Search results for: text embedding

Authors: Yufen Qin

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Topic-to-Essay generation is a challenging task in Natural language processing, which aims to generate novel, diverse, and topic-related text based on user input. Previous research has overlooked the generation of articles under the constraints of event elements, resulting in issues such as incomplete event elements and logical inconsistencies in the generated results. To fill this gap, this paper proposes an event-constrained approach for a topic-to-essay generation that enforces the completeness of event elements during the generation process. Additionally, a language model is employed to verify the logical consistency of the generated results. Experimental results demonstrate that the proposed model achieves a better BLEU-2 score and performs better than the baseline in terms of subjective evaluation on a real dataset, indicating its capability to generate higher-quality topic-related text.

Keywords: event element, language model, natural language processing, topic-to-essay generation.

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Authors: Shaza Melies, Saadeya Salem, Seham Kareh

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Cartoon films are multisemiotic as various modes integrate in the production of meaning. This study aims to examine the cultural and linguistic specific references in the Egyptian dubbed cartoon film Mulan. The study examines the translation strategies implemented in the Egyptian dubbed version of Mulan to meet the cultural preferences of the audience. The study reached the following findings: Using the traditional translation strategies does not deliver the intended meaning of the source text and causes loss in the intended humor. As a result, the findings showed that in the dubbed version, translators tend to omit, change, or add information to the target text to be accepted by the audience. The contrastive analysis of the Mulan (English and dubbed versions) proves the connotations that the dubbing has taken to be accepted by the target audience. Cartoon films are multisemiotic as various modes integrate in the production of meaning. This study aims to examine the cultural and linguistic specific references in the Egyptian dubbed cartoon film Mulan. The study examines the translation strategies implemented in the Egyptian dubbed version of Mulan to meet the cultural preferences of the audience. The study reached the following findings: Using the traditional translation strategies does not deliver the intended meaning of the source text and causes loss in the intended humor. As a result, the findings showed that in the dubbed version, translators tend to omit, change, or add information to the target text to be accepted by the audience. The contrastive analysis of the Mulan (English and dubbed versions) proves the connotations that the dubbing has taken to be accepted by the target audience.

Keywords: domestication, dubbing, Mulan, translation theories

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Authors: Mehrnoosh Pirhayati

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In this study, the researcher tried to propose a model of Translation Criticism (TC) regarding the phenomenon of Translation Quality Assessment (TQA). With changing the general view on re/writing as an illegal act, the researcher defined a scale for the act of translation and determined the redline of translation with other products. This research attempts to show TC as a related phenomenon to TQA. This study shows that TQA with using the rules and factors of TC as depicted in both product-oriented analysis and process-oriented analysis, determines the orientation or the level of the quality of translation. This study also depicts that TC, regarding TQA’s perspective, reveals the aim of the translation of original text and the root of ideological manipulation and re/writing. On the other hand, this study stresses the existence of a direct relationship between the linguistic materials and semiotic codes of a text or book. This study can be fruitful for translators, scholars, translation criticizers, and translation quality assessors, and also it is applicable in the area of pedagogy.

Keywords: a model of translation criticism, a model of translation quality assessment, critical discourse analysis (CDA), re/writing, translation criticism (TC), translation quality assessment (TQA)

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Authors: Asmaa Fathy Mohamed Desoky

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The subject of this research is the inference of intentionality and context from the verses of the Meccan surahs, which include the paradox of reward and punishment, applied to the duality of disbelief and faith; The Holy Quran is the most important sacred linguistic reference in the Arabic language because it is rich in all the rules of the language in addition to the linguistic miracle. the Quranic text is a first-class intentional text, sent down to convey something to the recipient (Muhammad first and then communicates it to Muslims) and influence and convince him, which opens the door to many Ijtihad; a desire to reach the will of Allah and his intention from his words Almighty. Intentionality as a term is one of the most important deliberative terms, but it will be modified to suit the Quranic discourse, especially since intentionality is related to intention-as it turned out earlier - that is, it turns the reader or recipient into a predictor of the unseen, and this does not correspond to the Quranic discourse. Hence, in this research, a set of dualities will be identified that will be studied in order to clarify the meaning of them according to the opinions of previous interpreters in accordance with the sanctity of the Quranic discourse, which is intentionally related to the dualities of reward and punishment, such as: the duality of disbelief and faith, noting that it is a duality that combines opposites and Paradox on one level, because it may be an external paradox between action and reaction, and may be an internal paradox in matters related to faith, and may be a situational paradox in a specific event or a certain fact. It should be noted that the intention of the Qur'anic text is fully realized in form and content, in whole and in part, and this research includes a presentation of some applied models of the issues of intention and context that appear in the verses of the paradox of reward and punishment in the Meccan surahs in Quraan.

