Search results for: topic naming

Authors: Myungsu Lim, William Xiu Shun Wong, Yoonjin Hyun, Chen Liu, Seongi Choi, Dasom Kim, Namgyu Kim

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The amount of real-time data generated through various mass media has been increasing rapidly. In this study, we had performed topic analysis by using the unstructured text data that is distributed through news article. As one of the most prevalent applications of topic analysis, the issue tracking technique investigates the changes of the social issues that identified through topic analysis. Currently, traditional issue tracking is conducted by identifying the main topics of documents that cover an entire period at the same time and analyzing the occurrence of each topic by the period of occurrence. However, this traditional issue tracking approach has limitation that it cannot discover dynamic mutation process of complex social issues. The purpose of this study is to overcome the limitations of the existing issue tracking method. We first derived core issues of each period, and then discover the dynamic mutation process of various issues. In this study, we further analyze the mutation process from the perspective of the issues categories, in order to figure out the pattern of issue flow, including the frequency and reliability of the pattern. In other words, this study allows us to understand the components of the complex issues by tracking the dynamic history of issues. This methodology can facilitate a clearer understanding of complex social phenomena by providing mutation history and related category information of the phenomena.

Keywords: Data Mining, Issue Tracking, Text Mining, topic Analysis, topic Detection, Trend Detection

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Authors: Oumaima Lahmar

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This paper aims to define a structured topography for finance researchers seeking to navigate the body of knowledge in their extrapolation of finance phenomena. To make sense of the body of knowledge in finance, a probabilistic topic modeling approach is applied on 6000 abstracts of academic articles published in three top journals in finance between 1976 and 2020. This approach combines both machine learning techniques and natural language processing to statistically identify the conjunctions between research articles and their shared topics described each by relevant keywords. The topic modeling analysis reveals 35 coherent topics that can well depict finance literature and provide a comprehensive structure for the ongoing research themes. Comparing the extracted topics to the Journal of Economic Literature (JEL) classification system, a significant similarity was highlighted between the characterizing keywords. On the other hand, we identify other topics that do not match the JEL classification despite being relevant in the finance literature.

Keywords: finance literature, textual analysis, topic modeling, perplexity

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Authors: Jake Gonzalez, Tommy Dang

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This paper proposes a temporal graph approach to visualize and analyze the evolution of gene relationships and nomenclature over time. An interactive web-based tool implements this temporal graph, enabling researchers to traverse a timeline and observe coupled dynamics in network topology and naming conventions. Analysis of a real human genomic dataset reveals the emergence of densely interconnected functional modules over time, representing groups of genes involved in key biological processes. For example, the antimicrobial peptide DEFA1A3 shows increased connections to related alpha-defensins involved in infection response. Tracking degree and betweenness centrality shifts over timeline iterations also quantitatively highlight the reprioritization of certain genes’ topological importance as knowledge advances. Examination of the CNR1 gene encoding the cannabinoid receptor CB1 demonstrates changing synonymous relationships and consolidating naming patterns over time, reflecting its unique functional role discovery. The integrated framework interconnecting these topological and nomenclature dynamics provides richer contextual insights compared to isolated analysis methods. Overall, this temporal graph approach enables a more holistic study of knowledge evolution to elucidate complex biology.

Keywords: temporal graph, gene relationships, nomenclature evolution, interactive visualization, biological insights

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Authors: Tzu-I Chiang

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A central question for finite-nonfinite distinction in Mandarin Chinese is how does Mandarin encode temporal information without the grammatical contrast between past and present tense. Moreover, how do L2 learners of Mandarin whose native language is English and whose L1 system has tense morphology, acquire the temporal encoding system in L2 Mandarin? The current study reports preliminary findings on the relationship between topic prominence and the temporal encoding in L1 and L2 Chinese. Oral narratives data from 30 natives and learners of Mandarin Chinese were collected via a film-retell task. In terms of coding, predicates collected from the narratives were transcribed and then coded based on four major verb types: n-degree Statives (quality-STA), point-scale Statives (status-STA), n-atom EVENT (ACT), and point EVENT (resultative-ACT). How native speakers and non-native speakers started retelling the story was calculated. Results of the study show that native speakers of Chinese tend to express Topic Time (TT) syntactically at the topic position; whereas L2 learners of Chinese across levels rely mainly on the default time encoded in the event types. Moreover, as the proficiency level of the learner increases, learners’ appropriate use of the event predicates increased, which supports the argument that L2 development of temporal encoding is affected by lexical aspect.

