Search results for: text segmentation

Authors: Thirayu Jumsai na Ayudhya

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Initial attempts to understand about what architecture means to people as they go about their everyday life through my previous research revealed that knowledge such as environmental psychology, environmental perception, environmental aesthetics, did not adequately address a perceived need for the contextualized and holistic theoretical framework. In my previous research, it is found that people’s making senses of their everyday architecture can be described in terms of four super‐ordinate themes; (1) building in urban (text), (2) building in (text), (3) building in human (text), (4) and building in time (text). For more comprehensively understanding of how people make sense of their everyday architectural experience, in this ongoing research Phuket Old town was selected as the focal urban context where the distinguish character of Chino-Portuguese is remarkable. It is expected that in a unique urban context like Phuket old town unprecedented super-ordinate themes will be unveiled through the reflection of people’s everyday experiences. The ongoing research of people’s architectural experience conducted in Phuket Island, Thailand, will be presented succinctly. The research will address the question of how do people make sense of their everyday architecture/buildings especially in a unique urban context, Phuket Old town, and identify ways in which people make sense of their everyday architecture. Participant-Produced-Photograph (PPP) and Interpretative Phenomenological Analysis (IPA) are adopted as main methodologies. PPP allows people to express experiences of their everyday urban context freely without any interference or forced-data generating by researchers. With IPA methodology a small pool of participants is considered desirable given the detailed level of analysis required and its potential to produce a meaningful outcome.

Keywords: architectural experience, the everyday architecture, Phuket, Thailand

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Authors: Claudia Ehrentraut, Osama Ibrahim, Hercules Dalianis

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Policy making situations are real-world problems that exhibit complexity in that they are composed of many interrelated problems and issues. To be effective, policies must holistically address the complexity of the situation rather than propose solutions to single problems. Formulating and understanding the situation and its complex dynamics, therefore, is a key to finding holistic solutions. Analysis of text based information on the policy problem, using Natural Language Processing (NLP) and Text analysis techniques, can support modelling of public policy problem situations in a more objective way based on domain experts knowledge and scientific evidence. The objective behind this study is to support modelling of public policy problem situations, using text analysis of verbal descriptions of the problem. We propose a formal methodology for analysis of qualitative data from multiple information sources on a policy problem to construct a causal diagram of the problem. The analysis process aims at identifying key variables, linking them by cause-effect relationships and mapping that structure into a graphical representation that is adequate for designing action alternatives, i.e., policy options. This study describes the outline of an algorithm used to automate the initial step of a larger methodological approach, which is so far done manually. In this initial step, inferences about key variables and their interrelationships are extracted from textual data to support a better problem structuring. A small prototype for this step is also presented.

Keywords: public policy, problem structuring, qualitative analysis, natural language processing, algorithm, inference extraction

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Authors: L. Godinho, N. Teixeira

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Nowadays, massification of Internet access represents one of the major challenges to the traditional powers of the State, among which the power to control its external image. The virtual world has also sparked the interest of social sciences which consider it a new field of study, an immense open text where sense is expressed. In this paper, that immense text has been accessed to so as to understand the perception Internet users from all over the world have of Portugal. Ours is a quantitative and qualitative approach, as we have resorted to buzz, thematic and category analysis. The results confirm the predominance of sea stereotype in others' vision of the Portuguese people, and evidence that national image has adapted to network communication through processes of individuation and paganization.

Keywords: national image, internet, self-communication, perception

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Authors: Hsin-Yang Wang, K. M. A. Salam, Ying-Jia Lin, Daniel Tan, Tzu-Hsuan Chou, Hung-Yu Kao

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Detecting user intent from natural language expression has a wide variety of use cases in different natural language processing applications. Recently few-shot training has a spike of usage on commercial domains. Due to the lack of significant sample features, the downstream task performance has been limited or leads to an unstable result across different domains. As a state-of-the-art method, the pre-trained BERT model gathering the sentence-level information from a large text corpus shows improvement on several NLP benchmarks. In this research, we are proposing a method to change multi-class classification tasks into binary classification tasks, then use the confidence score to rank the results. As a language model, BERT performs well on sequence data. In our experiment, we change the objective from predicting labels into finding the relations between words in sequence data. Our proposed method achieved 71.0% accuracy in the internal intent detection dataset and 63.9% accuracy in the HuffPost dataset. Acknowledgment: This work was supported by NCKU-B109-K003, which is the collaboration between National Cheng Kung University, Taiwan, and SoftBank Corp., Tokyo.

Keywords: OSML, BERT, text classification, one shot

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Authors: Latha Subbiah, Dhanalakshmi Samiappan

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In this paper, we propose denoising Common Carotid Artery (CCA) B mode ultrasound images by a decomposition approach to curvelet thresholding and automatic segmentation of the intima media thickness and adventitia boundary. By decomposition, the local geometry of the image, its direction of gradients are well preserved. The components are combined into a single vector valued function, thus removes noise patches. Double threshold is applied to inherently remove speckle noise in the image. The denoised image is segmented by active contour without specifying seed points. Combined with level set theory, they provide sub regions with continuous boundaries. The deformable contours match to the shapes and motion of objects in the images. A curve or a surface under constraints is developed from the image with the goal that it is pulled into the necessary features of the image. Region based and boundary based information are integrated to achieve the contour. The method treats the multiplicative speckle noise in objective and subjective quality measurements and thus leads to better-segmented results. The proposed denoising method gives better performance metrics compared with other state of art denoising algorithms.

