Search results for: multimodal text

Authors: Taurino S. R. Neto, Epitácio D. S. Neto, Flávio Signorelli, Gustavo G. M. Balbi, Alex H. Higashi, Mário Luiz R. Monteiro, Eloisa Bonfá, Danieli C. O. Andrade, Leandro C. Zacharias

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Purpose: To perform a multimodal evaluation, including the use of Optical Coherence Angiotomography (OCTA), in patients with primary antiphospholipid syndrome (PAPS) without ocular complaints and to compare them with healthy individuals. Methods: A complete structural and functional ophthalmological evaluation using OCTA and microperimetry (MP) exam in patients with PAPS, followed at a tertiary rheumatology outpatient clinic, was performed. All ophthalmologic manifestations were recorded and then statistical analysis was performed for comparative purposes; p <0.05 was considered statistically significant. Results: 104 eyes of 52 subjects (26 patients with PAPS without ocular complaints and 26 healthy individuals) were included. Among PAPS patients, 21 were female (80.8%) and 21 (80.8%) were Caucasians. Thrombotic PAPS was the main clinical criteria manifestation (100%); 65.4% had venous and 34.6% had arterial thrombosis. Obstetrical criteria were present in 34.6% of all thrombotic PAPS patients. Lupus anticoagulant was present in all patients. 19.2% of PAPS patients presented ophthalmologic findings against none of the healthy individuals. The most common retinal change was paracentral acute middle maculopathy (PAMM) (3 patients, 5 eyes), followed by drusen-like deposits (1 patient, 2 eyes) and pachychoroid pigment epitheliopathy (1 patient, 1 eye). Systemic hypertension and hyperlipidaemia were present in 100% of the PAPS patients with PAMM, while only six patients (26.1%) with PAPS without PAMM presented these two risk factors together. In the quantitative OCTA evaluation, we found significant differences between PAPS patients and controls in both the superficial vascular complex (SVC) and deep vascular complex (DVC) in the high-speed protocol, as well as in the SVC in the high-resolution protocol. In the analysis of the foveal avascular zone (FAZ) parameters, the PAPS group had a larger area of FAZ in the DVC using the high-speed method compared to the control group (p=0.047). In the quantitative analysis of the MP, the PAPS group had lower central (p=0.041) and global (p<0.001) retinal sensitivity compared to the control group, as well as in the sector analysis, with the exception of the inferior sector. In the quantitative evaluation of fixation stability, there was a trend towards worse stability in the PAPS subgroup with PAMM in both studied methods. Conclusions: PAMM was observed in 11.5% of PAPS patients with no previous ocular complaints. Systemic hypertension concomitant with hyperlipidemia was the most commonly associated risk factor for PAMM in patients with PAPS. PAPS patients present lower vascular density and retinal sensitivity compared to the control group, even in patients without PAMM.

Keywords: antiphospholipid syndrome, optical coherence angio tomography, optical coherence tomography, retina

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Authors: Pedro G. Rodrigues, Maria J. Bárrios, Sara A. Ambrósio

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The digitalisation of health is a profoundly transformative economic, political, and social process. As is often the case, such processes need to be carefully managed if misunderstandings, policy misalignments, or outright conflicts between the government and a wide gamut of stakeholders with competing interests are to be avoided. Thus, ensuring open lines of communication where all parties know what each other’s concerns are is key to good governance, as well as efficient and effective policymaking. This project aims to make a small but still significant contribution in this regard in that we seek to determine the extent to which health managers’ perceptions of what is a priority for digital health in Portugal are aligned with official policy perspectives. By applying state-of-the-art artificial intelligence technology first to the indexed literature on digital health and then to a set of official policy documents on the same topic, followed by a survey directed at health managers working in public and private hospitals in Portugal, we obtain two priority rankings that, when compared, will allow us to produce a synthesis and toolkit on digital health policy in Portugal, with a view to identifying areas of policy convergence and divergence. This project is also particularly peculiar in the sense that sophisticated digital methods related to text analytics are employed to study good governance aspects of digitalisation applied to health care.

Keywords: digital health, health informatics, text analytics, governance, natural language understanding

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Authors: Kim Haekyoung, Au Yunkyoung

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As digital technology continues to advance and become more widely accessible, young children are also growing up experiencing various media from infancy. In this changing environment, educating young children on media literacy has become an increasingly important task. With the diversification of media, it has become more necessary for children to understand, utilize, and critically explore the meaning of multimodal texts, which include text, images, and sounds connected to each other. Early childhood is a period when media literacy can bloom, and educational and policy support are needed to enable young children to express their opinions, communicate, and participate fully. However, most current media literacy education for young children focuses solely on teaching how to use media, with limited practical application and utilization. Therefore, this study aims to develop an inquiry-based media literacy education program for young children using topic-specific media content and explore the program's potential and impact on children's media literacy learning. Based on a theoretical and literature review on media literacy education, analysis of existing educational programs, and a survey on the current status and teacher perception of media literacy education for young children, this study developed a media literacy education program for young children considering the components of media literacy (understanding media characteristics, self-regulation, self-expression, critical understanding, ethical norms, social communication). To verify the effectiveness of the program, it was implemented with 20 five-year-old children from C City S Kindergarten, starting from March 24 to May 26, 2022, once a week for a total of 6 sessions. To explore quantitative changes before and after program implementation, repeated-measures analysis of variance was conducted, and qualitative analysis was used to analyze observed changes in the process. significant improvement in media literacy levels, such as understanding media characteristics, self-regulation, self-expression, critical understanding, ethical norms, and social communication. The developed inquiry-based media literacy education program for young children in this study can be effectively applied to enhance children's media literacy education and help improve their media literacy levels. Observed changes in the process also confirmed that children improved their ability to learn various topics, express their thoughts, and communicate with others using media content. These findings emphasize the importance of developing and implementing media literacy education programs and can help children develop the ability to safely and effectively use media in their media environment. Based on exploring the potential and impact of the inquiry-based media literacy education program for young children, this study confirmed positive changes in children's media literacy levels as a result of the program's implementation. These findings suggest that beyond education on how to use media, it can help develop children's ability to safely and effectively use media in their media environment. Furthermore, to improve children's media literacy levels and create a safe media environment, a variety of content and methodologies are needed, and continuous development and evaluation of educational programs are anticipated.

