Search results for: text comprehension EIAH

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: Halimat M. Ajose-Adeogun, Zaynab A. Bello

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Artificial Intelligence (AI) and Natural Language Processing (NLP) have transformed computer language comprehension, allowing computers to comprehend spoken and written language with human-like cognition. NLP, a multidisciplinary area that combines rule-based linguistics, machine learning, and deep learning, enables computers to analyze and comprehend human language. NLP applications in medicine range from tackling issues in electronic health records (EHR) and psychiatry to improving diagnostic precision in orthopedic surgery and optimizing clinical procedures with novel technologies like chatbots. The technology shows promise in a variety of medical sectors, including quicker access to medical records, faster decision-making for healthcare personnel, diagnosing dysplasia in Barrett's esophagus, boosting radiology report quality, and so on. However, successful adoption requires training for healthcare workers, fostering a deep understanding of NLP components, and highlighting the significance of validation before actual application. Despite prevailing challenges, continuous multidisciplinary research and collaboration are critical for overcoming restrictions and paving the way for the revolutionary integration of NLP into medical practice. This integration has the potential to improve patient care, research outcomes, and administrative efficiency. The research methodology includes using NLP techniques for Sentiment Analysis and Emotion Recognition, such as evaluating text or audio data to determine the sentiment and emotional nuances communicated by users, which is essential for designing a responsive and sympathetic chatbot. Furthermore, the project includes the adoption of a Personalized Intervention strategy, in which chatbots are designed to personalize responses by merging NLP algorithms with specific user profiles, treatment history, and emotional states. The synergy between NLP and personalized medicine principles is critical for tailoring chatbot interactions to each user's demands and conditions, hence increasing the efficacy of mental health care. A detailed survey corroborated this synergy, revealing a remarkable 20% increase in patient satisfaction levels and a 30% reduction in workloads for healthcare practitioners. The poll, which focused on health outcomes and was administered to both patients and healthcare professionals, highlights the improved efficiency and favorable influence on the broader healthcare ecosystem.

Keywords: natural language processing, artificial intelligence, healthcare communication, electronic health records, patient care

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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: Raj Chavan

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At present, the United States is home to more than 14,000 Water Resource Recovery Facilities (WRRFs), of which approximately 35% have implemented nutrient limits of some kind. These WRRFs contribute 10 to 15% of the total nutrient burden to surface rivers in the United States and account for approximately 1% of total power demand and 2% of total greenhouse gas emissions (GHG). There are several factors that have influenced the development of densification technologies in the direction of more compact and energy-efficient nutrient removal processes. Prior to surface water discharge, existing facilities that necessitate capacity expansion or biomass densification for greater treatability within the same footprint are being subjected to stricter nutrient removal requirements. Densification of activated sludge as a method for nutrient removal and process intensification at WRRFs has garnered considerable attention in recent times. The biological processes take place within the aerobic sediment granules, which form the basis of the technology. The possibility of generating granular sludge through continuous (or conventional) activated sludge processes (CAS) or densification of biomass through the transfer of activated sludge flocs to a denser biomass aggregate as an exceptionally efficient intensification technique has generated considerable interest. This presentation aims to furnish attendees with a foundational comprehension of densification through the illustration of practical concerns and insights. The subsequent subjects will be deliberated upon. What are some potential techniques for producing and preserving densified granules? What processes are responsible for the densification of biological flocs? How do physical selectors contribute to the process of biological flocs becoming denser? What viable strategies exist for the management of densified biological flocs, and which design parameters of physical selection influence the retention of densified biological flocs? determining operational solutions for floc and granule customization in order to meet capacity and performance objectives? The answers to these pivotal questions will be derived from existing full-scale treatment facilities, bench-scale and pilot-scale investigations, and existing literature data. By the conclusion of the presentation, the audience will possess a fundamental comprehension of the densification concept and its significance in attaining effective effluent treatment. Additionally, case studies pertaining to the design and operation of densification procedures will be incorporated into the presentation.