Keywords: curvelet, decomposition, levelset, ultrasound

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Authors: Sergio V Davalos, Alison L. Watkins

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User generated content (UGC) such as website post has data associated with it: time of the post, gender, location, type of device, and number of words. The text entered in user generated content (UGC) can provide a valuable dimension for analysis. In this research, each user post is treated as a collection of terms (words). In addition to the number of words per post, the frequency of each term is determined by post and by the sum of occurrences in all posts. This research focuses on one specific aspect of UGC: sentiment. Sentiment analysis (SA) was applied to the content (user posts) of two sets of political forums related to the US presidential elections for 2012 and 2016. Sentiment analysis results in deriving data from the text. This enables the subsequent application of data analytic methods. The SASA (SAIL/SAI Sentiment Analyzer) model was used for sentiment analysis. The application of SASA resulted with a sentiment score for each post. Based on the sentiment scores for the posts there are significant differences between the content and sentiment of the two sets for the 2012 and 2016 presidential election forums. In the 2012 forums, 38% of the forums started with positive sentiment and 16% with negative sentiment. In the 2016 forums, 29% started with positive sentiment and 15% with negative sentiment. There also were changes in sentiment over time. For both elections as the election got closer, the cumulative sentiment score became negative. The candidate who won each election was in the more posts than the losing candidates. In the case of Trump, there were more negative posts than Clinton’s highest number of posts which were positive. KNIME topic modeling was used to derive topics from the posts. There were also changes in topics and keyword emphasis over time. Initially, the political parties were the most referenced and as the election got closer the emphasis changed to the candidates. The performance of the SASA method proved to predict sentiment better than four other methods in Sentibench. The research resulted in deriving sentiment data from text. In combination with other data, the sentiment data provided insight and discovery about user sentiment in the US presidential elections for 2012 and 2016.

Keywords: sentiment analysis, text mining, user generated content, US presidential elections

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Authors: Chayanika Hazarika Bordoloi

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This paper is an attempt to work on a highly inflectional language called Assamese. This is also one of the national languages of India and very little has been achieved in terms of computational research. Building a language processing tool for a natural language is not very smooth as the standard and language representation change at various levels. This paper presents inflectional suffixes of Assamese verbs and how the statistical tools, along with linguistic features, can improve the tagging accuracy. Conditional random fields (CRF tool) was used to automatically tag and train the text data; however, accuracy was improved after linguistic featured were fed into the training data. Assamese is a highly inflectional language; hence, it is challenging to standardizing its morphology. Inflectional suffixes are used as a feature of the text data. In order to analyze the inflections of Assamese word forms, a list of suffixes is prepared. This list comprises suffixes, comprising of all possible suffixes that various categories can take is prepared. Assamese words can be classified into inflected classes (noun, pronoun, adjective and verb) and un-inflected classes (adverb and particle). The corpus used for this morphological analysis has huge tokens. The corpus is a mixed corpus and it has given satisfactory accuracy. The accuracy rate of the tagger has gradually improved with the modified training data.

Keywords: CRF, morphology, tagging, tagset

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Authors: Thuy Hanh Nguyen Thi

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By the method of deep reading and text analysis, this article will analyze the use and creation of dialects as a way of demonstrating Yan Lianke's creative stance. This article indicates that this is the writer’s narrative strategy in a fight against aphasia, a language disorder of Chinese people and culture, demonstrating a sense of return to folklore and marks his own linguistic style. In terms of verbal text, the dialect in the Yan Lianke’s novels manifested through the use of words, sentences and dialects. There are two types of dialects that exist in Yan Lianke’s novels: the current dialect system and the particular dialect system of Pa Lau world created by the writer himself in order to enrich the vocabulary of Han Chinese.

Keywords: Yan Lianke , aphasia, dialect, Pa Lou world

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Authors: Van Thinh Bui, Anh Tuan Tran, Quoc Viet Ngo, The Bao Pham

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Video retrieval is a searching problem on videos or clips based on content in which they are relatively close to an input image or video. The application of this retrieval consists of selecting video in a folder or recognizing a human in security camera. However, some recent approaches have been in challenging problem due to the diversity of video types, frame transitions and camera positions. Besides, that an appropriate measures is selected for the problem is a question. In order to overcome all obstacles, we propose a content-based video retrieval system in some main steps resulting in a good performance. From a main video, we process extracting keyframes and principal objects using Segmentation of Aggregating Superpixels (SAS) algorithm. After that, Speeded Up Robust Features (SURF) are selected from those principal objects. Then, the model “Bag-of-words” in accompanied by SVM classification are applied to obtain the retrieval result. Our system is performed on over 300 videos in diversity from music, history, movie, sports, and natural scene to TV program show. The performance is evaluated in promising comparison to the other approaches.