Keywords: young children, media literacy, media literacy education program, media content

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Authors: Guadalupe López-Bonilla

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Students of all educational levels participate in literacy practices that may involve print or digital media. Scholars from the New Literacy Studies distinguish practices that fulfill institutional purposes such as those established at schools from literate practices aimed at doing other kinds of activities, such as reading instructions in order to play a video game; the first are known as institutional practices while the latter are considered vernacular literacies. When students perform these kinds of activities they engage with print and digital media according to the demands of the task. In this paper, it is aimed to discuss the results of a research project focusing on literacy practices of high school students at 10 urban cybercafés in Mexico. The main objective was to analyze the literacy practices of students performing both school tasks and vernacular literacies. The methodology included a focused ethnography with online and face to face observations of 10 high school students (5 male and 5 female) and interviews after performing each task. In the results, it is presented how students treat texts as open, dynamic and relational artifacts when engaging in vernacular literacies; while texts are conceived as closed, authoritarian and fixed documents when performing school activities. Samples of each type of activity are shown followed by a discussion of the pedagogical implications for improving school literacy.

Keywords: digital literacy, text, school literacy, vernacular practices

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Authors: Kyi Pyar Zaw, Zin Mar Kyu

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Character recognition is the process of converting a text image file into editable and searchable text file. Feature Extraction is the heart of any character recognition system. The character recognition rate may be low or high depending on the extracted features. In the proposed paper, 25 features for one character are used in character recognition. Basically, there are three steps of character recognition such as character segmentation, feature extraction and classification. In segmentation step, horizontal cropping method is used for line segmentation and vertical cropping method is used for character segmentation. In the Feature extraction step, features are extracted in two ways. The first way is that the 8 features are extracted from the entire input character using eight direction chain code frequency extraction. The second way is that the input character is divided into 16 blocks. For each block, although 8 feature values are obtained through eight-direction chain code frequency extraction method, we define the sum of these 8 feature values as a feature for one block. Therefore, 16 features are extracted from that 16 blocks in the second way. We use the number of holes feature to cluster the similar characters. We can recognize the almost Myanmar common characters with various font sizes by using these features. All these 25 features are used in both training part and testing part. In the classification step, the characters are classified by matching the all features of input character with already trained features of characters.

Keywords: chain code frequency, character recognition, feature extraction, features matching, segmentation

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Authors: Natalia Kasatkina

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In an ever-increasing globalization, one’s grasp of diversity and tolerance has never been more indispensable, and it is a vital duty for all those in the field of foreign language teaching to help children cultivate such values. The present study explores the role of DIVERSITY and TOLERANCE in the language classroom and elementary, middle, and high school students’ perceptions of these two concepts. It draws on several theoretical domains of language acquisition, cultural awareness, and school psychology. Relying on these frameworks, the major findings are synthesized, and a paradigm of teaching tolerance through language-teaching is formulated. Upon analysing how tolerant our children are with ‘others’ in and outside the classroom, we have concluded that intolerance and aggression towards the ‘other’ increase with age, and that a feeling of supremacy over migrants and a sense of fear towards them begin to manifest more apparently when the students are in high school. In addition, we have also found that children in elementary school do not exhibit such prejudiced thoughts and behavior, which leads us to the believe that tolerance as well as intolerance are learned. Therefore, it is within our reach to teach our children to be open-minded and accepting. We have used the novel ‘Uncle Tom’s Cabin’ by Harriet Beecher Stowe as a springboard for lessons which are not only targeted at shedding light on the role of language in the modern world, but also aim to stimulate an awareness of cultural diversity. We equally strive to conduct further cross-cultural research in order to solidify the theory behind this study, and thus devise a language-based curriculum which would encourage tolerance through the examination of various literary texts.

Keywords: literary text, tolerance, EFL classroom, word-association test

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Authors: Gałka Aleksandra, Jelińska Justyna, Masiak Albert, Walentukiewicz Krzysztof

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An offline signature is well-known however not the safest way to verify identity. Nowadays, to ensure proper authentication, i.e. in banking systems, multimodal verification is more widely used. In this paper the online signature analysis based on dynamic time warping (DTW) coupled with machine learning approaches has been presented. In our research signatures made with biometric pens were gathered. Signature features as well as their forgeries have been described. For verification of authenticity various methods were used including convolutional neural networks using DTW matrix and multilayer perceptron using sums of DTW matrix paths. System efficiency has been evaluated on signatures and signature forgeries collected on the same day. Results are presented and discussed in this paper.