Keywords: densification, intensification, nutrient removal, granular sludge

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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: A. Noll, J. Roth, M. Scholz

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The importance of written language in a democratic society is non-controversial. Students with physical, learning, cognitive or developmental disabilities often have difficulties in understanding information which is presented in written language only. These students suffer from obstacles in diverse domains. In order to reduce such barriers in educational as well as in out-of-school areas, access to written information must be facilitated. Readability can be enhanced by linguistic simplifications like the application of easy-to-read language. Easy-to-read language shall help people with disabilities to participate socially and politically in society. The authors state, for example, that only short simple words should be used, whereas the occurrence of complex sentences should be avoided. So far, these guidelines were not empirically proved. Another way to reduce reading barriers is the use of visual support, for example, symbols. A symbol conveys, in contrast to a photo, a single idea or concept. Little empirical data about the use of symbols to foster the readability of texts exist. Nevertheless, a positive influence can be assumed, e.g., because of the multimedia principle. It indicates that people learn better from words and pictures than from words alone. A qualitative Interview and Eye-Tracking-Study, which was conducted by the authors, gives cause for the assumption that besides the illustration of single words, the visualization of complete sentences may be helpful. Thus, the effect of photos, which illustrate the content of complete sentences, is also investigated in this study. This leads us to the main research question which was focused on: Does the use of easy-to-read language and/or enriching text with symbols or photos facilitate pupils’ comprehension of learning tasks? The sample consisted of students with learning difficulties (N = 144) and students without SEN (N = 159). The students worked on the tasks, which dealt with introducing fractions, individually. While experimental group 1 received a linguistically simplified version of the tasks, experimental group 2 worked with a variation which was linguistically simplified and furthermore, the keywords of the tasks were visualized by symbols. Experimental group 3 worked on exercises which were simplified by easy-to-read-language and the content of the whole sentences was illustrated by photos. Experimental group 4 received a not simplified version. The participants’ reading ability and their IQ was elevated beforehand to build four comparable groups. There is a significant effect of the different setting on the students’ results F(3,140) = 2,932; p = 0,036*. A post-hoc-analyses with multiple comparisons shows that this significance results from the difference between experimental group 3 and 4. The students in the group easy-to-read language plus photos worked on the exercises significantly more successfully than the students who worked in the group with no simplifications. Further results which refer, among others, to the influence of the students reading ability will be presented at the ICERI 2018.

Keywords: inclusive education, mathematics education, easy-to-read language, photos, symbols, special educational needs

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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: Brooke Sweeney, David White, Felix Amparano, Nick A. Clark, Amy R. Beck, Mathew Lindquist, Lora Edwards, Julie Vandal, Jennifer Lisondra, Katie Cox, Renee Arensberg, Allen Cummins, Jazmine Cedeno, Jason D. Fraser, Kelsey Dean, Helena H. Laroche, Cristina Fernandez

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Background: National organizations call for standardized pre-surgical requirements and education to optimize postoperative outcomes. Since 2017 our surgery program has used defined protocols and educational curricula pre- and post-surgery. In response to patient outcomes, our educational content was refined to include quizzes to assess patient knowledge and surgical preparedness. We aim to optimize adolescent pre-bariatric surgery preparedness by improving overall aggregate pre-surgical assessment performance from 68% to 80% within 12 months. Methods: A multidisciplinary improvement team was developed within the weight management clinic (WMC) of our tertiary care, free-standing children’s hospital. A manual has been utilized since 2017, with limitations in consistent delivery and patient uptake of information. The curriculum has been improved to include quizzes administered during WMC visits prior to bariatric surgery. The initial outcome measure is the pre-surgical quiz score of adolescents preparing for bariatric surgery. Process measure was the number of questions answered correctly to test the questions. Baseline performance was determined by a patient assessment survey of pre-surgical preparedness at patient visits. Plan-Do-Study-Act cycles (PDSA) included: 1) creation and implementation of a refined curriculum, 2) development of 5 new quizzes based upon learning objectives, and 3) improving provider-lead teaching and quiz administration within clinic workflow. Run charts assessed impact over time. Results: A total of 346 quiz questions were administered to 34 adolescents. The outcome measure improved from a baseline mean of 68% to 86% following PDSA 2 cycles, and it was sustained. Conclusion/Implication: Patient/family comprehension of surgical preparedness improved with standardized education via team member-led teaching and assessment using quizzes during pre-surgical clinic visits. The next steps include launching redesigned teaching materials with modules correlated to quizzes and assessment of comprehension and outcomes post-surgically.