Keywords: intentionality, context, the paradox, reward, punishment, Meccan surahs

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Authors: Ainagul Yermekova, Liudmila Goncharenko, Ali Baghirzade, Sergey Sybachin

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In this article, we address the problem of Kazakhstan's transition to the Latin alphabet. The transition process started in 2017 and is scheduled to be completed in 2025. In connection with these events, the problem of recognizing the characters of the new alphabet is raised. Well-known character recognition programs such as ABBYY FineReader, FormReader, MyScript Stylus did not recognize specific Kazakh letters that were used in Cyrillic. The author tries to give an assessment of the well-known method of character recognition that could be in demand as part of the country's transition to the Latin alphabet. Three methods of character recognition: template, structured, and feature-based, are considered through the algorithms of operation. At the end of the article, a general conclusion is made about the possibility of applying a certain method to a particular recognition process: for example, in the process of population census, recognition of typographic text in Latin, or recognition of photos of car numbers, store signs, etc.

Keywords: text detection, template method, recognition algorithm, structured method, feature method

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Authors: Rui Yin, Haojie Wang, Xun Li

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Recently, mainstream dense retrieval methods have obtained state-of-the-art results on some datasets and tasks. However, they require large amounts of training data, which is not available in most domains. The severe performance degradation of dense retrievers on new data domains has limited the use of dense retrieval methods to only a few domains with large training datasets. In this paper, we propose an unsupervised domain-adaptive approach based on query generation. First, a generative model is used to generate relevant queries for each passage in the target corpus, and then the generated queries are used for mining negative passages. Finally, the query-passage pairs are labeled with a cross-encoder and used to train a domain-adapted dense retriever. Experiments show that our approach is more robust than previous methods in target domains that require less unlabeled data.

Keywords: dense retrieval, query generation, unsupervised training, text retrieval

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Authors: Moshe Wasserblat, Jonathan Mamou, Oren Pereg

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Natural Language Processing (NLP) has made a major leap in the last few years, in practical integration into medical solutions; for example, extracting clinical concepts from medical texts such as medical condition, medication, treatment, and symptoms. However, training and deploying those models in real environments still demands a large amount of annotated data and NLP/Machine Learning (ML) expertise, which makes this process costly and time-consuming. We present a practical and efficient method for clinical concept extraction that does not require costly labeled data nor ML expertise. The method includes three steps: Step 1- the user injects a large in-domain text corpus (e.g., PubMed). Then, the system builds a contextual model containing vector representations of concepts in the corpus, in an unsupervised manner (e.g., Phrase2Vec). Step 2- the user provides a seed set of terms representing a specific medical concept (e.g., for the concept of the symptoms, the user may provide: ‘dry mouth,’ ‘itchy skin,’ and ‘blurred vision’). Then, the system matches the seed set against the contextual model and extracts the most semantically similar terms (e.g., additional symptoms). The result is a complete set of terms related to the medical concept. Step 3 –in production, there is a need to extract medical concepts from the unseen medical text. The system extracts key-phrases from the new text, then matches them against the complete set of terms from step 2, and the most semantically similar will be annotated with the same medical concept category. As an example, the seed symptom concepts would result in the following annotation: “The patient complaints on fatigue [symptom], dry skin [symptom], and Weight loss [symptom], which can be an early sign for Diabetes.” Our evaluations show promising results for extracting concepts from medical corpora. The method allows medical analysts to easily and efficiently build taxonomies (in step 2) representing their domain-specific concepts, and automatically annotate a large number of texts (in step 3) for classification/summarization of medical reports.

Keywords: clinical concepts, concept expansion, medical records annotation, medical records summarization

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Authors: Kristine D. de Leon, Junifer A. Abatayo, Jose Cristina M. Pariña

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The current study is a comparative analysis of the use of shell nouns as a cohesive device (CD) in an English for Second Language (ESL) setting in order to identify their use and relationship in the quality of second language (L2) writing. As these nouns were established to anticipate the meaning within, across or outside the text, their use has fascinated writing researchers. The corpus of the study included published articles from reputable journals and graduate students’ papers in order to analyze the frequency of shell nouns using “highly prevalent” nouns in the academic community, to identify the different lexicogrammatical patterns where these nouns occur and to the functions connected with these patterns. The result of the study implies that published authors used more shell nouns in their paper than graduate students. However, the functions of the different lexicogrammatical patterns for the frequently occurring shell nouns are somewhat similar. These results could help students in enhancing the cohesion of their text and in comprehending it.