Keywords: dynamic time warping, handwritten signature verification, feature-based recognition, online signature

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Authors: Christiane Paulus

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Post-Islamism assumes that the Quran should not be viewed in terms of what Lyotard identifies as a ‘meta-narrative'. However, its socio-ethical content can be viewed as critical of power discourse (Foucault). Practicing religion seems to be limited to rites and individual spirituality, taqwa. Alternatively, can we build on Muhammad Abduh's classic-modern reform and develop it through a postmodernist frame? This is the main question of this study. Through his general and vague remarks on the context of the Quran, Abduh was the first to refer to the historical and cultural distance of the text as an obstacle for interpretation. His application, however, corresponded to the modern absolute idea of authentic sharia. He was followed by Amin al-Khuli, who hermeneutically linked the content of the Quran to the theory of evolution. Fazlur Rahman and Nasr Hamid abu Zeid remain reluctant to go beyond the general level in terms of context. The hermeneutic circle, therefore, persists in challenging, how to get out to overcome one’s own assumptions. The insight into and the acceptance of the lasting ambivalence of understanding can be grasped as a postmodern approach; it is documented in Derrida's discovery of the shift in text meanings, difference, also in Lyotard's theory of différend. The resulting mixture of meanings (Wolfgang Welsch) can be read together with the classic ambiguity of the premodern interpreters of the Quran (Thomas Bauer). Confronting hermeneutic difficulties in general, Niklas Luhmann proves every description an attribution, tautology, i.e., remaining in the circle. ‘De-tautologization’ is possible, namely by analyzing the distinctions in the sense of objective, temporal and social information that every text contains. This could be expanded with the Kantian aesthetic dimension of reason (critique of pure judgment) corresponding to the iʽgaz of the Coran. Luhmann asks, ‘What distinction does the observer/author make?’ Quran as a speech from God to the first listeners could be seen as a discourse responding to the problems of everyday life of that time, which can be viewed as the general goal of the entire Qoran. Through reconstructing koranic Lifeworlds (Alfred Schütz) in detail, the social structure crystallizes the socio-economic differences, the enormous poverty. The koranic instruction to provide the basic needs for the neglected groups, which often intersect (old, poor, slaves, women, children), can be seen immediately in the text. First, the references to lifeworlds/social problems and discourses in longer koranic passages should be hypothesized. Subsequently, information from the classic commentaries could be extracted, the classical Tafseer, in particular, contains rich narrative material for reconstructing. By selecting and assigning suitable, specific context information, the meaning of the description becomes condensed (Clifford Geertz). In this manner, the text gets necessarily an alienation and is newly accessible. The socio-ethical implications can thus be grasped from the difference of the original problem and the revealed/improved order/procedure; this small step can be materialized as such, not as an absolute solution but as offering plausible patterns for today’s challenges as the Agenda 2030.

Keywords: postmodern hermeneutics, condensed description, sociological approach, small steps of reform

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Authors: Vaidehi Murarka, Sneha Mehta, Dishant Upadhyay

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Our project topic is “Alphabet Recognition using pixel probability distribution”. The project uses techniques of Image Processing and Machine Learning in Computer Vision. Alphabet recognition is the mechanical or electronic translation of scanned images of handwritten, typewritten or printed text into machine-encoded text. It is widely used to convert books and documents into electronic files etc. Alphabet Recognition based OCR application is sometimes used in signature recognition which is used in bank and other high security buildings. One of the popular mobile applications includes reading a visiting card and directly storing it to the contacts. OCR's are known to be used in radar systems for reading speeders license plates and lots of other things. The implementation of our project has been done using Visual Studio and Open CV (Open Source Computer Vision). Our algorithm is based on Neural Networks (machine learning). The project was implemented in three modules: (1) Training: This module aims “Database Generation”. Database was generated using two methods: (a) Run-time generation included database generation at compilation time using inbuilt fonts of OpenCV library. Human intervention is not necessary for generating this database. (b) Contour–detection: ‘jpeg’ template containing different fonts of an alphabet is converted to the weighted matrix using specialized functions (contour detection and blob detection) of OpenCV. The main advantage of this type of database generation is that the algorithm becomes self-learning and the final database requires little memory to be stored (119kb precisely). (2) Preprocessing: Input image is pre-processed using image processing concepts such as adaptive thresholding, binarizing, dilating etc. and is made ready for segmentation. “Segmentation” includes extraction of lines, words, and letters from the processed text image. (3) Testing and prediction: The extracted letters are classified and predicted using the neural networks algorithm. The algorithm recognizes an alphabet based on certain mathematical parameters calculated using the database and weight matrix of the segmented image.

Keywords: contour-detection, neural networks, pre-processing, recognition coefficient, runtime-template generation, segmentation, weight matrix

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Authors: Yunseok Noh, Chang-Uk Kwak, Sun-Joong Kim, Seong-Bae Park

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Scripts are one of the basic text resources to understand broadcasting contents. Since broadcast media wields lots of influence over the public, tools for understanding broadcasting contents are more required. Topic modeling is the method to get the summary of the broadcasting contents from its scripts. Generally, scripts represent contents descriptively with directions and speeches. Scripts also provide scene segments that can be seen as semantic units. Therefore, a script can be topic modeled by treating a scene segment as a document. Because scripts consist of speeches mainly, however, relatively small co-occurrences among words in the scene segments are observed. This causes inevitably the bad quality of topics based on statistical learning method. To tackle this problem, we propose a method of learning with additional word co-occurrence information obtained using scene similarities. The main idea of improving topic quality is that the information that two or more texts are topically related can be useful to learn high quality of topics. In addition, by using high quality of topics, we can get information more accurate whether two texts are related or not. In this paper, we regard two scene segments are related if their topical similarity is high enough. We also consider that words are co-occurred if they are in topically related scene segments together. In the experiments, we showed the proposed method generates a higher quality of topics from Korean drama scripts than the baselines.