Keywords: bariatric surgery, adolescent, clinic, pre-bariatric training

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Authors: Geoffrey A. Wright

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In an attempt to address shortcomings revealed in international assessments and lamented in legislation, many schools are reducing or eliminating elective courses, applying the rationale that replacing "non-essential" subjects with core subjects, such as mathematics and language arts, will better position students in the global market. However, there is evidence that systematically pairing a core subject with another complementary subject may lead to greater overall learning in both subjects. In this paper, we outline the methods and preliminary findings from a study we conducted analyzing the influence learning programming has on student mathematical comprehension and ability. The purpose of this research is to demonstrate in what ways two subjects might complement each other, and to better understand the principles and conditions that encourage what we call lateral transfer, the synergistic effect that occurs when a learner studies two complementary subjects.

Keywords: programming, engineering, technology, complementary subjects

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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: Flavio Campos

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This paper describes an implementation of a STEM curriculum program using robotics as a technological resource at a private school in Brazil. Emphasized the pedagogic and didactic aspects and brings a discussion about STEM curriculum and the perspective of using robotics and the relation between curriculum, science and technologies into the learning process. The results indicate that STEM curriculum integration with robotics as a technological resource in K-12 students learning process has complex aspects, such as relation between time/space, the development of educators and the relation between robotics and other subjects. Therefore, the comprehension of these aspects could indicate some steps that we should consider when integrating STEM basis and robotics into curriculum, which can improve education for science and technology significantly.

Keywords: STEM curriculum, educational robotics, constructionist approach, education and technology

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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: ShuPei Wang, Yina Patterson

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This article outlines strategies for improving oral expression to advance proficiency in speaking and listening skills through structured argumentation. The objective is to empower students to effectively use the target language to express opinions and construct compelling arguments. This empowerment is achieved by honing learners' debating and questioning skills, which involves increasing their familiarity with vocabulary and phrases relevant to debates and deepening their understanding of the cultural context surrounding pertinent issues. Through this approach, students can enhance their ability to articulate complex concepts and discern critical points, surpassing superficial comprehension and enabling them to engage in the target language actively and competently.

Keywords: debate, teaching and materials design, spoken expression, listening proficiency, critical thinking

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Authors: Najwa Alsayed Omar

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With the increasing popularity of the Internet, online reading has become an essential source for EFL readers. Using strategies to comprehend information on online reading texts play a crucial role in students’ academic success. Metacognitive reading strategies are effective factors that enhance EFL learners reading comprehension. This study aimed at exploring the use of online metacognitive reading strategies by postgraduate Libyan EFL students. Quantitative data was collected using the Survey of Online Reading Strategies (OSORS). The findings revealed that the participants were moderate users of metacognitive online reading strategies. Problem solving strategies were the most frequently reported used strategies, while support reading strategies were the least. The five most and least frequently reported strategies were identified. Based on the findings, some future research recommendations were presented.

Keywords: metacognitive strategies, online reading, online reading strategies, postgraduate students

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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: Shirly May Balais

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This study aims to evaluate the effects of vocabulary instruction in improving the students’ learning in science. The teacher-researcher utilized the vocabulary instructional materials in enriching the science vocabulary of grade four learners. The students were also given an achievement test to determine the effects of vocabulary instructional materials. The assessment indicated that students had shown improvement in comprehension and science literacy. This also helps the students to grasp, understand, and communicate appropriate science concepts and the integration of imagery makes learning science fun. In this research, descriptive qualitative methods and observation interviews were used to describe the effects of using vocabulary instructional materials in improving the science vocabulary of grade four learners. The students’ perceptions were studied, analyzed, and interpreted qualitatively.

Keywords: instruction, learning, science, vocabulary

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Authors: Jihee Jang, Seowon Yoon, Gaeun Son, Minjung Kang, Joon Yeon Choeh, Kee-Hong Choi