Keywords: anaphoric, cataphoric, lexico-grammatical, shell nouns

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Authors: Revoti Prasad Bora, Saurabh Yadav, Nikita Katyal

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In the context of educational data mining, the use case of extracting information from images containing both text and diagrams is of high importance. Hence, document analysis requires the extraction of diagrams from such images and processes the text and diagrams separately. To the author’s best knowledge, none among plenty of approaches for extracting tables, figures, etc., suffice the need for real-time processing with high accuracy as needed in multiple applications. In the education domain, diagrams can be of varied characteristics viz. line-based i.e. geometric diagrams, chemical bonds, mathematical formulas, etc. There are two broad categories of approaches that try to solve similar problems viz. traditional computer vision based approaches and deep learning approaches. The traditional computer vision based approaches mainly leverage connected components and distance transform based processing and hence perform well in very limited scenarios. The existing deep learning approaches either leverage YOLO or faster-RCNN architectures. These approaches suffer from a performance-accuracy tradeoff. This paper proposes a U-Net based architecture that formulates the diagram extraction as a segmentation problem. The proposed method provides similar accuracy with a much faster extraction time as compared to the mentioned state-of-the-art approaches. Further, the segmentation mask in this approach allows the extraction of diagrams of irregular shapes.

Keywords: computer vision, deep-learning, educational data mining, faster-RCNN, figure extraction, image segmentation, real-time document analysis, text extraction, U-Net, YOLO

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Authors: Taekyong Lee, Joon-Young Kim, Jae-Min Cha

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Piping and instrumentation diagram (P&ID) is an essential design drawing describing the interconnection of process equipment and the instrumentation installed to control the process. P&IDs are modified and managed throughout a whole life cycle of a process plant. For the ease of data transfer, P&IDs are generally handed over from a design company to an engineering company as portable document format (PDF) which is hard to be modified. Therefore, engineering companies have to deploy a great deal of time and human resources only for manually converting P&ID images into a computer aided design (CAD) file format. To reduce the inefficiency of the P&ID conversion, various symbols and texts in P&ID images should be automatically recognized. However, recognizing information in P&ID images is not an easy task. A P&ID image usually contains hundreds of symbol and text objects. Most objects are pretty small compared to the size of a whole image and are densely packed together. Traditional recognition methods based on geometrical features are not capable enough to recognize every elements of a P&ID image. To overcome these difficulties, state-of-the-art deep learning models, RetinaNet and connectionist text proposal network (CTPN) were used to build a system for recognizing symbols and texts in a P&ID image. Using the RetinaNet and the CTPN model carefully modified and tuned for P&ID image dataset, the developed system recognizes texts, equipment symbols, piping symbols and instrumentation symbols from an input P&ID image and save the recognition results as the pre-defined extensible markup language format. In the test using a commercial P&ID image, the P&ID information recognition system correctly recognized 97% of the symbols and 81.4% of the texts.

Keywords: object recognition system, P&ID, symbol recognition, text recognition

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Authors: M. Naidoo

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Artificial intelligence often requires large amounts of good quality data. Within important fields, such as healthcare, the training of AI systems predominately relies on health and personal data; however, the usage of this data is complicated by various layers of law and ethics that seek to protect individuals’ privacy rights. This research seeks to establish the challenges AI and data sciences pose to (i) informational rights, (ii) privacy rights, and (iii) data protection. To solve some of the issues presented, various methods are suggested, such as embedding values in technological development, proper balancing of rights and interests, and others.

Keywords: artificial intelligence, data science, law, policy

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Authors: Rosa Figueroa, Christopher Flores