Keywords: topic prominence, temporal encoding, lexical aspect, L2 acquisition

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

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

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

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Authors: Sadeq Al Yaari, Fayza Alhammadi, Ayman Al Yaari, Montaha Al Yaari, Aayah Al Yaari, Adham Al Yaari, Sajedah Al Yaari, Saleh Al Yami

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Background: There has been a debate in the literature over the years as to whether or not MossTalk Words program fits Arab Broca’s aphasics (BAs) due to that language differences and also the fact that the technique has not yet been used for aphasics with semantic dementia (SD aphasics). Aims: To oversimplify the above mentioned debate slightly for purposes of exposition, the purpose of the present study is to investigate the “usability” of this program as well as pictures and community as therapeutic techniques for both Arab BAs and SD aphasics. Method: The subjects of this study are two Saudi aphasics (53 and 57 years old, respectively). The former suffers from Broca’s aphasia due to a stroke, while the latter suffers from semantic dementia. Both aphasics can speak English and have used the Moss Talk Words program in addition to intensive picture-naming therapeutic sessions for two years. They were tested by one of the researchers four times (a time per six months). The families of the two subjects, in addition to their relatives and friends, played a major part in all therapeutic sessions. Conclusion: Results show that in averages across the entire therapeutic sessions, MossTalk Words program was clearly found more effective in modeling BAs’ pronunciation than that of SD aphasic. Furthermore, picture-naming intensive exercises in addition to the positive role of the community members played a major role in the progress of the two subjects’ performance.

Keywords: moss talk words, program, technique, Broca’s aphasia, semantic dementia, subjects, picture, community

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Authors: Adriana Salgado, Sandra Castaneda, Ivan Perez

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Learning to read and write is a complex process involving several cognitive skills, contextual, and cultural environments. The basis of this development is linguistic skills, such as the ability to name and understand vocabulary, retell a story, phonological awareness, letter knowledge, among others. In children with autism spectrum disorder (ASD), one of the main concerns is related to language disorders. Nevertheless, most of the children with ASD are able to decode written information but have difficulties in reading comprehension. The research of these processes in the Spanish-speaking population is limited. However, the increasing prevalence of this diagnosis (1 in 115 children) in Mexico has implications at different levels. Educational research is an important area of interest in ASD children, such as emergent literacy. Reading and writing expand the possibilities of academic, cultural, and social information access. Taking this information into account, the objective of this research was to identify the relationship between language skills, alphabet knowledge, phonological awareness, and early reading and writing in ASD Spanish-speaking children. The method used for this research was based on tasks that were selected, adapted and in some cases designed to measure initial reading and writing, as well as language skills (naming, receptive vocabulary, and narrative skills), phonological awareness (similar phonological word pairs, beginning sound awareness and spelling) and letter knowledge, in a sample of 45 children (38 boys and 7 girls) with prior diagnosis of ASD. Descriptive analyses, as well as bivariate correlations, cluster analysis, and canonical correspondence, were obtained for the data results. Results showed that variability was large; however, it was possible to characterize the sample in low, medium, and high score groups regarding children performance. The low score group (46.7% of the sample), had a null or deficient performance in language skills and phonological awareness, some could identify up to five letters of the alphabet, showed no early reading skills but they could scribble. The middle score group was characterized by a highly variable performance in different tasks, with better language skills in receptive and naming vocabulary, some narrative, letter knowledge, and phonological awareness (beginning sound awareness) skills. The high score group, (24.4% of the sample) had the best performance in language skills in relation to the sample data, as well as in the rest of the measured skills. Finally, scores were canonically correlated between naming, receptive vocabulary, narrative, phonological awareness, letter knowledge and initial learning of reading and writing skills for the high score group and letter knowledge, naming and receptive vocabulary for the lower score group, which is consistent with previous research in typical and ASD children. In conclusion, the obtained data is consistent with previous studies. Despite large variability, it was possible to identify performance profiles and relations based on linguistic, phonological awareness, and letter knowledge skills. These skills were predictor variables of the initial development of reading and writing. The above has implications for a future program and strategies development that may benefit the acquisition of reading and writing in ASD children.