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Background: Self-report multiple choice questionnaires have been widely utilized to quantitatively measure one’s personality and psychological constructs. Despite several strengths (e.g., brevity and utility), self-report multiple-choice questionnaires have considerable limitations in nature. With the rise of machine learning (ML) and Natural language processing (NLP), researchers in the field of psychology are widely adopting NLP to assess psychological constructs to predict human behaviors. However, there is a lack of connections between the work being performed in computer science and that psychology due to small data sets and unvalidated modeling practices. Aims: The current article introduces the study method and procedure of phase II, which includes the interview questions for the five-factor model (FFM) of personality developed in phase I. This study aims to develop the interview (semi-structured) and open-ended questions for the FFM-based personality assessments, specifically designed with experts in the field of clinical and personality psychology (phase 1), and to collect the personality-related text data using the interview questions and self-report measures on personality and psychological distress (phase 2). The purpose of the study includes examining the relationship between natural language data obtained from the interview questions, measuring the FFM personality constructs, and psychological distress to demonstrate the validity of the natural language-based personality prediction. Methods: The phase I (pilot) study was conducted on fifty-nine native Korean adults to acquire the personality-related text data from the interview (semi-structured) and open-ended questions based on the FFM of personality. The interview questions were revised and finalized with the feedback from the external expert committee, consisting of personality and clinical psychologists. Based on the established interview questions, a total of 425 Korean adults were recruited using a convenience sampling method via an online survey. The text data collected from interviews were analyzed using natural language processing. The results of the online survey, including demographic data, depression, anxiety, and personality inventories, were analyzed together in the model to predict individuals’ FFM of personality and the level of psychological distress (phase 2).

Keywords: personality prediction, psychological distress prediction, natural language processing, machine learning, the five-factor model of personality

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Authors: Devleminck Steven, Debackere Boris

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This research is about the ways artists and scientists deal with (and endure) new meaning and comprehend and construct the world. The project reflects on the intense connection between comprehension and construction and their place of creation – the ‘locus of action’. It seeks to define a liquid form of understanding and analysis capable of approaching our complex liquid world as discussed by Zygmunt Bauman. The aim is to establish a multi-viewpoint theoretical approach based on the dynamic concept of the Flâneur as introduced by Baudelaire, replacing single viewpoint categorization. This is coupled with the concept of thickening as proposed by Clifford Geertz with its implication of interaction between multi-layers of meaning. Here walking and looking is introduced as a method or strategy, a model or map, providing a framework of understanding in conditions of hybridity and change.

Keywords: action, art, liquid, locus, negotiation, place, science

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Authors: António Fiúza, Aurora Futuro, Joana Monteiro, Joaquim Góis

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Lepidolite is an important lithium mineral that, to the author’s best knowledge, has not been used to produce lithium hydroxide, which is necessary for energy conversion to electric vehicles. Alkaline leaching of lithium concentrates allows the establishment of a production diagram avoiding most of the environmental drawbacks that are associated with the usage of acid reagents. The tested processes involve a pretreatment by digestion at high temperatures with additives, followed by leaching at hot atmospheric pressure. The solutions obtained must be compatible with solutions from the leaching of spodumene concentrates, allowing the development of a common treatment diagram, an important accomplishment for the feasible exploitation of Portuguese resources. Statistical programming and interpretation techniques minimize the laboratory effort required by conventional approaches and allow phenomenological comprehension.

Keywords: alkaline leaching, lithium, research design, statistical interpretation

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Authors: Ramune Kasperaviciene, Jurgita Motiejuniene, Dalia Venckiene

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Familiarising students with strategies for transferring cultural meanings (intertextual units, culture-specific idioms, culture-specific items, etc.) should be part of a comprehensive translator training programme. The present paper focuses on strategies for transferring such meanings into other languages and explores possibilities for introducing these methods and practice to translation students. The authors (university translation teachers) analyse the means of transferring cultural meanings from English into Lithuanian in a specific travel book, attribute these means to theoretically grounded strategies, and make calculations related to the frequency of adoption of specific strategies; translation students are familiarised with concepts and methods related to transferring cultural meanings and asked to put their theoretical knowledge into practice, i.e. interpret and translate certain culture-specific items from the same source text, and ground their decisions on theory; the comparison of the strategies employed by the professional translator of the source text (as identified by the authors of this study) and by the students is made. As a result, both students and teachers gain valuable experience, and new practices of conducting translation classes for a specific purpose evolve. Conclusions highlight the differences and similarities of non-professional and professional choices, summarise the possibilities for introducing methods of transferring cultural meanings to students, and round up with specific considerations of the impact of theoretical knowledge and the degree of experience on decisions made in the translation process.