Keywords: video retrieval, principal objects, keyframe, segmentation of aggregating superpixels, speeded up robust features, bag-of-words, SVM

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Authors: Elham Shirvani–Ghadikolaei, Seyed Mahdi Sajjadi

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State of the art technology has the tremendous impact on our life, in this situation education system have been influenced as well as. In this paper, tried to compare two space of learning text and hypertext with each other, and some challenges of using hypertext in religious education. Regarding the fact that, hypertext is an undeniable part of learning in this world and it has highly beneficial for the education process from class to office and home. In this paper tried to solve this question: the consequences and challenges of applying hypertext in religious education. Also, the consequences of this survey demonstrate the role of curriculum designer and planner of education to solve this problem.

Keywords: Hyper-textual, learning, religious education, learning text

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Authors: Eunjung Lee

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This research investigates the intricate connection between cultural differences and online consumer behaviors by integrating Hofstede's Cultural Dimensions theory with analysis methodologies such as text mining, data mining, and topic analysis. Our aim is to provide a comprehensive understanding of how national cultural differences influence individuals' behaviors when engaging with online reviews. To ensure the relevance of our investigation, we systematically analyze and interpret the cultural nuances influencing online consumer behaviors, especially in the context of online reviews. By anchoring our research in Hofstede's Cultural Dimensions theory, we seek to offer valuable insights for marketers to tailor their strategies based on the cultural preferences of diverse global consumer bases. In our methodology, we employ advanced text mining techniques to extract insights from a diverse range of online reviews gathered globally for a specific product or service like Netflix. This approach allows us to reveal hidden cultural cues in the language used by consumers from various backgrounds. Complementing text mining, data mining techniques are applied to extract meaningful patterns from online review datasets collected from different countries, aiming to unveil underlying structures and gain a deeper understanding of the impact of cultural differences on online consumer behaviors. The study also integrates topic analysis to identify recurring subjects, sentiments, and opinions within online reviews. Marketers can leverage these insights to inform the development of culturally sensitive strategies, enhance target audience segmentation, and refine messaging approaches aligned with cultural preferences. Anchored in Hofstede's Cultural Dimensions theory, our research employs sophisticated methodologies to delve into the intricate relationship between cultural differences and online consumer behaviors. Applied to specific cultural dimensions, such as individualism vs. collectivism, masculinity vs. femininity, uncertainty avoidance, and long-term vs. short-term orientation, the study uncovers nuanced insights. For example, in exploring individualism vs. collectivism, we examine how reviewers from individualistic cultures prioritize personal experiences while those from collectivistic cultures emphasize communal opinions. Similarly, within masculinity vs. femininity, we investigate whether distinct topics align with cultural notions, such as robust features in masculine cultures and user-friendliness in feminine cultures. Examining information-seeking behaviors under uncertainty avoidance reveals how cultures differ in seeking detailed information or providing succinct reviews based on their comfort with ambiguity. Additionally, in assessing long-term vs. short-term orientation, the research explores how cultural focus on enduring benefits or immediate gratification influences reviews. These concrete examples contribute to the theoretical enhancement of Hofstede's Cultural Dimensions theory, providing a detailed understanding of cultural impacts on online consumer behaviors. As online reviews become increasingly crucial in decision-making, this research not only contributes to the academic understanding of cultural influences but also proposes practical recommendations for enhancing online review systems. Marketers can leverage these findings to design targeted and culturally relevant strategies, ultimately enhancing their global marketing effectiveness and optimizing online review systems for maximum impact.

Keywords: comparative analysis, cultural dimensions, marketing intelligence, national culture, online consumer behavior, text mining

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Authors: Marilia Correa Parecis De Oliveira

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This research looks at the novel Miguel e os demônios (2009), by the contemporary Brazilian author Lourenço Mutarelli. In it, the presence of film language resources is remarkable, creating thus a kind of scripted writing. We intend to analyze the presence of film language in work under study, in which there is a mixture of the characteristics of the novel and screenplay genres, trying to explore which aesthetic and meaning effects of the ownership of a visual language for the creation of a literary text create in the novel. The objective of this research is to identify and analyze the formal and thematic aspects that characterize the hybridity of literature and film in the novel by Lourenço Mutarelli. The method employed comprises reading and production cataloging of theoretical and critical texts, literary and film theory, historical review about the author, and also the realization of an analytical and interpretative reading of novel. In Miguel e os demônios there is a range of formal and thematic elements of popular narrative genres such as the detective story and action film, with a predominance of verb forms in the present and NPs - features that tend to make present the narrated scenes, as in the cinema. The novel, in this sense, is located in an intermediate position between the literary text and the pre-film text, as though filled with proper elements of the language of film, you can not fit it categorically in the genre script, since it does not reduce the script because aspires to be read as a novel. Therefore, the difficulty of fitting the work in a single gender also refused to be extra-textual factors - such as your publication as novel - but, rather, by the binary classifications serve solely to imprison the work on a label, which impoverish not only reading the text, as also the possibility of recognizing literature as a constant dialogue space and interaction with other media. We can say, therefore, that frame the work Miguel e os demônios in one of the two genres (novel or screenplay) proves not enough, since the text is revealed a hybrid narrative, consisting in a kind of scripted writing. In this sense, it is like a text that is born in a society saturated by audiovisual in their daily lives in order to be consumed by readers who, in ascending scale, exchange books by visual narratives. However, the novel uses film's resources without giving up its constitution as literature; on the contrary, it enriches the visual and linguistically, dialoguing with the complex contemporary horizon marked by the cultural industry.

