao

Abstract:

Social inequality is a persistent problem. One of the ways to solve this problem is through education. At present, vulnerable groups are often less geographically accessible to educational resources. However, compared with educational resources, communication equipment is easier for vulnerable groups. Now that information and communication technology (ICT) has entered the field of education, today we can accept the convenience that ICT provides in education, and the mobility that it brings makes learning independent of time and place. With mobile learning, teachers and students can start discussions in an online chat room without the limitations of time or place. However, because liquidity learning is quite convenient, people tend to solve problems in short online texts with lack of detailed information in a lack of convenient online environment to express ideas. Therefore, the ICT education environment may cause misunderstanding between teachers and students. Therefore, in order to better understand each other's views between teachers and students, this study aims to clarify the essays of the analysts and classify the students into several types of learning questions to clarify the views of teachers and students. In addition, this study attempts to extend the description of possible omissions in short texts by using external resources prior to classification. In short, by applying a short text classification, this study can point out each student's learning problems and inform the instructor where the main focus of the future course is, thus improving the ICT education environment. In order to achieve the goals, this research uses convolutional neural network (CNN) method to analyze short discussion content between teachers and students in an ICT education environment. Divide students into several main types of learning problem groups to facilitate answering student problems. In addition, this study will further cluster sub-categories of each major learning type to indicate specific problems for each student. Unlike most neural network programs, this study attempts to extend short texts with external resources before classifying them to improve classification performance. In short, by applying the classification of short texts, we can point out the learning problems of each student and inform the instructors where the main focus of future courses will improve the ICT education environment. The data of the empirical process will be used to pre-process the chat records between teachers and students and the course materials. An action system will be set up to compare the most similar parts of the teaching material with each student's chat history to improve future classification performance. Later, the function of short text classification uses CNN to classify rich chat records into several major learning problems based on theory-driven titles. By applying these modules, this research hopes to clarify the main learning problems of students and inform teachers that they should focus on future teaching.

Keywords: ICT education improvement, social equality, short text analysis, convolutional neural network

Procedia PDF Downloads 128