Keywords: autism, autism spectrum disorders, early literacy, emergent literacy

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Authors: Zhi Liu, Xian Peng, Monika Domanska, Lingyun Kang, Sannyuya Liu

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Massive Open education has become increasingly popular among worldwide learners. An increasing number of course reviews are being generated in Massive Open Online Course (MOOC) platform, which offers an interactive feedback channel for learners to express opinions and feelings in learning. These reviews typically contain subjective emotion and topic information towards the courses. However, it is time-consuming to artificially detect these opinions. In this paper, we propose an emotion-oriented topic detection model to automatically detect the students’ opinioned aspects in course reviews. The known overall emotion orientation and emotional words in each review are used to guide the joint probabilistic modeling of emotion and aspects in reviews. Through the experiment on real-life review data, it is verified that the distribution of course-emotion-aspect can be calculated to capture the most significant opinioned topics in each course unit. This proposed technique helps in conducting intelligent learning analytics for teachers to improve pedagogies and for developers to promote user experiences.

Keywords: Massive Open Online Course (MOOC), course reviews, topic model, emotion recognition, topical aspects

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Authors: Zhifang Liao, Yanbing Li, Li Xu, Yan Zhang, Xiaoping Fan, Jinsong Wu

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Pull Request (PR) is the primary method for code contributions from the external contributors in Github. PR review is an essential part of open source software developments for maintaining the quality of software. Matching a new PR of an appropriate integrator will make the PR review more effective. However, PR and integrator matching are now organized manually in Github. To reduce this cost, we presented an AIPM model to predict highly relevant integrator of incoming PRs. AIPM uses topic model to extract topics from the PRs, and builds a one-to-one correspondence between topics and integrators. Then, AIPM finds the most suitable integrator according to the maximum entry of the topic-document distribution. On average, AIPM can reach a precision of 60%, and even in some projects, can reach a precision of 80%.

Keywords: pull Request, integrator matching, Github, open source project, topic model

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Authors: Bharti Bhandari, Bharati Mehta, Sabyasachi Sircar

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Medical education is advancing in India, with its advancement newer innovations are being incorporated in teaching and assessment methodology. Our study focusses on a teaching innovation that is more student-centric than teacher-centric and is the need of the day. The teaching innovation was carried out in 1st year MBBS students of our institute. Students were assigned control and test groups. Priming was done for the students in the test group with an open-book MCQ based test in a particular topic before delivering formal didactic lecture on that topic. The control group was not assigned any such exercise. This was followed by formal didactic lecture on the same topic. Thereafter, both groups were assessed on the same topic. The marks were compiled and analysed using appropriate statistical tests. Students were also given questionnaire to elicit their views on the benefits of “self-priming”. The mean marks scored in theory assessment by the test group were statistically higher than the marks scored by the controls. According to students’ feedback, the ‘self-priming “process was interesting, helped in better orientation during class-room lectures and better understanding of the topic. They want it to be repeated for other topics with moderate difficulty level. Better performance of the students in the primed group validates the combination of student-centric priming model and didactic lecture as superior to the conventional, teacher-centric methods alone. If this system is successfully followed, the present teacher-centric pedagogy should increasingly give way to student-centric activities where the teacher is only a facilitator.