Keywords: Brazilian literature, cinema, Lourenço Mutarelli, screenplay

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Authors: Habibollah Mashhady, Moslem Fatollahi

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This study tries to contrast the use of metadiscoursal markers in English and Persian Newspaper Editorials as persuasive text types. These markers are linguistic elements in the text which do not add to the propositional content of it, rather they serve to realize the Halliday’s (1985) textual and interpersonal functions of language. At first, some of the most common markers from five subcategories of Text Connectives, Illocution Markers, Hedges, Emphatics, and Attitude Markers were identified in both English and Persian newspapers. Then, the frequency of occurrence of these markers in both English and Persian corpus consisting of 44 randomly selected editorials (18,000 words in each) from several English and Persian newspapers was recorded. After that, using a two-way chi square analysis, the overall x2 obs was found to be highly significant. So, the null hypothesis of no difference was confidently rejected. Finally, in order to determine the contribution of each subcategory to the overall x 2 value, one-way chi square analyses were applied to the individual subcategories. The results indicated that only two of the five subcategories of markers were statistically significant. This difference is then attributed to the differing spirits prevailing in the linguistic communities involved. Regarding the minor research question it was found that, in contrast to English writers, Persian writers are more writer-oriented in their writings.

Keywords: metadiscoursal markers, textual meta-function, interpersonal meta-function, persuasive texts, English and Persian newspaper editorials

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Authors: Yi Gu

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The Three-Body Problem by Cixin Liu has been a bestseller Chinese Sci-Fi novel for years since 2008. The book was translated into English by Ken Liu in 2014 and won the prestigious 2015 science fiction and fantasy writing Hugo Award, drawing greater attention from wider international communities. The story exposes the horrors of the Chinese Cultural Revolution in the 1960s, in an intriguing narrative for readers at home and abroad. However, without the access to the source text, western readers may not be aware that the original Chinese version of the book is rich in gender-bias. Some Chinese scholars have applied feminist translation theories to their analysis on this book before, based on isolated selected, cherry-picking examples. Thus this paper aims to obtain a more thorough picture of how translators can cope with gender discrimination and reshape the gendered discourse from the source text, by systematically investigating the lexical and syntactic patterns in the translation of Liu’s entire book of 400 pages. The source text and the translation were downloaded into digital files, automatically aligned at paragraph level and then manually post-edited. They were then compiled into a parallel corpus of 114,629 English words and 204,145 Chinese characters using Sketch Engine. Gender-discrimination markers such as the overuse of ‘girl’ to describe an adult woman were searched in the source text, and the alignment made it possible to identify the strategies adopted by the translator to mitigate gender discrimination. The results provide a framework for translators to address gender bias. The study also shows how corpus methods can be used to further research in feminist translation and critical discourse analysis.

Keywords: corpus, discourse analysis, feminist translation, science fiction translation

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Authors: Seedwell Sithole

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One of the persistent problems in accounting education is how to effectively support students’ learning. A promising technique to this issue is to investigate the extent that learning is determined by the design of instructional material. This study examines the academic performance of students using three instructional designs in financial accounting. Student’s performance scores and reported mental effort ratings were used to determine the instructional effectiveness. The findings of this study show that accounting students prefer graph and text designs that are integrated. The results suggest that spatially separated graph and text presentations in accounting should be reorganized to align with the requirements of human cognitive architecture.

Keywords: accounting, cognitive load, education, instructional preferences, students

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Authors: Jingjie Li, Wenjie Hu

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Phraseological units in academic English texts have been a central focus in recent corpus linguistic research. A wide variety of phraseological units have been explored, including collocations, chunks, lexical bundles, patterns, semantic sequences, etc. This paper describes a special category of clause-level phraseological units, namely, Characteristic Sentence Stems (CSSs), with a view to describing their defining criteria and extraction method. CSSs are contiguous lexico-grammatical sequences which contain a subject-predicate structure and which are frame expressions characteristic of academic writing. The extraction of CSSs consists of six steps: Part-of-speech tagging, n-gram segmentation, structure identification, significance of occurrence calculation, text range calculation, and overlapping sequence reduction. Significance of occurrence calculation is the crux of this study. It includes the computing of both the internal association and the boundary independence of a CSS and tests the occurring significance of the CSS from both inside and outside perspectives. A new normalization algorithm is also introduced into the calculation of LocalMaxs for reducing overlapping sequences. It is argued that many sentence stems are so recurrent in academic texts that the most typical of them have become the habitual ways of making meaning in academic writing. Therefore, studies of CSSs could have potential implications and reference value for academic discourse analysis, English for Academic Purposes (EAP) teaching and writing.