Keywords: broadcasting contents, scripts, text similarity, topic model

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Authors: M. T. Artese, G. Ciocca, I. Gagliardi

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Food is a social and cultural aspect of every individual. Food products, processing, and traditions have been identified as cultural objects carrying history and identity of social groups. Traditional recipes are passed down from one generation to the other, often to strengthen the link with the territory. The paper presents CookIT, a web portal developed to collect Italian traditional recipes related to regional cuisine, with the purpose to disseminate the knowledge of typical Italian recipes and the Mediterranean diet which is a significant part of Italian cuisine. The system designed is completed with multimodal means of browsing and data retrieval. Stored recipes can be retrieved integrating and combining a number of different methods and keys, while the results are displayed using classical styles, such as list and mosaic, and also using maps and graphs, with which users can play using available keys for interaction.

Keywords: collaborative portal, Italian cuisine, intangible cultural heritage, traditional recipes, searching and browsing

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Authors: Matthew Baucum

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With the increasing popularity of fMRI as an experimental method, psychology and neuroscience can greatly benefit from advanced techniques for summarizing and synthesizing large amounts of data from brain imaging studies. One promising avenue is automated meta-analyses, in which natural language processing methods are used to identify the brain regions consistently associated with certain semantic concepts (e.g. “social”, “reward’) across large corpora of studies. This study builds on this approach by demonstrating how, in fMRI meta-analyses, individual voxels can be treated as vectors in a semantic space and evaluated for their “proximity” to terms of interest. In this technique, a low-dimensional semantic space is built from brain imaging study texts, allowing words in each text to be represented as vectors (where words that frequently appear together are near each other in the semantic space). Consequently, each voxel in a brain mask can be represented as a normalized vector sum of all of the words in the studies that showed activation in that voxel. The entire brain mask can then be visualized in terms of each voxel’s proximity to a given term of interest (e.g., “vision”, “decision making”) or collection of terms (e.g., “theory of mind”, “social”, “agent”), as measured by the cosine similarity between the voxel’s vector and the term vector (or the average of multiple term vectors). Analysis can also proceed in the opposite direction, allowing word cloud visualizations of the nearest semantic neighbors for a given brain region. This approach allows for continuous, fine-grained metrics of voxel-term associations, and relies on state-of-the-art “open vocabulary” methods that go beyond mere word-counts. An analysis of over 11,000 neuroimaging studies from an existing meta-analytic fMRI database demonstrates that this technique can be used to recover known neural bases for multiple psychological functions, suggesting this method’s utility for efficient, high-level meta-analyses of localized brain function. While automated text analytic methods are no replacement for deliberate, manual meta-analyses, they seem to show promise for the efficient aggregation of large bodies of scientific knowledge, at least on a relatively general level.

Keywords: FMRI, machine learning, meta-analysis, text analysis

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Authors: Amany ElShazly, Lubna A. Sherif

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The entanglement of humans with the environment has always been inevitable and often causes destruction. In this respect, ‘Ecolinguistics’ helps humans to understand the link between languages and the environment. Stibbe (2014a) has indicated that ‘linguistics’, particularly, Critical Discourse Studies (CDS), provides an interpretation of language which shapes world views, while the ‘eco’ side maintains the life-sustaining interactions of humans and the physical environment. This paper considers two key ecological instances, namely: The Grand Ethiopian Renaissance Dam (GERD) as a focal point of political dispute and THE LINE project as well as Etthadar lel Akhdar (Go Green Initiative) as two examples of combating ecological degradation. ‘Ecosophy’ as explained by Naess (1996) is used to describe the ecolinguistic framework, which assesses discourse where the linguistic lens focuses on the use of metaphor, and ‘Positive Discourse’ framework, which resonates with respect and care for the natural world.

Keywords: ecosophy, critical discourse studies, metaphor, positive discourse, social semiotics, ecolinguistics

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Authors: Benedicta Asante, Brenna Bath, Olugbenga Adebayo, Catherine Trask

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Background: Waste Collection Workers’ (WCWs) activities contribute greatly to the recycling sector and are an important component of the waste management industry. As the recycling sector evolves, reports of injuries and fatal accidents in the industry demand notice particularly common and debilitating musculoskeletal disorders such as low back pain (LBP). WCWs are likely exposed to diverse work-related hazards that could contribute to LBP. However, to our knowledge there has never been a systematic review or other synthesis of LBP findings within this workforce. The aim of this systematic review was to determine the prevalence and risk factors of LBP among WCWs. Method: A comprehensive search was conducted in Ovid Medline, EMBASE, and Global Health e-publications with search term categories ‘low back pain’ and ‘waste collection workers’. Articles were screened at title, abstract, and full-text stages by two reviewers. Data were extracted on study design, sampling strategy, socio-demographic, geographical region, and exposure definition, definition of LBP, risk factors, response rate, statistical techniques, and LBP prevalence. Risk of bias (ROB) was assessed based on Hoy Damien’s ROB scale. Results: The search of three databases generated 79 studies. Thirty-two studies met the study inclusion criteria for both title and abstract; thirteen full-text articles met the study criteria at the full-text stage. Seven articles (54%) reported prevalence within 12 months of LBP between 42-82% among WCW. The major risk factors for LBP among WCW included: awkward posture; lifting; pulling; pushing; repetitive motions; work duration; and physical loads. Summary data and syntheses of findings was presented in trend-lines and tables to establish the several prevalence periods based on age and region distribution. Public health implications: LBP is a major occupational hazard among WCWs. In light of these risks and future growth in this industry, further research should focus on more detail ergonomic exposure assessment and LBP prevention efforts.