Keywords: medical education, open-book test, pedagogy, priming

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Authors: Yu Hung Chiang, Hei Chia Wang

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In the academic area, it is important for research to find proper research domain. Many researchers may refer to conference issues to find their interesting or new topics. Furthermore, conferences issues can help researchers realize current research trends in their field and learn about cutting-edge developments in their specialty. However, online published conference information may widely be distributed; it is not easy to be concluded. Many researchers use search engine of journals or conference issues to filter information in order to get what they want. However, this search engine has its limitation. There will still be some issues should be considered; i.e. researchers cannot find the associated topics which may be useful information for them. Hence, use Knowledge Management (KM) could be a way to resolve these issues. In KM, ontology is widely adopted; but most existed ontology construction methods do not consider social information between target users. To effective in academic KM, this study proposes a method of constructing research Topic Maps using Open Directory Project (ODP) and Social Information Processing (SIP). Through catching of social information in conference website: i.e. the information of co-authorship or collaborator, research topics can be associated among related researchers. Finally, the experiments show Topic Maps successfully help researchers to find the information they need more easily and quickly as well as construct associations between research topics.

Keywords: knowledge management, topic map, social information processing, ontology extraction

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Authors: Takahiro Nishigaki, Katsumi Nitta, Takashi Onoda

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In this paper, we present a method of applying Independent Topic Analysis (ITA) to increasing the number of document data. The number of document data has been increasing since the spread of the Internet. ITA was presented as one method to analyze the document data. ITA is a method for extracting the independent topics from the document data by using the Independent Component Analysis (ICA). ICA is a technique in the signal processing; however, it is difficult to apply the ITA to increasing number of document data. Because ITA must use the all document data so temporal and spatial cost is very high. Therefore, we present Incremental ITA which extracts the independent topics from increasing number of document data. Incremental ITA is a method of updating the independent topics when the document data is added after extracted the independent topics from a just previous the data. In addition, Incremental ITA updates the independent topics when the document data is added. And we show the result applied Incremental ITA to benchmark datasets.

Keywords: text mining, topic extraction, independent, incremental, independent component analysis

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Authors: Melissa Vang, Raheyma Khan, Haihua Chen

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The coronavirus disease 2019 (COVID‐19) pandemic has changed people's lives from all over the world. More people have turned to Twitter to engage online and discuss the COVID-19 vaccine. This study aims to present a text mining approach to identify people's attitudes towards the COVID-19 vaccine on Twitter. To achieve this purpose, we collected 54,268 COVID-19 vaccine tweets from September 01, 2020, to November 01, 2020, then the BERT model is used for the sentiment and topic analysis. The results show that people had more negative than positive attitudes about the vaccine, and countries with an increasing number of confirmed cases had a higher percentage of negative attitudes. Additionally, the topics discussed in positive and negative tweets are different. The tweet datasets can be helpful to information professionals to inform the public about vaccine-related informational resources. Our findings may have implications for understanding people's cognitions and feelings about the vaccine.

Keywords: BERT, COVID-19 vaccine, sentiment analysis, topic modeling

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Authors: Smail Boussaadi, Hassina Aliane

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With the rapid growth of scientific literature, it is becoming increasingly challenging for researchers to keep up with the latest findings in their fields. Academic, professional networks play an essential role in connecting researchers and disseminating knowledge. To improve the user experience within these networks, we need effective article recommendation systems that provide personalized content.Current recommendation systems often rely on collaborative filtering or content-based techniques. However, these methods have limitations, such as the cold start problem and difficulty in capturing semantic relationships between articles. To overcome these challenges, we propose a new approach that combines BERTopic (Bidirectional Encoder Representations from Transformers), a state-of-the-art topic modeling technique, with community detection algorithms in a academic, professional network. Experiences confirm our performance expectations by showing good relevance and objectivity in the results.