Keywords: characteristic sentence stem, extraction method, phraseological unit, the statistical measure

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Authors: García López

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The Government Departments of Health have the task of informing and educating citizens about public health issues. For this, they use channels like Twitter, key in the search for health information and the propagation of content. The tweets, important in the virality of the content, may contain emotions that influence the contagion and exchange of knowledge. The goal of this study is to perform an analysis of the emotional projection of health information shared on Twitter by official American accounts: the disease control account CDCgov, National Institutes of Health, NIH, the government agency HHSGov, and the professional organization PublicHealth. For this, we used Tone Analyzer, an International Business Machines Corporation (IBM) tool specialized in emotion detection in text, corresponding to the categorical model of emotion representation. For 15 days, all tweets from these accounts were analyzed with the emotional analysis tool in text. The results showed that their tweets contain an important emotional load, a determining factor in the success of their communications. This exposes that official accounts also use subjective language and contain emotions. The predominance of emotion joy over sadness and the strong presence of emotions in their tweets stimulate the virality of content, a key in the work of informing that government health departments have.

Keywords: emotions in tweets, emotion detection in the text, health information on Twitter, American health official accounts, emotions on Twitter, emotions and content

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Authors: Ganfeng Yu, Yuefeng Ma, Shanliang Yang

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The word discovery is a key problem in text information retrieval technology. Methods in new word discovery tend to be closely related to words because they generally obtain new word results by analyzing words. With the popularity of social networks, individual netizens and online self-media have generated various network texts for the convenience of online life, including network words that are far from standard Chinese expression. How detect network words is one of the important goals in the field of text information retrieval today. In this paper, we integrate the word embedding model and clustering methods to propose a network word discovery framework based on sentence semantic similarity (S³-NWD) to detect network words effectively from the corpus. This framework constructs sentence semantic vectors through a distributed representation model, uses the similarity of sentence semantic vectors to determine the semantic relationship between sentences, and finally realizes network word discovery by the meaning of semantic replacement between sentences. The experiment verifies that the framework not only completes the rapid discovery of network words but also realizes the standard word meaning of the discovery of network words, which reflects the effectiveness of our work.

Keywords: text information retrieval, natural language processing, new word discovery, information extraction

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Authors: Rita Chattopadhyay, Vivek Anand Thoutam

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Speech is the most acceptable means of communication where we can quickly exchange our feelings and thoughts. Quite often, people can communicate orally but cannot interact or work with computers or devices. It’s easy and quick to give speech commands than typing commands to computers. In the same way, it’s easy listening to audio played from a device than extract output from computers or devices. Especially with Robotics being an emerging market with applications in warehouses, the hospitality industry, consumer electronics, assistive technology, etc., speech-based human-machine interaction is emerging as a lucrative feature for robot manufacturers. Considering this factor, the objective of this paper is to design the “Audio-Visual Co-Data Processing Pipeline.” This pipeline is an integrated version of Automatic speech recognition, a Natural language model for text understanding, object detection, and text-to-speech modules. There are many Deep Learning models for each type of the modules mentioned above, but OpenVINO Model Zoo models are used because the OpenVINO toolkit covers both computer vision and non-computer vision workloads across Intel hardware and maximizes performance, and accelerates application development. A speech command is given as input that has information about target objects to be detected and start and end times to extract the required interval from the video. Speech is converted to text using the Automatic speech recognition QuartzNet model. The summary is extracted from text using a natural language model Generative Pre-Trained Transformer-3 (GPT-3). Based on the summary, essential frames from the video are extracted, and the You Only Look Once (YOLO) object detection model detects You Only Look Once (YOLO) objects on these extracted frames. Frame numbers that have target objects (specified objects in the speech command) are saved as text. Finally, this text (frame numbers) is converted to speech using text to speech model and will be played from the device. This project is developed for 80 You Only Look Once (YOLO) labels, and the user can extract frames based on only one or two target labels. This pipeline can be extended for more than two target labels easily by making appropriate changes in the object detection module. This project is developed for four different speech command formats by including sample examples in the prompt used by Generative Pre-Trained Transformer-3 (GPT-3) model. Based on user preference, one can come up with a new speech command format by including some examples of the respective format in the prompt used by the Generative Pre-Trained Transformer-3 (GPT-3) model. This pipeline can be used in many projects like human-machine interface, human-robot interaction, and surveillance through speech commands. All object detection projects can be upgraded using this pipeline so that one can give speech commands and output is played from the device.

Keywords: OpenVINO, automatic speech recognition, natural language processing, object detection, text to speech

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Authors: Ye Tian

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Soft power has replaced hard power and become one of the most attractive ways nations pursue to expand their international influence. One of the ways to improve a nation’s soft power is to commercialise the country and brand or rebrand it to the international audience, and thus attract interests or foreign investments. In this process, translation has often been regarded as merely a tool, and researches in it are either in translating literature as culture export or in how (in)accuracy of translation influences the branding campaign. This paper proposes to analyse nation branding campaign with framing theory, and thus gives an entry for translation studies to come to a central stage in today’s soft power research. To frame information or elements of a text, an event, or, as in this paper, a nation is to put them in a mental structure. This structure can be built by outsiders or by those who create the text, the event, or by citizens of the nation. To frame information like this can be regarded as a process of translation, as what translation does in its traditional meaning of ‘translating a text’ is to put a framework on the text to, deliberately or not, highlight some of the elements while hiding the others. In the discourse of nations, then, people unavoidably simplify a national image and put the nation into their imaginary framework. In this way, problems like stereotype and prejudice come into being. Meanwhile, if nations seek ways to frame or reframe themselves, they make efforts to have in control what and who they are in the eyes of international audiences, and thus make profits, economically or politically, from it. The paper takes African nations, which are usually perceived as a whole, and the United Kingdom as examples to justify passive and active framing process, and assesses both positive and negative influence framing has on nations. In conclusion, translation as framing causes problems like prejudice, and the image of a nation is not always in the hands of nation branders, but reframing the nation in a positive way has the potential to turn the tide.