Keywords: low back pain, scavenger, waste collection workers, waste pickers

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Authors: Josiel Delgadillo, Johnson Kinyua, Charles Mutigwe

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The purpose of sentiment analysis is to determine the sentiment strength (e.g., positive, negative, neutral) from a textual source for good decision-making. Natural language processing in domains such as financial markets requires knowledge of domain ontology, and pre-trained language models, such as BERT, have made significant breakthroughs in various NLP tasks by training on large-scale un-labeled generic corpora such as Wikipedia. However, sentiment analysis is a strong domain-dependent task. The rapid growth of social media has given users a platform to share their experiences and views about products, services, and processes, including financial markets. StockTwits and Twitter are social networks that allow the public to express their sentiments in real time. Hence, leveraging the success of unsupervised pre-training and a large amount of financial text available on social media platforms could potentially benefit a wide range of financial applications. This work is focused on sentiment analysis using social media text on platforms such as StockTwits and Twitter. To meet this need, SkyBERT, a domain-specific language model pre-trained and fine-tuned on financial corpora, has been developed. The results show that SkyBERT outperforms current state-of-the-art models in financial sentiment analysis. Extensive experimental results demonstrate the effectiveness and robustness of SkyBERT.

Keywords: BERT, financial markets, Twitter, sentiment analysis

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Authors: Holly A. Rick, Melissa McCartney

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The role of faculty has changed from the impact of Covid-19. Universities are changing faculty expectations. There is a changes in faculty workloads, and shift in how faculty work within a university. The research will identify areas where faculty are satisfied with their work, areas they would like their organizations to change, and how the faculty life is impacted by outside university obligations. A survey to obtain work-life balance, teaching responsibilities, and how a faculty’s personal life impacts their ability to work at their organization was conducted. The results of this research will identify areas where faculty have opportunities to engage in teaching, to balance their work life, and where organizations can change to support their faculty. Different ways of teaching including hyflex and other multimodal models will allow for faculty to engage in their teaching practice, professional development, and begin to establish work-life balance activities.

Keywords: faculty engagement, faculty responsibilities, HyFlex, teaching, work-life balance

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Authors: Renukswamy Chikkamath, Vishvapalsinhji Ramsinh Parmar, Christoph Hewel, Markus Endres

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Given a patent document, identifying distinct semantic annotations is an interesting research aspect. Text annotation helps the patent practitioners such as examiners and patent attorneys to quickly identify the key arguments of any invention, successively providing a timely marking of a patent text. In the process of manual patent analysis, to attain better readability, recognising the semantic information by marking paragraphs is in practice. This semantic annotation process is laborious and time-consuming. To alleviate such a problem, we proposed a dataset to train machine learning algorithms to automate the highlighting process. The contributions of this work are: i) we developed a multi-class dataset of size 150k samples by traversing USPTO patents over a decade, ii) articulated statistics and distributions of data using imperative exploratory data analysis, iii) baseline Machine Learning models are developed to utilize the dataset to address patent paragraph highlighting task, and iv) future path to extend this work using Deep Learning and domain-specific pre-trained language models to develop a tool to highlight is provided. This work assists patent practitioners in highlighting semantic information automatically and aids in creating a sustainable and efficient patent analysis using the aptitude of machine learning.

Keywords: machine learning, patents, patent sentiment analysis, patent information retrieval

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Authors: Kyung Bae Park, Sung Ho Ha

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Online user-generated contents (UGC) significantly change the way customers behave (e.g., shop, travel), and a pressing need to handle the overwhelmingly plethora amount of various UGC is one of the paramount issues for management. However, a current approach (e.g., sentiment analysis) is often ineffective for leveraging textual information to detect the problems or issues that a certain management suffers from. In this paper, we employ text mining of Latent Dirichlet Allocation (LDA) on a popular online review site dedicated to complaint from users. We find that the employed LDA efficiently detects customer complaints, and a further inspection with the visualization technique is effective to categorize the problems or issues. As such, management can identify the issues at stake and prioritize them accordingly in a timely manner given the limited amount of resources. The findings provide managerial insights into how analytics on social media can help maintain and improve their reputation management. Our interdisciplinary approach also highlights several insights by applying machine learning techniques in marketing research domain. On a broader technical note, this paper illustrates the details of how to implement LDA in R program from a beginning (data collection in R) to an end (LDA analysis in R) since the instruction is still largely undocumented. In this regard, it will help lower the boundary for interdisciplinary researcher to conduct related research.

Keywords: latent dirichlet allocation, R program, text mining, topic model, user generated contents, visualization

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Authors: Gintaras Mitrulevičius

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This text, which is based on the conference report, seeks to briefly examine the relationship between the concepts of social democracy and democratic socialism, drawing attention to the essential aspects of its development and, in particular, discussing the contradictions in the relationship between these concepts in the modern period. In the preparation of this text, such research methods as historical, historical-comparative methods were used, as well as methods of analyzing, synthesizing, and generalizing texts. The history of the use of terms in social democracy and democratic socialism shows that these terms were used alternately and almost synonymously. At the end of the 20th century, traditional social democracy was transformed into the so-called "new social democracy." Many of the new social democrats do not consider themselves democratic socialists and avoid the historically characteristic identification of social democracy with democratic socialism. It has become quite popular to believe that social democracy is a separate ideology from democratic socialism. Or that it has become a variant of the ideology of liberalism. This is a testimony to the crisis of ideological self-awareness of social democracy. Since the beginning of the 21st century, social democracy has also experienced a growing crisis of electoral support. This, among other things, led to her slight shift to the left. In this context, some social democrats are once again talking about democratic socialism. The rise of the ideas of democratic socialism in the United States was catalyzed by Bernie Sanders. But the proponents of democratic socialism in the United States have different concepts of democratic socialism. In modern Europe, democratic socialism is also spoken of by leftists of non-social democratic origin, whose understanding is different from that of democratic socialism inherent in classical social democracy. Some political scientists also single out the concepts in question. Analysis of the problem shows that there are currently several concepts of democratic socialism on the spectrum of the political left, both social-democratic and non-social-democratic.