Keywords: scientific articles, community detection, academic social network, recommender systems, neural topic model

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Authors: Charlene Petersen, Herman Grobler, Karel Botha

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Restorative intervention with adolescents from a family violence context is a much needed resource given the limited access to mental health services in South Africa. In this research article the qualitative component which formed part of a mixed methods design of an overall research study, is discussed. A qualitative case study design was used. This article explores a psycho-education strategy, using a visual creative medium as a method for reconstructing identity in the context of family violence. The aim of this psycho-education strategy was to move away from interventions based on the biomedical model, but focused more on meaning-making about violent traumatic events adolescents have experienced, and to develop more positive, adaptive views about themselves in the present, and experience hope about the future. The research question that was asked was how the meaning, that adolescents from a specific community in South Africa give to family violence, contribute to defining their identity? Twelve participants were purposively selected for the study and included both male and female adolescents with ages ranging from 15 to 18 years from three secondary schools. The strategy was applied over five sessions with the intention to bring about awareness of different selves, identifying and naming the selves, and becoming aware of the configuration of identity that could lead to a redefined identity. The data were thematically and visually analyzed. Through the process of tailoring which forms the basis for reconstruction process, participants could identify the different selves, become aware of how they configure in the field. Through the process of tailoring the different self-parts, the sense of self became more self-cohesive and allowed the individual to become aware of the role of certain. Through identifying and naming the future self and resilient self the participants were able to accomplish some order and meaning in their lives. It provided them with a sense of predictability and an optimistic and hopefulness towards the future. The research findings indicated that this strategy can be used as a method for reconstructing identity in the context of family violence.

Keywords: identity, family violence, self-configuration, reconstructing identity, psycho-education strategy

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Authors: Kadir Özsoy

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Creating a moderately competitive learning environment is believed to have positive effects on student interest and motivation. The best way today to attract young learners to get involved in a fun, competitive learning experience is possible through mobile applications as these learners mostly rely on games and applications on their phones and tablets to have fun, communicate, look for information and study. In this study, a mobile application called ‘QuizUp’ is used to create a specific game topic for elementary level students at Anadolu University Preparatory School. The topic is specially designed with weekly-added questions in accordance with the course syllabus. Students challenge their classmates or randomly chosen opponents to answer questions related to their course subjects. They also chat and post on the topic’s wall in English. The study aims at finding out students’ perceptions towards the use of the application as a classroom and extra-curricular activity through a survey. The study concludes that educational games boost students’ motivation, lead to increased effort, and positively change their studying habits.

Keywords: competitive learning, educational application, effort, motivation 'QuizUp', study habits

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Authors: Francesca di Donato, Sara Trucco

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Green accounting is a growing topic of interest. Indeed, nowadays, most firms affect the environment; therefore, companies are seeking the best way to disclose environmental information. Furthermore, companies are increasingly committed to improving the environment, and the topic is gaining more importance to the public, governments, and policymakers. Green accounting is a type of accounting that considers environmental costs and their impact on the financial performance of firms. Thus, the motivation of the current research is to investigate the state-of-the-art literature on the relationship between green accounting and firm performance since the birth of the topic of green accounting and to investigate gaps in the literature that represent fruitful terrain for future research. In doing so, this study provides a bibliometric literature review of existing evidence related to the link between green accounting and firm performance since 2000. The search, based on the most relevant databases for scientific journals (which are Scopus, Emerald, Web of Science, Google Scholar, and Econlit), returned 1917 scientific articles. The articles were manually reviewed in order to identify only the relevant studies in the field by excluding articles with titles and abstracts out of scope. The final sample was composed of 107 articles. A content analysis was carried out on the final sample of articles; in doing so, a classification system has been proposed. Findings show the most relevant environmental costs and issues considered in previous studies and how green accounting may be linked to the financial and non-financial performance of a firm. The study also offers suggestions for future research in this domain. This study has several practical implications. Indeed, the topic of green accounting may be applied to different sectors and different types of companies. Therefore, this study may help managers to better understand the most relevant environmental information to disclose and how environmental issues may be managed to improve the performance of the firms. Moreover, the bibliometric literature review may be of interest to those stakeholders who are interested in the historical evolution of the topic.

Keywords: bibliometric literature review, firm performance, green accounting, literature review

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Authors: John Goodhue, Xiaonan Wei

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Current legal decisions and policies regarding the naming as artificial intelligence as inventor are reviewed with emphasis on the recent decisions by the European Patent Office regarding the DABUS inventions holding that an artificial intelligence machine cannot be an inventor. Next, a set of hypotheticals is introduced and examined to better understand how artificial intelligence might be used to create or assist in creating new inventions and how application of existing or proposed changes in the law would affect the ability to protect these inventions including due to restrictions on artificial intelligence for being named as inventors, ownership of inventions made by artificial intelligence, and the effects on legal standards for inventiveness or obviousness.