Keywords: framing, nation branding, stereotype, translation

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Authors: Roni Ramon-Gonen, Amir Dori, Shahar Shelly

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Background and objectives: Healthcare professionals produce abundant textual information in their daily clinical practice. The extraction of insights from all the gathered information, mainly unstructured and lacking in normalization, is one of the major challenges in computational medicine. In this respect, text mining assembles different techniques to derive valuable insights from unstructured textual data, so it has led to being especially relevant in Medicine. Neurological patient’s history allows the clinician to define the patient’s symptoms and along with the result of the nerve conduction study (NCS) and electromyography (EMG) test, assists in formulating a differential diagnosis. Past medical history (PMH) helps to direct the latter. In this study, we aimed to identify relevant PMH, understand which PMHs are common among patients in the referral cohort and documented by the medical staff, and examine the differences by sex and age in a large cohort based on textual format notes. Methods: We retrospectively identified all patients with abnormal NCS between May 2016 to February 2022. Age, gender, and all NCS attributes reports were recorded, including the summary text. All patients’ histories were extracted from the text report by a query. Basic text cleansing and data preparation were performed, as well as lemmatization. Very popular words (like ‘left’ and ‘right’) were deleted. Several words were replaced with their abbreviations. A bag of words approach was used to perform the analyses. Different visualizations which are common in text analysis, were created to easily grasp the results. Results: We identified 5282 unique patients. Three thousand and five (57%) patients had documented PMH. Of which 60.4% (n=1817) were males. The total median age was 62 years (range 0.12 – 97.2 years), and the majority of patients (83%) presented after the age of forty years. The top two documented medical histories were diabetes mellitus (DM) and surgery. DM was observed in 16.3% of the patients, and surgery at 15.4%. Other frequent patient histories (among the top 20) were fracture, cancer (ca), motor vehicle accident (MVA), leg, lumbar, discopathy, back and carpal tunnel release (CTR). When separating the data by sex, we can see that DM and MVA are more frequent among males, while cancer and CTR are less frequent. On the other hand, the top medical history in females was surgery and, after that, DM. Other frequent histories among females are breast cancer, fractures, and CTR. In the younger population (ages 18 to 26), the frequent PMH were surgery, fractures, trauma, and MVA. Discussion: By applying text mining approaches to unstructured data, we were able to better understand which medical histories are more relevant in these circumstances and, in addition, gain additional insights regarding sex and age differences. These insights might help to collect epidemiological demographical data as well as raise new hypotheses. One limitation of this work is that each clinician might use different words or abbreviations to describe the same condition, and therefore using a coding system can be beneficial.

Keywords: abnormal studies, healthcare analytics, medical history, nerve conduction studies, text mining, textual analysis

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Authors: Ekaterina M. Myasnikova, Andrey A. Makashov, Alexander V. Spirov

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First manifestation of a segmentation pattern in the early Drosophila development is the formation of expression domains (along with the main embryo axis) of genes belonging to the trunk gene class. Highly variable expression of genes from gap family in early Drosophila embryo is strongly reduced by the start of gastrulation due to the gene cross-regulation. The dynamics of gene expression is described by a gene circuit model for a system of four gap genes. It is shown that for the formation of a steep and stationary border by the model it is necessary that there existed a nucleus (modeling point) in which the gene expression level is constant in time and hence is described by a stationary equation. All the rest genes expressed in this nucleus are in a dynamic equilibrium. The mechanism of border formation associated with the existence of a stationary nucleus is also confirmed by the experiment. An important advantage of this approach is that properties of the system in a stationary nucleus are described by algebraic equations and can be easily handled analytically. Thus we explicitly characterize the cross-regulation properties necessary for the robustness and formulate the conditions providing this effect through the properties of the initial input data. It is shown that our formally derived conditions are satisfied for the previously published model solutions.

Keywords: drosophila, gap genes, reaction-diffusion model, robustness

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Authors: J. Chow

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In laboratory settings, this study measured and reported the effects of undergraduate students watching animated videos on learning microeconomics as compared with the effectiveness of reading written texts. The study described an experiment on learning microeconomics in higher education using two different types of learning materials. It reported the effectiveness on microeconomics learning of watching animated videos and reading written texts. Undergraduate students in the university were randomly assigned to either a ‘video group’ or a ‘text group’ in the experiment. Previously-validated multiple-choice questions on fundamental concepts of microeconomics were administered. Both groups showed improvement between the pre-test and post-test. The experience of learning using text and video materials was also assessed. After controlling the student characteristics variables, the analyses showed that both types of materials showed comparable level of perceived learning experience. The effect size and statistical significance of these results supported the hypothesis that animated video is an effective alternative to text materials as a learning tool for students. The findings suggest that such animated videos may support teaching microeconomics in higher education.