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Text categorization is the problem of assigning a new document to a set of predetermined categories, on the basis of a training set of free-text data that contains documents whose category membership is known. To train a classification model, it is necessary to extract characteristics in the form of tokens that facilitate the learning and classification process. In text categorization, the feature extraction process involves the use of word sequences also known as N-grams. In general, it is expected that documents belonging to the same category share similar features. The Smith-Waterman (SW) algorithm is a dynamic programming algorithm that performs a local sequence alignment in order to determine similar regions between two strings or protein sequences. This work explores the use of SW algorithm as an alternative to feature extraction in text categorization. The dataset used for this purpose, contains 2,610 annotated documents with the classes Obese/Non-Obese. This dataset was represented in a matrix form using the Bag of Word approach. The score selected to represent the occurrence of the tokens in each document was the term frequency-inverse document frequency (TF-IDF). In order to extract features for classification, four experiments were conducted: the first experiment used SW to extract features, the second one used unigrams (single word), the third one used bigrams (two word sequence) and the last experiment used a combination of unigrams and bigrams to extract features for classification. To test the effectiveness of the extracted feature set for the four experiments, a Support Vector Machine (SVM) classifier was tuned using 20% of the dataset. The remaining 80% of the dataset together with 5-Fold Cross Validation were used to evaluate and compare the performance of the four experiments of feature extraction. Results from the tuning process suggest that SW performs better than the N-gram based feature extraction. These results were confirmed by using the remaining 80% of the dataset, where SW performed the best (accuracy = 97.10%, weighted average F-measure = 97.07%). The second best was obtained by the combination of unigrams-bigrams (accuracy = 96.04, weighted average F-measure = 95.97) closely followed by the bigrams (accuracy = 94.56%, weighted average F-measure = 94.46%) and finally unigrams (accuracy = 92.96%, weighted average F-measure = 92.90%).

Keywords: comorbidities, machine learning, obesity, Smith-Waterman algorithm

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Authors: Chien-Hung Chen, Yan-Chun Hsing, Yung-Chun Chang

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The Internet has grown into a powerful medium for information dispersion and social interaction that leads to a rapid growth of social media which allows users to easily post their emotions and perspectives regarding certain topics online. Our research aims at using natural language processing and text mining techniques to explore the public emotions expressed on Twitter by analyzing the sentiment behind tweets. In this paper, we propose a composite kernel method that integrates tree kernel with the linear kernel to simultaneously exploit both the tree representation and the distributed emotion keyword representation to analyze the syntactic and content information in tweets. The experiment results demonstrate that our method can effectively detect public emotion of tweets while outperforming the other compared methods.

Keywords: emotion recognition, natural language processing, composite kernel, sentiment analysis, text mining

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Authors: Siamak Samani, Nadereh Sohrabi

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Psychological nano-therapy is a new method based on systems theory. According to the theory, systems with severe dysfunctions are resistant to changes. Psychological nano-therapy helps the therapists to break this ice. Two key concepts in psychological nano-therapy are nano-functions and nano-behaviors. The most important step in psychological nano-therapy in family therapy is selecting the most effective nano-function and nano-behavior. The aim of this study was to check the effectiveness of psychological nano-therapy for family therapy. One group pre-test-post-test design (quasi-experimental Design) was applied for research. The sample consisted of ten families with severe marital conflict. The important character of these families was resistance for participating in family therapy. In this study, sending respectful (nano-function) text massages (nano-behavior) with cell phone were applied as a treatment. Cohesion/respect sub scale from self-report family processes scale and family readiness for therapy scale were used to assess all family members in pre-test and post-test. In this study, one of family members was asked to send a respectful text massage to other family members every day for a week. The content of the text massages were selected and checked by therapist. To compare the scores of families in pre-test and post-test paired sample t-test was used. The results of the test showed significant differences in both cohesion/respect score and family readiness for therapy between per-test and post-test. The results revealed that these families have found a better atmosphere for participation in a complete family therapy program. Indeed, this study showed that psychological nano-therapy is an effective method to make family readiness for therapy.

Keywords: family therapy, family conflicts, nano-therapy, family readiness

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Authors: Zohreh Ramin

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One of the most important contributions that Edward Said has had in the realm of critical theory is his insistence on the worldliness of the text and the critic. By this, Said meant that the critic and the text must be considered in their ‘material’ contexts. Foregrounding the substantial role of a critic as embodying what he refers to as ‘critical consciousness’, a true critic, Said maintains, is one who can stand between the ‘dominant culture’ and ‘the totalizing forms of critical systems.’ Considered as one of Iran’s major contemporary intellectuals, Jalal Ale Ahmad is responsible for introducing the idea of ‘Westoxication’ in Iran, constructing a social paradigm of the necessity to return to tradition in contemporary Iran. The present paper intends to study Al-Ahmad’s definition of the orient versus the occident, his criticism of the ‘machination’ of contemporary Iranian society, and his solution to the problem of ‘Westoxication’. The objective of this study is to see whether Ale Ahmad can be considered as embodying the spirit of ‘critical consciousness’ as described by Said as the necessary tool in the hands of an intellectual who is simultaneously attached filitavely to his culture but can detach himself affilitavely through employing critical consciousness.