Keywords: Artificial intelligence, innovation, invention, patent

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Authors: Daniel Pinheiro Da Silva Junior, Aline Paes, Daniel De Oliveira, Christiano Lacerda Ghuerren, Marcio Duran

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The Courts of Accounts are institutions responsible for overseeing and point out irregularities of Public Administration expenses. They have a high demand for processes to be analyzed, whose decisions must be grounded on severity laws. Despite the existing large amount of processes, there are several cases reporting similar subjects. Thus, previous decisions on already analyzed processes can be a precedent for current processes that refer to similar topics. Identifying similar topics is an open, yet essential task for identifying similarities between several processes. Since the actual amount of topics is considerably large, it is tedious and error-prone to identify topics using a pure manual approach. This paper presents a tool based on Machine Learning and Natural Language Processing to assists in building a labeled dataset. The tool relies on Topic Modelling with Latent Dirichlet Allocation to find the topics underlying a document followed by Jensen Shannon distance metric to generate a probability of similarity between documents pairs. Furthermore, in a case study with a corpus of decisions of the Rio de Janeiro State Court of Accounts, it was noted that data pre-processing plays an essential role in modeling relevant topics. Also, the combination of topic modeling and a calculated distance metric over document represented among generated topics has been proved useful in helping to construct a labeled base of similar and non-similar document pairs.

Keywords: courts of accounts, data labelling, document similarity, topic modeling

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Authors: Bahor Bahriddinovna Turaeva

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The article provides a structural analysis of the titles of the famous Kyrgyz writer Chingiz Aitmatov’s creative works “The Day Lasts More Than a Hundred Years”, “Doomsday”. The author’s creative purpose in naming the work of art, the role of the elements of the plot, and the composition of the novels in revealing the essence of the title are explained. The criteria that are important in naming the author’s works in different genres are classified, and the titles that mean artistic time and artistic space are studied separately. Chronotope is being concerned as the literary-aesthetic category in world literary studies, expressing the scope of the universe interpretation, the author’s outlook and imagination regarding the world foundation, defining personages, and the composition means of expressing the sequence and duration of the events. A creative comprehension of the chronotope as a means of arranging the work composition, structure and constructing an epic field of the text demands a special approach to understanding the aesthetic character of the work. Since the chronotope includes all the elements of a fictional work, it is impossible to present the plot, composition, conflict, system of characters, feelings, and mood of the characters without the description of the chronotope. In the following development of the scientific-theoretical thought in the world, the chronotope is accepted to be one of the poetic means to demonstrate reality as well as to be a literary process that is basic for the expression of reality in the compositional construction and illustration of the plot relying on the writer’s intention and the ideological conception of the literary work. Literary time enables one to cognate the literary world picture created by the author in terms of the descriptive subject and object of the work. Therefore, one of the topical tasks of modern Uzbek literary studies is to describe historical evidence, event, the life of outstanding people, the chronology of the near past based on the literary time; on the example of the creative works of a certain period, creators or an individual writer are analyzed in separate or comparative-typological aspect.

Keywords: novel, title, chronotope, motive, epigraph, analepsis, structural analysis, plot line, composition

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Authors: M. Ismail, E. Grifell-Tatjé, A. Paz

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A significant discussion on the topic of blockchain as a solution to the issues of intellectual property highlights the relevance that this topic holds. Some experts label this technology as destructive since it holds immense potential to change course of traditional practices. The extent and areas to which this technology can be of use are still being researched. This paper provides an in-depth review on the intellectual property and blockchain technology. Further it explores what makes blockchain suitable for intellectual property, the practical solutions available and the support different governments are offering. This paper further studies the framework of universities in context of its outputs and how can they be streamlined using blockchain technology. The paper concludes by discussing some limitations and future research question.