Keywords: democratic socializm, socializm, social democracy, new social democracy, political ideologies

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Authors: Seval Kula-Kartal

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Developing students’ reading comprehension skills is an aim that is difficult to accomplish and requires to follow long-term and systematic teaching and assessment processes. In these processes, teachers need tools to provide guidance to them on what reading comprehension is and which comprehension skills they should develop. Due to a lack of clear and evidence-based frameworks defining reading comprehension skills, especially in Turkiye, teachers and students mostly follow various processes in the classrooms without having an idea about what their comprehension goals are and what those goals mean. Since teachers and students do not have a clear view of comprehension targets, strengths, and weaknesses in students’ comprehension skills, the formative feedback processes cannot be managed in an effective way. It is believed that detecting and defining influential comprehension skills may provide guidance both to teachers and students during the feedback process. Therefore, in the current study, some of the reading comprehension frameworks that define comprehension skills operationally were examined. The aim of the study is to develop a simple and clear framework that can be used by teachers and students during their teaching, learning, assessment, and feedback processes. The current study is qualitative research in which documents related to reading comprehension skills were analyzed. Therefore, the study group consisted of recourses and frameworks which made big contributions to theoretical and operational definitions of reading comprehension. A content analysis was conducted on the resources included in the study group. To determine the validity of the themes and sub-categories revealed as the result of content analysis, three educational assessment experts were asked to examine the content analysis results. The Fleiss’ Cappa coefficient revealed that there is consistency among themes and categories defined by three different experts. The content analysis of the reading comprehension frameworks revealed that comprehension skills could be examined under four different themes. The first and second themes focus on understanding information given explicitly or implicitly within a text. The third theme includes skills used by the readers to make connections between their personal knowledge and the information given in the text. Lastly, the fourth theme focus on skills used by readers to examine the text with a critical view. The results suggested that fundamental reading comprehension skills can be examined under four themes. Teachers are recommended to use these themes in their reading comprehension teaching and assessment processes. Acknowledgment: This research is supported by Pamukkale University Scientific Research Unit within the project, whose title is Developing A Reading Comprehension Rubric.

Keywords: reading comprehension, assessing reading comprehension, comprehension taxonomies, educational assessment

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Authors: K. Senthil Nathan, P. Rajasekaran

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Fatigue is a feeling of extreme physical or mental tiredness. Almost everyone becomes fatigued at some time, but driver’s fatigue is a serious problem that leads to thousands of automobile crashes each year. Fatigue process is often a change from the alertness and vigor state to the tiredness and weakness state. It is not only accompanied by drowsiness but also has a negative impact on mood. There have been studies to detect and quantify fatigue from the measurement of physiology variables such as electroencephalogram (EEG), electrooculogram (EOG), and electromyogram (EMG). This project involves a multimodal sensing of driver’s drowsiness. The first method is to count the eye blinking rate. In the second level, we authenticate the results of eye blink module with a grip sensor. The Flexiforce sensor is placed over the steering wheel. In the third level, the activities are sensed, the time elapsed from the driver’s last activity is counted here. The activities in the sense: Changing gear, applying brake, pressing sound horns, and turning the steering wheel. Absence of these activities is also an indicator of fatigue.

Keywords: eye blink sensor, Flexiforce sensor, EEG, EOG, EMG

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Authors: Pooja Booluck

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This project seeks to translate a chapter in Le Silence des Chagos by Shenaz Patel a Mauritian author whose work has never been translated before. The chapter discusses the attempt of the protagonist to return to her home country Diego Garcia after her deportation. The English translation will offer an historical account to the target audience of the deportation of Chagossians to Mauritius during the 1970s. The target audience comprises of English-speaking translation scholars translation students and African literature scholars. In light of making the cultural elements of Mauritian culture accessible the translation will maintain the cultural items such as food and oral discourses in Creole so as to preserve the authenticity of the source culture. In order to better comprehend the cultural elements mentioned the target reader will be provided with detailed footnotes explaining the cultural and historical references. This translation will also address the importance of folkloric songs in Mauritius and its intergenerational function in Mauritian communities which will also remain in Creole. While such an approach will help to preserve the meaning of the source text the borrowing technique and the foreignizing method will be employed which will in turn help the reader in becoming more familiar with the Mauritian community. Translating a text from French to English while maintaining certain words or discourses in a minority language such as Creole bears certain challenges: How does the translator ensure the comprehensibility of the reader? Are there any translation losses? What are the choices of the translator?