Keywords: animated videos for education, laboratory experiment, microeconomics education, undergraduate economics education

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Authors: Alev Atak

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In this paper, we aim to create a financial sentiment index by investigating the company’s voluntary information disclosures. We retrieve structured content from BIST 100 companies’ financial reports for the period 1998-2018 and extract relevant financial information for sentiment analysis through Natural Language Processing. We measure strategy-related disclosures and their cross-sectional variation and classify report content into generic sections using synonym lists divided into four main categories according to their liquidity risk profile, risk positions, intra-annual information, and exposure to risk. We use Word Error Rate and Cosin Similarity for comparing and measuring text similarity and derivation in sets of texts. In addition to performing text extraction, we will provide a range of text analysis options, such as the readability metrics, word counts using pre-determined lists (e.g., forward-looking, uncertainty, tone, etc.), and comparison with reference corpus (word, parts of speech and semantic level). Therefore, we create an adequate analytical tool and a financial dictionary to depict the importance of granular financial disclosure for investors to identify correctly the risk-taking behavior and hence make the aggregated effects traceable.

Keywords: financial sentiment, machine learning, information disclosure, risk

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Authors: Yi-Ting Wang, Wen-Shu Lai

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The subject of this paper is the photography in the 1983 film Paris, Texas, directed by Wim Wenders. Wenders is well known as a film director as well as a photographer. We have found that photography is shown as a photographic element in many of his films. Some of these photographs serve as details within the films, while others play important roles that are relevant to the story. This paper aims to consider photographs in film as a specific type of text, which is the output of both still photography and the film itself. In the film Paris, Texas, three sets of important photographs appear whose symbolic meanings are as dialectical as their text types. The relationship between the existence of these photos and the storyline is both dependent and isolated. The film’s images fly by and progress into other images, while the photos in the film serve a unique narrative function by stopping the continuously flowing images thus provide the viewer a space for imagination and contemplation. They are more than just artistic forms; they also contained multiple meanings. The photographs in Paris, Texas play the role of both presence and absence according to their shifting meanings. There are references to their presence: photographs exist between film time and narrative time, so in terms of the interaction between the characters in the film, photographs are a common symbol of the beginning and end of the characters’ journeys. In terms of the audience, the film’s photographs are a link in the viewing frame structure, through which the creative motivation of the film director can be explored. Photographs also point to the absence of certain objects: the scenes in the photos represent an imaginary map of emotion. The town of Paris, Texas is therefore isolated from the physical presence of the photograph, and is far more abstract than the reality in the film. This paper embraces the ambiguous nature of photography and demonstrates its presence and absence in film with regard to the meaning of text. However, it is worth reflecting that the temporary nature of the interpretation of the film’s photographs is far greater than any other type of photographic text: the characteristics of the text cause the interpretation results to change along with the variations in the interpretation process, which makes their meaning a dynamic process. The photographs’ presence or absence in the context of Paris, Texas also demonstrates the presence and absence of the creator, time, the truth, and the imagination. The film becomes more complete as a result of the revelation of the photographs, while the intertextual connection between these two forms simultaneously provides multiple possibilities for the interpretation of the photographs in the film.

Keywords: film, Paris, Texas, photography, Wim Wenders

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Authors: Katharine Pollock

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Feminist scholars assert that a defining aspect of feminist confessional literature is that it expresses both an individual and communal identity, one which is predicated on the commonly-shared aspects of female experience. Reading feminist confessional literature in this way accommodates a plurality of readerly experiences and textual interpretations. It affirms the individual whilst acknowledging those experiences which bind women together, and refuses traditional objective criticism. It invites readers to see themselves reflected in the text, and encourages them to share their own stories. Similarly, music which communicates women’s personal experience, fictive or not, expresses a dual identity. There is an inherent risk of imposing a confessional reading upon a musical or literary text. Understanding music as being multivocal in the same way as confessional literature negates this patriarchal tendency, and allows listeners to engage with both the subjective and collective aspects of a text. By hearing their own stories reflected in the music, listeners engage in an ongoing dialogic process in which female stories are prioritised. This refuses patriarchal silencing and ensures a diversity of female voices. To demonstrate the veracity of these claims, literary criticism is applied to Lily Allen’s music, and memoir My Thoughts Exactly.

Keywords: confession, female, feminist, literature, music

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Authors: Charles-Olivier Amédée-Manesme, Benoit Faye, Eric Le Fur

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In this paper, the heterogeneity of the Bordeaux Legends 50 wine market price segment is addressed. For this purpose, quantile regression is applied – with market segmentation based on wine bottle price quantile – and the hedonic price of wine attributes is computed for various price segments of the market. The approach is applied to a major privately held data set which consists of approximately 30,000 transactions over the 2003–2014 period. The findings suggest that the relative hedonic prices of several wine attributes differ significantly among deciles. In particular, the elasticity coefficient of the expert ratings shows strong variation among prices. If - as suggested in the literature - expert ratings have a positive influence on wine price on average, they have a clearly decreasing impact over the quantiles. Finally, the lower the wine price, the higher the potential for price appreciation over time. Other variables such as chateaux or vintage are also shown to vary across the distribution of wine prices. While enhancing our understanding of the complex market dynamics that underlie Bordeaux wines’ price, this research provides empirical evidence that the QR approach adequately captures heterogeneity among wine price ranges, which simultaneously applies to wine stock, vintage and auctions’ house.