Keywords: cultural meanings, culture-specific items, strategies for transferring cultural meanings, translator training

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Authors: Kateriina Rannula, Elle Sõrmus, Siret Piirsalu

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Mixed generation classroom is a phenomenon that current higher education establishments are faced with daily trying to meet the needs of modern labor market with its emphasis on lifelong learning and retraining. Representatives of mainly X and Y generations in one classroom acquiring higher education is a challenge to lecturers considering all the characteristics that differ one generation from another. The importance of outlining different strategies and considering the needs of the students lies in the necessity for everyone to acquire the maximum of the provided knowledge as well as to understand each other to study together in one classroom and successfully cooperate in future workplaces. In addition to different generations, there are also learners with different native languages which have an impact on reading and understanding texts in third languages, including possible translation. Current research aims to investigate, describe and compare reading strategies among the representatives of generation X and Y. Hypotheses were formulated - representatives of generation X and Y use different reading strategies which is also different among first and third year students of the before mentioned generations. Current study is an empirical, qualitative study. To achieve the aim of the research, relevant literature was analyzed and a semi-structured questionnaire conducted among the first and third year students of Tallinn Health Care College. Questionnaire consisted of 25 statements on the text reading strategies, 3 multiple choice questions on preferences considering the design and medium of the text, and three open questions on the translation process when working with a text in student’s third language. The results of the questionnaire were categorized, analyzed and compared. Both, generation X and Y described their reading strategies to be 'scanning' and 'surfing'. Compared to generation X, first year generation Y learners valued interactivity and nonlinear texts. Students frequently used strategies of skimming, scanning, translating and highlighting together with relevant-thinking and assistance-seeking. Meanwhile, the third-year generation Y students no longer frequently used translating, resourcing and highlighting while Generation X learners still incorporated these strategies. Knowing about different needs of the generations currently inside the classrooms and on the labor market enables us with tools to provide sustainable education and grants the society a work force that is more flexible and able to move between professions. Future research should be conducted in order to investigate the amount of learning and strategy- adoption between generations. As for reading, main suggestions arising from the research are as follows: make a variety of materials available to students; allow them to select what they want to read and try to make those materials visually attractive, relevant, and appropriately challenging for learners considering the differences of generations.

Keywords: generation X, generation Y, learning strategies, reading strategies

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Authors: Kohtaroh Miyamoto

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As enterprise computing becomes more and more complex, the costs and technical challenges of IT system maintenance and support are increasing rapidly. One popular approach to managing IT system maintenance is to prepare and use an FAQ (Frequently Asked Questions) system to manage and reuse systems knowledge. Such an FAQ system can help reduce the resolution time for each service incident ticket. However, there is a major problem where over time the knowledge in such FAQs tends to become outdated. Much of the knowledge captured in the FAQ requires periodic updates in response to new insights or new trends in the problems addressed in order to maintain its usefulness for problem resolution. These updates require a systematic approach to define the exact portion of the FAQ and its content. Therefore, we are working on a novel method to hierarchically structure the FAQ and automate the updates of its structure and content. We use structured information and the unstructured text information with the timelines of the information in the service incident tickets. We cluster the tickets by structured category information, by keywords, and by keyword modifiers for the unstructured text information. We also calculate an urgency score based on trends, resolution times, and priorities. We carefully studied the tickets of one of our projects over a 2.5-year time period. After the first 6 months, we started to create FAQs and confirmed they improved the resolution times. We continued observing over the next 2 years to assess the ongoing effectiveness of our method for the automatic FAQ updates. We improved the ratio of tickets covered by the FAQ from 32.3% to 68.9% during this time. Also, the average time reduction of ticket resolution was between 31.6% and 43.9%. Subjective analysis showed more than 75% reported that the FAQ system was useful in reducing ticket resolution times.

Keywords: FAQ system, resolution time, service incident tickets, IT system maintenance

Procedia PDF Downloads 316

Authors: Fiúza A., Góis J. Leite M., Braga H., Lima A., Jorge P., Moutela P., Martins L., Futuro A.

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Lepidolite is an important lithium mineral that, to the author’s best knowledge, has not been used to produce lithium hydroxide, necessary for energy conversion to electric vehicles. Alkaline leaching of lithium concentrates allows the establishment of a production diagram avoiding most of the environmental drawbacks that are associated with the usage of acid reagents. The tested processes involve a pretreatment by digestion at high temperatures with additives, followed by leaching at hot atmospheric pressure. The solutions obtained must be compatible with solutions from the leaching of spodumene concentrates, allowing the development of a common treatment diagram, an important accomplishment for the feasible exploitation of Portuguese resources. Statistical programming and interpretation techniques are used to minimize the laboratory effort required by conventional approaches and also allow phenomenological comprehension.