Keywords: Westoxication, filiative, affiliative, machination

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Authors: Arianna Sacerdoti

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The translation of Haiku Poetry into Latin is fundamentally experimental in nature. One of the first seminal books containing such translations, alongside translations into different modern languages, 'A Piedi Scalzi', was written by Tartamella in 2016. The results of a text-oriented study of this book will be commented upon and analyzed. The author Arianna Sacerdoti made similar translations with high school student. Such an experiment garners interest across a diverse range of disciplines such as teaching, translation studies, and classics reception studies. The methodology employed is text-oriented as the Haiku poem translations will be commented on by considering their relationship with the original. The results of this investigation, conducted within the field of experimental teaching, are expected to confirm the usefulness of this approach to the teaching of Latin and its potential to actively involve students in identifying the diachronic differences between the world of classical antiquity and the contemporary one.

Keywords: ancient latin, Haiku, translation studies, reception of classics

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Authors: Giya Erina

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Linguists have analyzed the rhetorical structure of various forensic genres, but only a few have investigated the complete structure of death row statements. Unlike other forensic text types, such as suicide or ransom notes, the focus of death row statement analysis is not the authenticity or falsity of the text, but its intended meaning and its communicative purpose. As it constitutes their last statement before their execution, there are probably many things that inmates would like to express. This study mainly examines the rhetorical moves of 200 death row statements from the Texas Department of Criminal Justice website using rhetorical move analysis. The rhetorical moves identified in the statements will be classified based on their communicative purpose, and they will be grouped into moves and steps. A move structure will finally be suggested from the most common or characteristic moves and steps, as well as some sub-moves. However, because of some statements’ atypicality, some moves may appear in different parts of the texts or not at all.

Keywords: Death row statements, forensic linguistics, genre analysis, move analysis

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Authors: Narissa Lewis, Susan Geertshuis

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The global and national employability agenda is changing the higher education landscape as academic staff are faced with the responsibility of developing employability capabilities and attributes in addition to delivering discipline specific content and skills. They realise that the shift towards teaching sustainable capabilities means a shift in the way they teach. But what that shift should be or how they should bring it about is unclear. As part of a national funded project, representatives from several New Zealand (NZ) higher education institutions and the NZ Association of Graduate Employers partnered to discover, trial and disseminate means of embedding employability in the curriculum. Findings from four focus groups (n=~75) and individual interviews (n=20) with staff from several NZ higher education institutions identified factors that enable or hinder embedded employability development within their respective institutions. Participants believed that higher education institutions have a key role in developing graduates for successful lives and careers however this requires a significant shift in culture within their respective institutions. Participants cited three main barriers: lack of strategic direction, support and guidance; lack of understanding and awareness of employability; and lack of resourcing and staff capability. Without adequate understanding and awareness of employability, participants believed it is difficult to understand what employability is let alone how it can be embedded in the curriculum. This presentation will describe some of the impacts that the employability agenda has on staff as they try to move from traditional to contemporary forms of teaching to develop employability attributes of students. Changes at the institutional level are required to support contemporary forms of teaching, however this is often beyond the sphere of influence at the teaching staff level. The study identified that small changes to teaching practices were necessary and a simple model to facilitate change from traditional to contemporary forms of teaching was developed. The model provides a framework to identify small but impactful teaching practices and exemplar teaching practices were identified. These practices were evaluated for transferability into other contexts to encourage small but impactful changes to embed employability in the curriculum.

Keywords: curriculum design, change management, employability, teaching exemplars

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Authors: Silvia Santano Guillén, Luigi Lo Iacono, Christian Meder

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One of the main aims of current social robotic research is to improve the robots’ abilities to interact with humans. In order to achieve an interaction similar to that among humans, robots should be able to communicate in an intuitive and natural way and appropriately interpret human affects during social interactions. Similarly to how humans are able to recognize emotions in other humans, machines are capable of extracting information from the various ways humans convey emotions—including facial expression, speech, gesture or text—and using this information for improved human computer interaction. This can be described as Affective Computing, an interdisciplinary field that expands into otherwise unrelated fields like psychology and cognitive science and involves the research and development of systems that can recognize and interpret human affects. To leverage these emotional capabilities by embedding them in humanoid robots is the foundation of the concept Affective Robots, which has the objective of making robots capable of sensing the user’s current mood and personality traits and adapt their behavior in the most appropriate manner based on that. In this paper, the emotion recognition capabilities of the humanoid robot Pepper are experimentally explored, based on the facial expressions for the so-called basic emotions, as well as how it performs in contrast to other state-of-the-art approaches with both expression databases compiled in academic environments and real subjects showing posed expressions as well as spontaneous emotional reactions. The experiments’ results show that the detection accuracy amongst the evaluated approaches differs substantially. The introduced experiments offer a general structure and approach for conducting such experimental evaluations. The paper further suggests that the most meaningful results are obtained by conducting experiments with real subjects expressing the emotions as spontaneous reactions.