Keywords: Chagos archipelagos in Exile, English translation, Le Silence des Chagos, Mauritian culture and history

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Authors: Dasom Kim, Chen Liu, Myungsu Lim, Su-Hyeon Jeon, ByeoungKug Jeon, Kee-Young Kwahk, Namgyu Kim

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Recently, numerous documents including unstructured data and text have been created due to the rapid increase in the usage of social media and the Internet. Each document is usually provided with a specific category for the convenience of the users. In the past, the categorization was performed manually. However, in the case of manual categorization, not only can the accuracy of the categorization be not guaranteed but the categorization also requires a large amount of time and huge costs. Many studies have been conducted towards the automatic creation of categories to solve the limitations of manual categorization. Unfortunately, most of these methods cannot be applied to categorizing complex documents with multiple topics because the methods work by assuming that one document can be categorized into one category only. In order to overcome this limitation, some studies have attempted to categorize each document into multiple categories. However, they are also limited in that their learning process involves training using a multi-categorized document set. These methods therefore cannot be applied to multi-categorization of most documents unless multi-categorized training sets are provided. To overcome the limitation of the requirement of a multi-categorized training set by traditional multi-categorization algorithms, we previously proposed a new methodology that can extend a category of a single-categorized document to multiple categorizes by analyzing relationships among categories, topics, and documents. In this paper, we design a survey-based verification scenario for estimating the accuracy of our automatic categorization methodology.

Keywords: big data analysis, document classification, multi-category, text mining, topic analysis

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Authors: Christine Demaecker

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Many researchers have underlined the importance of metaphors in specialised language. Their use of specific domains helps us understand the conceptualisations used to communicate new ideas or difficult topics. Within the wide area of specialised discourse, wine tasting is a very specific example because it is almost exclusively metaphoric. Wine tasting metaphors express various conceptualisations. They are not linguistic but rather conceptual, as defined by Lakoff & Johnson. They correspond to the linguistic expression of a mental projection from a well-known or more concrete source domain onto the target domain, which is the taste of wine. But unlike most specialised terminologies, the vocabulary is never clearly defined. When metaphorical terms are listed in dictionaries, their definitions remain vague, unclear, and circular. They cannot be replaced by literal linguistic expressions. This makes it impossible to transfer them into another language with the traditional linguistic translation methods. Qualitative research investigates whether wine tasting metaphors could rather be translated with the cognitive translation process, as well described by Nili Mandelblit (1995). The research is based on a corpus compiled from two high-profile wine guides; the Parker’s Wine Buyer’s Guide and its translation into French and the Guide Hachette des Vins and its translation into English. In this small corpus with a total of 68,826 words, 170 metaphoric expressions have been identified in the original English text and 180 in the original French text. They have been selected with the MIPVU Metaphor Identification Procedure developed at the Vrije Universiteit Amsterdam. The selection demonstrates that both languages use the same set of conceptualisations, which are often combined in wine tasting notes, creating conceptual integrations or blends. The comparison of expressions in the source and target texts also demonstrates the use of the cognitive translation approach. In accordance with the principle of relevance, the translation always uses target language conceptualisations, but compared to the original, the highlighting of the projection is often different. Also, when original metaphors are complex with a combination of conceptualisations, at least one element of the original metaphor underlies the target expression. This approach perfectly integrates into Lederer’s interpretative model of translation (2006). In this triangular model, the transfer of conceptualisation could be included at the level of ‘deverbalisation/reverbalisation’, the crucial stage of the model, where the extraction of meaning combines with the encyclopedic background to generate the target text.

Keywords: cognitive translation, conceptual integration, conceptual metaphor, interpretative model of translation, wine tasting metaphor

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Authors: Jason Digalakis, John Cotronis

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Memetic algorithms (MAs) are useful for solving optimization problems. It is quite difficult to search the search space of the optimization problem with large dimensions. There is a challenge to use all the cores of the system. In this study, a sequential implementation of the memetic algorithm is converted into a concurrent version, which is executed on the cores of both CPU and GPU. For this reason, CUDA and OpenMP libraries are operated on the parallel algorithm to make a concurrent execution on CPU and GPU, respectively. The aim of this study is to compare CPU and GPU implementation of the memetic algorithm. For this purpose, fourteen benchmark functions are selected as test problems. The obtained results indicate that our approach leads to speedups up to five thousand times higher compared to one CPU thread while maintaining a reasonable results quality. This clearly shows that GPUs have the potential to acceleration of MAs and allow them to solve much more complex tasks.

Keywords: memetic algorithm, CUDA, GPU-based memetic algorithm, open multi processing, multimodal functions, unimodal functions, non-linear optimization problems

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Authors: Fatin Khairani Khairul 'Azam

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Reading comprehension requires the formation of an articulate mental representation of the information in a text. It involves three interdepended elements—the reader, the text, and the activity, all situated into an extensive sociocultural context. Incorporating metacognitive think-aloud strategy into teaching reading comprehension would improve learners’ reading comprehension skills as it helps to monitor their thinking as they read. Furthermore, by integrating Digital Educational Learning Initiative Malaysia (DELIMa) platform in teaching reading comprehension, it can make the process interactive and fun. A quasi-experimental one-group pre-test post-test design was used to identify the effectiveness of using metacognitive think-aloud strategy via DELIMa platform in improving pupils’ reading comprehension performance and their perceptions towards reading comprehension. The participants of the study comprised 82 of form 1 pupils from a secondary school in Pasir Gudang, Johor, Malaysia. All participants were required to sit for pre-and post-tests to track their reading comprehension performance and perceptions. The findings revealed that incorporating metacognitive think-aloud strategy is an effective strategy in teaching reading comprehension as the performance of pupils in reading comprehension and their perceptions towards reading comprehension were improved during the post tests. It is hoped that the findings of the study would be useful to the teachers incorporating the same strategy in teaching to improve pupils' reading skills. It is suggested that future study should involve the motivation factor of the participants on incorporating think-aloud strategy into teaching reading comprehension as well.