Keywords: artificial intelligence, tailings free process, ferroelectric electrolyte battery, life cycle assessment

Procedia PDF Downloads 103

Authors: Suratno

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Metacognition thinking skills should be developed early on in learning. The aim of research builds metacognition thinking skills through collaborative learning with self-evaluation. Approach to action research study involving 32 middle school students in Jember Indonesia. Indicators metacognition skills consist of planning, information management strategies, comprehension monitoring, and debugging strategies. Data were analyzed by t test and analysis of instructional videos. Results of the study here were significant differences in metacognition skills before and after the implementation of collaborative learning with self-evaluation. Analysis instructional video showing the difference artifacts of student learning activities to learning before and after implementation of collaborative learning with self-evaluation. Self-evaluation makes students familiar practice thinking skills metacognition.

Keywords: metacognition, collaborative, evaluation, thinking skills

Procedia PDF Downloads 340

Authors: Geta Bekalu Belayneh, Solmoi Park

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This study examines the role of slag in the process of hydration and carbonation of carbonation-cured slag cement. Carbonation-cured slag-blended cement paste samples were prepared with varying slag percentages of 0%, 10%, 30%, and 50%. The curing process lasted for a maximum of 28 days. The findings demonstrated that the carbonation depth increased as the curing period was extended, and a larger slag percentage promoted a more extensive penetration of carbonation. The degree of belite reaction was greatly enhanced in the slag-blended cement, resulting in an increased ability to bind CO₂ in the blended cement. These findings enhance comprehension of the behaviour of blended cement produced through carbonation-curing, facilitating the advancement of more environmentally friendly and long-lasting concrete constructions.

Keywords: carbonation curing, blast furnace slag, characterization, Portland cement

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Authors: Zsuzsa Szakaly

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Several constitutions have explicit or implicit eternity clauses in the European Union, their classic roles were analyzed so far, albeit there are new possibilities emerging in relation to the identity of the constitutions of the Member States. The aim of the study is to look at the practice of the Constitutional Courts of the Member States in detail regarding eternity clauses where limiting constitutional amendment has practical bearing, and to examine the influence of such practice on Europeanization. There are some states that apply explicit eternity clauses embedded in the text of the constitution, e.g., Italy, Germany, and Romania. In other states, the Constitutional Court 'unearthed' the implicit eternity clauses from the text of the basic law, e.g., Slovakia and Croatia. By using comparative analysis to examine the explicit or implicit clauses of the concerned constitutions, taking into consideration the new trends of the judicial opinions of the Member States and the fresh scientific studies, the main questions are: How to wield the double-edged sword of eternity clauses? To support European Integration or to support the sovereignty of the Member State? To help Europeanization or to act against it? Eternity clauses can easily find themselves between a rock and a hard place, the law of the European Union and the law of a Member State, with more possible interpretations. As more and more Constitutional Courts started to declare elements of their Member States’ constitutional identities, these began to interfere with the eternity clauses. Will this trend eventually work against Europeanization? As a result of the research, it can be stated that a lowest common denominator exists in the practice of European Constitutional Courts regarding eternity clauses. The chance of a European model and the possibility of this model influencing the status quo between the European Union and the Member States will be examined by looking at the answers these courts have found so far.

Keywords: constitutional court, constitutional identity, eternity clause, European Integration