Keywords: hedonics, market segmentation, quantile regression, heterogeneity, wine economics

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Authors: Bensaid A., Mostephaoui T., Nedjai R.

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A considerable area of Algerian lands are threatened by the phenomenon of wind erosion. For a long time, wind erosion and its associated harmful effects on the natural environment have posed a serious threat, especially in the arid regions of the country. In recent years, as a result of increases in the irrational exploitation of natural resources (fodder) and extensive land clearing, wind erosion has particularly accentuated. The extent of degradation in the arid region of the Algerian Mécheriadepartment generated a new situation characterized by the reduction of vegetation cover, the decrease of land productivity, as well as sand encroachment on urban development zones. In this study, we attempt to investigate the potential of remote sensing and geographic information systems for detecting the spatial dynamics of the ancient dune cords based on the numerical processing of PlanetScope PSB.SB sensors images by September 29, 2021. As a second step, we prospect the use of a multi-scale geographic object-based image analysis (GEOBIA) approach to segment the high spatial resolution images acquired on heterogeneous surfaces that vary according to human influence on the environment. We have used the fractal net evolution approach (FNEA) algorithm to segment images (Baatz&Schäpe, 2000). Multispectral data, a digital terrain model layer, ground truth data, a normalized difference vegetation index (NDVI) layer, and a first-order texture (entropy) layer were used to segment the multispectral images at three segmentation scales, with an emphasis on accurately delineating the boundaries and components of the sand accumulation areas (Dune, dunes fields, nebka, and barkhane). It is important to note that each auxiliary data contributed to improve the segmentation at different scales. The silted areas were classified using a nearest neighbor approach over the Naâma area using imagery. The classification of silted areas was successfully achieved over all study areas with an accuracy greater than 85%, although the results suggest that, overall, a higher degree of landscape heterogeneity may have a negative effect on segmentation and classification. Some areas suffered from the greatest over-segmentation and lowest mapping accuracy (Kappa: 0.79), which was partially attributed to confounding a greater proportion of mixed siltation classes from both sandy areas and bare ground patches. This research has demonstrated a technique based on very high-resolution images for mapping sanded and degraded areas using GEOBIA, which can be applied to the study of other lands in the steppe areas of the northern countries of the African continent.

Keywords: land development, GIS, sand dunes, segmentation, remote sensing

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Authors: Sumaira Mukhtar

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The present research aims at the discussion of the subversion of the hegemony of the feminine self in the text Moth Smoke by a Pakistani novelist Mohsin Hamid. It presents the notion of the subversion of the grand narratives of the ‘positioning’ of feminine identity in Pakistani patriarchal society by presenting a de-stereotyped personality of Mumtaz, the protagonist in Moth Smoke. The dominant masculine traits in Mumtaz’s personality have been negotiated since she is an untraditional female character in the novel. In this regard, the researcher has taken a feministic stance in this study by presenting the proposition that subaltern can also speak. Mumtaz’s character reminds one of Hedda from Henrik Ibsen’s play Hedda Gabler. So, the masculine traits in Mumtaz’s personality have also been compared with Hedda’s. Besides, the research study will also bring into notice that how that in the postmodern scenario, marginalization of the women have been responded back by women and hereby Mumtaz by uplifting her social status and class. Her de-stereotyped feminine self has been reinforced by the dialogues and incidents in the text. This research is qualitative in design and is based on the textual analysis. An interpretive research method has also been utilized since the researcher has tried to decode the text in supporting the notion of de-stereotyping of feminine self. This research would add to the body of Pakistani literature and Feministic theory.

Keywords: de-stereotyped, feminine identity, marginalization, masculine traits

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Authors: Neneng Hayatul Milah

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The most important reading skill for students is comprehension. Understanding the reading text will have an impact on learning outcomes. However, reading comprehension instruction in Indonesian elementary schools is lacking. A more effective learning model is needed to enhance students' reading comprehension. This study aimed to evaluate the effectiveness of the CIRC (Cooperative Integrated Reading and Composition) model with Padlet integration in improving the reading comprehension skills of grade IV students in elementary schools in Cimahi City, Indonesia. This research methodology was quantitative with a pre-experiment research type and one group pretest-posttest research design. The sample of this study consisted of 30 students. The results of statistical analysis showed that there was a significant effect of using the CIRC learning model using Padlet on improving students' reading comprehension skills of narrative text. The mean score of students' pretest was 67.41, while the mean score of the posttest increased to 84.82. The paired sample t-test resulted in a t-count score of -13.706 with a significance score of <0.001, which is smaller than α = 0.05. This research is expected to provide useful insights for educational practitioners on how the use of the CIRC model using Padlet can improve the reading comprehension skills of elementary school students.

Keywords: reading comprehension skills, CIRC, Padlet, narrative text

Procedia PDF Downloads 36