Keywords: affective computing, emotion recognition, humanoid robot, human-robot-interaction (HRI), social robots

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Authors: Kevin Smith

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Publicly traded company in the US are legally obligated to host earnings calls that discuss their most recent financial reports. During these calls, investors are able to ask these companies questions about these financial reports and on the future direction of the company. This paper examines whether common institutional owners use these calls as a way to indirectly signal to companies in their portfolio to not take actions that could hurt the common owner's interests. This paper uses transcripts taken from the earnings calls of the six largest health insurance companies in the US from 2014 to 2019. This data is analyzed using text analysis and sentiment analysis to look for patterns in the statements made by common owners. The analysis found that common owners where more likely to recommend against direct price competition and instead redirect the insurance companies towards more passive actions, like investing in new technologies. This result indicates a mechanism that common owners use to reduce competition in the health insurance market.

Keywords: common ownership, text analysis, sentiment analysis, machine learning

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Authors: Moquan Gong

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In recent years, with the rapid development of deep learning, pre-training technology for natural language processing has made great progress. The early field of natural language processing has long used word vector methods such as Word2Vec to encode text. These word vector methods can also be regarded as static pre-training techniques. However, this context-free text representation brings very limited improvement to subsequent natural language processing tasks and cannot solve the problem of word polysemy. ELMo proposes a context-sensitive text representation method that can effectively handle polysemy problems. Since then, pre-training language models such as GPT and BERT have been proposed one after another. Among them, the BERT model has significantly improved its performance on many typical downstream tasks, greatly promoting the technological development in the field of natural language processing, and has since entered the field of natural language processing. The era of dynamic pre-training technology. Since then, a large number of pre-trained language models based on BERT and XLNet have continued to emerge, and pre-training technology has become an indispensable mainstream technology in the field of natural language processing. This article first gives an overview of pre-training technology and its development history, and introduces in detail the classic pre-training technology in the field of natural language processing, including early static pre-training technology and classic dynamic pre-training technology; and then briefly sorts out a series of enlightening technologies. Pre-training technology, including improved models based on BERT and XLNet; on this basis, analyze the problems faced by current pre-training technology research; finally, look forward to the future development trend of pre-training technology.

Keywords: natural language processing, pre-training, language model, word vectors

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Authors: Min Chen, Rubi Gupta

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Understanding and predicting stock market movements is a challenging problem. It is believed stock markets are partially driven by public sentiments, which leads to numerous research efforts to predict stock market trend using public sentiments expressed on social media such as Twitter but with limited success. Recently a microblogging website StockTwits is becoming increasingly popular for users to share their discussions and sentiments about stocks and financial market. In this project, we analyze the text content of StockTwits tweets and extract financial sentiment using text featurization and machine learning algorithms. StockTwits tweets are first pre-processed using techniques including stopword removal, special character removal, and case normalization to remove noise. Features are extracted from these preprocessed tweets through text featurization process using bags of words, N-gram models, TF-IDF (term frequency-inverse document frequency), and latent semantic analysis. Machine learning models are then trained to classify the tweets' sentiment as positive (bullish) or negative (bearish). The correlation between the aggregated daily sentiment and daily stock price movement is then investigated using Pearson’s correlation coefficient. Finally, the sentiment information is applied together with time series stock data to predict stock price movement. The experiments on five companies (Apple, Amazon, General Electric, Microsoft, and Target) in a duration of nine months demonstrate the effectiveness of our study in improving the prediction accuracy.