Procedia PDF Downloads 128

Authors: Mian Huang, Chi Ma, Junyu Lin, William Lu

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Introduction: Bone health attracts more attention recently and an intelligent question and answer (QA) chatbot for osteoporosis is helpful for science popularization. With Generative Pretrained Transformer (GPT) technology developing, we build an osteoporosis corpus dataset and then fine-tune LLaMA, a famous open-source GPT foundation large language model(LLM), on our self-constructed osteoporosis corpus. Evaluated by clinical orthopedic experts, our fine-tuned model outperforms vanilla LLaMA on osteoporosis QA task in Chinese. Three-dimensional quantitative computed tomography (QCT) measured bone mineral density (BMD) is considered as more accurate than DXA for BMD measurement in recent years. We develop an automatic Phantom-less QCT(PL-QCT) that is more efficient for BMD measurement since no need of an external phantom for calibration. Combined with LLM on osteoporosis, our PL-QCT provides efficient and accurate BMD measurement for our chatbot users. Material and Methods: We build an osteoporosis corpus containing about 30,000 Chinese literatures whose titles are related to osteoporosis. The whole process is done automatically, including crawling literatures in .pdf format, localizing text/figure/table region by layout segmentation algorithm and recognizing text by OCR algorithm. We train our model by continuous pre-training with Low-rank Adaptation (LoRA, rank=10) technology to adapt LLaMA-7B model to osteoporosis domain, whose basic principle is to mask the next word in the text and make the model predict that word. The loss function is defined as cross-entropy between the predicted and ground-truth word. Experiment is implemented on single NVIDIA A800 GPU for 15 days. Our automatic PL-QCT BMD measurement adopt AI-associated region-of-interest (ROI) generation algorithm for localizing vertebrae-parallel cylinder in cancellous bone. Due to no phantom for BMD calibration, we calculate ROI BMD by CT-BMD of personal muscle and fat. Results & Discussion: Clinical orthopaedic experts are invited to design 5 osteoporosis questions in Chinese, evaluating performance of vanilla LLaMA and our fine-tuned model. Our model outperforms LLaMA on over 80% of these questions, understanding ‘Expert Consensus on Osteoporosis’, ‘QCT for osteoporosis diagnosis’ and ‘Effect of age on osteoporosis’. Detailed results are shown in appendix. Future work may be done by training a larger LLM on the whole orthopaedics with more high-quality domain data, or a multi-modal GPT combining and understanding X-ray and medical text for orthopaedic computer-aided-diagnosis. However, GPT model gives unexpected outputs sometimes, such as repetitive text or seemingly normal but wrong answer (called ‘hallucination’). Even though GPT give correct answers, it cannot be considered as valid clinical diagnoses instead of clinical doctors. The PL-QCT BMD system provided by Bone’s QCT(Bone’s Technology(Shenzhen) Limited) achieves 0.1448mg/cm2(spine) and 0.0002 mg/cm2(hip) mean absolute error(MAE) and linear correlation coefficient R2=0.9970(spine) and R2=0.9991(hip)(compared to QCT-Pro(Mindways)) on 155 patients in three-center clinical trial in Guangzhou, China. Conclusion: This study builds a Chinese osteoporosis corpus and develops a fine-tuned and domain-adapted LLM as well as a PL-QCT BMD measurement system. Our fine-tuned GPT model shows better capability than LLaMA model on most testing questions on osteoporosis. Combined with our PL-QCT BMD system, we are looking forward to providing science popularization and early morning screening for potential osteoporotic patients.

Keywords: GPT, phantom-less QCT, large language model, osteoporosis

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Authors: Deepika Verma, Runa Sarkar

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One of the prominent debates in the social entrepreneurship literature has been to establish whether entrepreneurial work for social well-being by for-profit organizations can be classified as social entrepreneurship or not. Of late, the scholarship has reached a consensus. It concludes that there seems little sense in confining social entrepreneurship to just non-profit organizations. Boosted by this research, increasingly a lot of businesses engaged in filling the social infrastructure gaps in developing countries are calling themselves social enterprise. These organizations are diverse in their ownership, size, objectives, operations and business models. The lack of a comprehensive definition of social enterprise leads to three issues. Firstly, researchers may face difficulty in creating a database for social enterprises because the choice of an entity as a social enterprise becomes subjective or based on some pre-defined parameters by the researcher which is not replicable. Secondly, practitioners who use ‘social enterprise’ in their vision/mission statement(s) may find it difficult to adjust their business models accordingly especially during the times when they face the dilemma of choosing social well-being over business viability. Thirdly, social enterprise and social entrepreneurship attract a lot of donor funding and venture capital. In the paucity of a comprehensive definitional guide, the donors or investors may find assigning grants and investments difficult. It becomes necessary to develop an exhaustive and objective definition of social enterprise and examine whether the understanding of the academicians and practitioners about social enterprise match. This paper develops a dictionary of words often associated with social enterprise or (and) social entrepreneurship. It further compares two lexicographic definitions of social enterprise imputed from the abstracts of academic journal papers and trade publications extracted from the EBSCO database using the ‘tm’ package in R software.

Keywords: EBSCO database, lexicographic definition, social enterprise, text mining

Procedia PDF Downloads 372