Keywords: DELIMa Platform, ESL Learners, Metacognitive Strategy, Pupils' Perceptions, Reading Comprehension, Think-Aloud Strategy

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Authors: Jaehyung An, Sungjoo Lee

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Patent documents constitute an up-to-date and reliable source of knowledge for reflecting technological advance, so patent analysis has been widely used for identification of technological trends and formulation of technology strategies. But, identifying technological information from patent data entails some limitations such as, high cost, complexity, and inconsistency because it rely on the expert’ knowledge. To overcome these limitations, researchers have applied to a quantitative analysis based on the keyword technique. By using this method, you can include a technological implication, particularly patent documents, or extract a keyword that indicates the important contents. However, it only uses the simple-counting method by keyword frequency, so it cannot take into account the sematic relationship with the keywords and sematic information such as, how the technologies are used in their technology area and how the technologies affect the other technologies. To automatically analyze unstructured technological information in patents to extract the semantic information, it should be transformed into an abstracted form that includes the technological key concepts. Specific sentence structure ‘SAO’ (subject, action, object) is newly emerged by representing ‘key concepts’ and can be extracted by NLP (Natural language processor). An SAO structure can be organized in a problem-solution format if the action-object (AO) states that the problem and subject (S) form the solution. In this paper, we propose the new methodology that can extract the SAO structure through technical elements extracting rules. Although sentence structures in the patents text have a unique format, prior studies have depended on general NLP (Natural language processor) applied to the common documents such as newspaper, research paper, and twitter mentions, so it cannot take into account the specific sentence structure types of the patent documents. To overcome this limitation, we identified a unique form of the patent sentences and defined the SAO structures in the patents text data. There are four types of technical elements that consist of technology adoption purpose, application area, tool for technology, and technical components. These four types of sentence structures from patents have their own specific word structure by location or sequence of the part of speech at each sentence. Finally, we developed algorithms for extracting SAOs and this result offer insight for the technology innovation process by providing different perspectives of technology.

Keywords: NLP, patent analysis, SAO, semantic-analysis

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Authors: Xu Jiaqiao

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Text sentiment analysis is an important branch of natural language processing. This technology is widely used in public opinion analysis and web surfing recommendations. At present, the mainstream sentiment analysis methods include three parts: sentiment analysis based on a sentiment dictionary, based on traditional machine learning, and based on deep learning. This paper mainly analyzes and compares the advantages and disadvantages of the SVM method of traditional machine learning and the Long Short-term Memory (LSTM) method of deep learning in the field of Chinese sentiment analysis, using Chinese comments on Sina Microblog as the data set. Firstly, this paper classifies and adds labels to the original comment dataset obtained by the web crawler, and then uses Jieba word segmentation to classify the original dataset and remove stop words. After that, this paper extracts text feature vectors and builds document word vectors to facilitate the training of the model. Finally, SVM and LSTM models are trained respectively. After accuracy calculation, it can be obtained that the accuracy of the LSTM model is 85.80%, while the accuracy of SVM is 91.07%. But at the same time, LSTM operation only needs 2.57 seconds, SVM model needs 6.06 seconds. Therefore, this paper concludes that: compared with the SVM model, the LSTM model is worse in accuracy but faster in processing speed.

Keywords: sentiment analysis, support vector machine, long short-term memory, Chinese microblog comments

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Authors: Omotayo Olalere

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The relevance of code-switching for intercultural communication through literary translation cannot be overemphasized. The translation of code-switching and its implications for translations studies have been studied in the context of African literature. In these cases, code-switching was examined in the more general terms of its usage in source text and not particularly in Ngugi’s novels and its translations. In addition, the functions of translation and code-switching in the lyrics of some popular African songs have been studied, but this study is related more with oral performance than with written literature. As such, little has been done on the German translation of code-switching in African works. This study intends to fill this lacuna by examining the concept of code-switching in the German translations in Ngugi’s Petals of Blood. The aim is to highlight the significance of code-switching as a phenomenon in this African (Ngugi’s) novel written in English and to also focus on its representation in the two German translations. The target texts to be used are Verbrannte Blueten and Land der flammenden Blueten. “Abrogration“ as a concept will play an important role in the analysis of the data. Findings will show that the ideology of a translator plays a huge role in representing the concept of “abrogration” in the translation of code-switching in the selected source text. The study will contribute to knowledge in translation studies by bringing to limelight the need to foreground aspects of language contact in translation theory and practice, particularly in the African context. Relevant translation theories adopted for the study include Bandia’s (2008) postcolonial theory of translation and Snell-Hornby”s (1988) cultural translation theory.

Keywords: code switching, german translation, ngugi wa thiong’o, petals of blood

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Authors: Sanghamitra Sadhu

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A paradigm shift from capitalism to information technology is discerned in the era globalisation. The idea of public sphere, which was theorized in terms of its decline in the wake of the rise of commercial mass media has now emerged as a transnational or global sphere with the discourse being dominated by the ‘network society’. In other words, the dynamic of globalisation has brought about ‘a spatial turn’ in the social and political sciences which is also manifested in the public sphere, Especially the global public sphere. The paper revisits the Habermasian concept of the public sphere and focuses on the various social networking sites with their plausibility to create a virtual global public sphere. Situating Habermas’s notion of the bourgeois public sphere in the present context of global public sphere, it considers the changing dimensions of the public sphere across time and examines the concept of the ‘public’ with its shifting transformation from the concrete collective to the fluid ‘imagined’ category. The paper addresses the problematic of multimodal self-portraiture in the social networking sites as well as various online diaries/journals with an attempt to explore the nuances of the networked self.

Keywords: globalisation, network society, public sphere, self-fashioning, identity, autonomy

Procedia PDF Downloads 391