Keywords: machine learning, sentiment analysis, stock price prediction, tweet processing

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Authors: Christopher Dick

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While the translation of 'literal language' poses numerous challenges for the translator, the translation of 'figurative language' creates even more complicated issues. It has been only in the last several decades that scholars have attempted to propose theories of figurative language translation, including metaphor translation. Even less work has applied these theories to metaphoric translation in literary texts. And almost no work has linked an analysis of metaphors in translation with the recent scholarship on conceptual metaphors. A study of literature in translation must not only examine the inevitable shifts that occur as specific metaphors move from source language to target language but also analyze the ways in which these shifts impact conceptual metaphors and, ultimately, the text as a whole. Doing so contributes to on-going efforts to bridge the sometimes wide gulf between considerations of content and form in literary studies. This paper attempts to add to the body of scholarly literature on metaphor translation and the function of metaphor in a literary text. Specifically, the study examines the metaphoric expressions in Hemingway’s The Sun Also Rises. First, the issue of Hemingway and metaphor is addressed. Next, the study examines the specific metaphors in the original novel in English and the German translations, first in Annemarie Horschitz’s 1928 German version and then in the recent Werner Schmitz 2013 translation. Hemingway’s metaphors, far from being random occurrences of figurative language, are linguistic manifestations of deeper conceptual metaphors that are central to an interpretation of the text. By examining the modifications that are made to these original metaphoric expressions as they are translated into German, one can begin to appreciate the shifts involved with metaphor translation. The translation of Hemingway’s metaphors into German represents significant metaphoric loss and shifting that subsequently shakes the important conceptual metaphors in the novel.

Keywords: Hemingway, Conceptual Metaphor, Translation, Stylistics

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Authors: Wagneur Edouard

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Tropical algebra is the algebra constructed over an idempotent semifield S. We show here that every m-dimensional tropical module M over S with strongly independent basis can be embedded into Sm, and provide an algebraic invariant -the Γ-matrix of M- which characterises the isomorphy class of M. The strong independence condition also yields a significant improvement to the Whitney embedding for tropical torsion modules published earlier We also show that the strong independence of the basis of M is equivalent to the unique representation of elements of M. Numerous examples illustrate our results.

Keywords: classification, idempotent semi-modules, strong independence, tropical algebra

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Authors: Eduardo Álvarez, Gerardo Quiroga, Jorge Orozco, Gabriel Chavira

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AmI proposes a new way of thinking about computers, which follows the ideas of the Ubiquitous Computing vision of Mark Weiser. In these, there is what is known as a Disappearing Computer Initiative, with users immersed in intelligent environments. Hence, technologies need to be adapted so that they are capable of replacing the traditional inputs to the system by embedding these in every-day artifacts. In this work, we present an approach, which uses Radiofrequency Identification (RFID) and Near Field Communication (NFC) technologies. In the latter, a new form of interaction appears by contact. We compare both technologies by analyzing their requirements and advantages. In addition, we propose using a combination of RFID and NFC.

Keywords: touching interaction, ambient intelligence, ubiquitous computing, interaction, NFC and RFID

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Authors: Ritu Sharma

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In order to be objective, critics must examine the dynamic relationships between the author, the reader, the text, and the outside world. However, it is also crucial to recognize that because the language was created by God, meaning is ingrained in it. Meaning is located in and discovered through literature rather than being limited to the author, reader, text, or the outside world. The link between the author, the reader, and the text is crucial because literature unites an author and a reader through the use of language. Literature is a potent kind of communication, and Ethan Frome's audience is forever changed as a result of the book's language and the language its characters use. The narrative of Ethan Frome and his wife Zeena is presented in Ethan Frome. Ethan's story is told throughout the course of the book, revealed through the eyes of the narrator, an outsider passing through Starkfield, as well as through the insight that the narrator gains from the townspeople and his stay on the Frome farm. The story is set in the rural New England community of Starkfield, Massachusetts. The weather provides the ideal setting for Ethan and the narrator to get to know one another as the narrator gets preoccupied with unraveling the narrative that underlies Ethan's physical anomalies. In addition to telling a gripping tale and capturing human nature as it is, Ethan Frome uses its storyline to achieve something more significant. The book by Edith Wharton supports language. Zeena's deliberate and convincing language challenges relativity and meaninglessness. Ethan and Mattie's effort to effectively use words reflects the complexity of language, and their battle illustrates the influence that language may have if and when it is used. Ethan Frome defends the written word, the foundation upon which it is constructed, as a literary work. Communication is based on language, and as the characters respond to and get involved in disputes throughout the book, Zeena, Ethan, and Mattie, each reflects particular theories of communication that help define their uses of communication within the broader context of language.

Keywords: dynamic relationships, potent, communication, complexity

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Authors: Ulrica Pettersson

Abstract:

Collection of information on incidents is regularly done through pre-printed incident report forms. These tend to be incomplete and frequently lack essential information. ne consequence is that reports with inadequate information, that do not fulfil analysts’ requirements, are transferred into the analysis process. To improve an incident reporting form, theory in design science, witness psychology and interview and questionnaire research has been used. Previously three experiments have been conducted to evaluate the form and shown significant improved results. The form has proved to capture knowledge, regardless of the incidents’ character or context. The aim in this paper is to describe how design science, in more detail a design hierarchy can be used to construct a collection form for improvements in safety science.

Keywords: data collection, design science, incident reports, safety science

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Authors: Jonathan Ogwal, Louis H. Kamulegeya, John M. Bwanika, Davis Musinguzi

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Introduction: Community retail Pharmacy drug distribution points (CRPDDP) were implemented in the Lango sub-region as part of the Ministry of Health’s response to improving access and adherence to antiretroviral treatment (ART). Clients received their ART refills from nearby local pharmacies; as such, the need for continuous engagement through mobile phone appointment reminders and health messages. We share learnings from the implementation of mobile text reminders and voice call follow-ups among ART clients attending the CRPDDP program in northern Uganda. Methods: A retrospective data review of electronic medical records from four pharmacies allocated for CRPDDP in the Lira and Apac districts of the Lango sub-region in Northern Uganda was done from February to August 2022. The process involved collecting phone contacts of eligible clients from the health facility appointment register and uploading them onto a messaging platform customized by Rapid-pro, an open-source software. Client information, including code name, phone number, next appointment date, and the allocated pharmacy for ART refill, was collected and kept confidential. Contacts received appointment reminder messages and other messages on positive living as an ART client. Routine voice call follow-ups were done to ascertain the picking of ART from the refill pharmacy. Findings: In total, 1,354 clients were reached from the four allocated pharmacies found in urban centers. 972 clients received short message service (SMS) appointment reminders, and 382 were followed up through voice calls. The majority (75%) of the clients returned for refills on the appointed date, 20% returned within four days after the appointment date, and the remaining 5% needed follow-up where they reported that they were not in the district by the appointment date due to other engagements. Conclusion: The use of mobile text reminders and voice call follow-ups improves the attendance of community retail pharmacy refills.

Keywords: antiretroviral treatment, community retail drug distribution points, mobile text reminders, voice call follow-up

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Authors: Hirreche Baghdad Mohamed

Abstract:

One of the main texts in popular culture in Algeria is a symbolic and imaginary tale, through which the author was able to derive from the world and popular cultural stock and symbolic capital elements that enabled him to create a synthesis between a number of imaginary and real events. Thanks to the level of spirituality that the author was experiencing, he was able to go deep in order to redraw the boundaries of human life in view of its existence and status (life experiences, its end, and its fate). It is a text that is consistent with religious values and has a philosophical depth. This poem can be shared in official and unofficial meetings, during feasts, and during popular celebrations, such as circumcision ceremonies, marriage, and condolences. It has also the ability to draw attention and appeal to the listener and let him travel into the imaginary world. It is the text related to the story of "Ras b’nadem", or "the head of a man", or rather, a "human skull", for which only a few academic studies have been devoted, and there are two copies of it, one attributed to Lakhdar Ibn Khalouf as a matter of suspicion, while the other is attributed to Qadour Ibn Ashour Al-Zarhouni.

Keywords: ras B’Nadam, ras al mahna, lakhdar ibn khalouf, qadour ibn ashour, sufism, melhoun poetry, resistance poetry

Procedia PDF Downloads 192

Authors: Sulaiman Ahmed

Abstract:

This paper will analyse the classical Islamic text in order to determine whether the Arab spring was a rebellion or a revolution. Commencing in 2010, we saw a series of revolutions or what some would call rebellions throughout the Arab peninsula. Many of the religious clergies came out emphatically in support of the people who wanted to overthrow the leaders. This brought forth the important question about the acceptability of rebelling against unjust leaders in Islamic theological texts. The paper will look to analyse the Islamic legal and theological position on the permissibility of rebelling, whether there is scholarly consensus on the issue, and how the texts are analysed in order to come to the current position we have today. The position of the clergy who supported the Arab spring will also be analysed in order to deduce if their position falls within the religious framework. An inquiry will be about to determine the ideology of those who joined the rebellion after the inception and whether these ideas can be found in classical Islamic texts. The nuances of these positions will be analysed in order to determine whether what we witnessed was a rebellion or a revolution.

Keywords: rebellion, revolution, Arab spring, scholarly consensus

Procedia PDF Downloads 154