Keywords: blockchain, decentralization, open innovation, intellectual property, patents, university-industry relationship

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Authors: Anna Wszołek

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For a very long time, the doctor-patient relationship had a paternalistic character. The events of the II World War, as well as fast development of the biotechnology and medicine caused an important change in that relationship. Human beings and their dignity were put in the centre of philosophical and legal debate. The increasing frequency of clinical trials led to the emergence of bioethics, which dealt with the topic of the possibilities and boundaries of such research in relation to individual’s autonomy. Thus, there was a transformation from a paternalistic relationship to a more collaborative one in which the patient has more room for self-determination. Today, patients are more and more aware of their rights and the obligations placed on doctors and the health care system, which is linked to an increase in medical malpractice claims. Unfortunately, these claims are not always justified. There is a strong concentration around the topic of patient’s good, however, at the other side there are doctors who feel, on the example of Poland, they might be easily accused and sued for medical malpractice even though they fulfilled their duties. Such situation may have a negative impact on the quality of health care services and patient’s interests. This research is going to present doctor’s perspective on the topic of medical malpractice allegations. It is supposed to show possible damage to a doctor’s reputation caused by frivolous and weakly justified medical malpractice accusations, as well as means to protect this reputation.

Keywords: doctor's reputation, medical malpractice, personal rights, unjustified allegations

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Authors: Bashaiar Alsanaa

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The advent of new forms of media has always led to a change in the way existing media deliver content. No medium has been replaced by another yet over the course of history. Whether this fact changes with the introduction of new age technology and social media remains to be seen. Snapchat may be the first application, to seriously challenge TV. It is perhaps the new face of television. The individualistic nature of Snapchat, whereby users control who, when, and in what order to watch, assesses user freedom from traditional broadcasters’ control. This study aims to fill the void in research conducted around such topic. The research explores how Snapchat maybe slowly but replacing TV. The study surveys users in Kuwait in order to present an overview of the topic. It also draws a framework through which implications and suggestions for future research may be discussed to better serve the advancement of media research.

Keywords: Kuwait, media, Snapchat, television

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Authors: Muriel Canas-Walker

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Polygamy is a sensitive issue yet a surprisingly popular topic on television. In China, among other palace intrigues dramas, "The Legend of Zhen Huan" stands out in its harsh portrayal of sequestered concubines in the Forbidden City. In the United States the critically acclaimed "Big Love", set in the Mormon community, generated much discussion and controversy, both accademically and on social media. More recently "The Handmaid’s Tale", adapted from the famous novel by Canadian writer Margaret Atwood, also contributed to the topic. All three dramas feature the plight of women caught in a polygamy system and are particularly popular with female audiences. Using Foucault’s theory of power, visual anthropology, and feminist perspective this paper aims at analyzing the treatment of this sensitive topic in the media and its reception. From the seemingly happy sister wives in "Big Love", to the fiercely competitive concubines in "The Legend of Zhen Huan" and the tragically coerced handmaids in "The Handmaid’s Tale", the lives of women in a polygamy system are inspiring to modern audiences. This paper’s objective is to understand how the treatment of polygamy is relevant to these audiences.

Keywords: polygamy, michel foucault, feminism, visual anthropology

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Authors: Aya Salama

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Digital Twin is an emerging research topic that attracted researchers in the last decade. It is used in many fields, such as smart manufacturing and smart healthcare because it saves time and money. It is usually related to other technologies such as Data Mining, Artificial Intelligence, and Machine Learning. However, Human digital twin (HDT), in specific, is still a novel idea that still needs to prove its feasibility. HDT expands the idea of Digital Twin to human beings, which are living beings and different from the inanimate physical entities. The goal of this research was to create a Human digital twin that is responsible for real-time human replies automation by simulating human behavior. For this reason, clustering, supervised classification, topic extraction, and sentiment analysis were studied in this paper. The feasibility of the HDT for personal replies generation on social messaging applications was proved in this work. The overall accuracy of the proposed approach in this paper was 63% which is a very promising result that can open the way for researchers to expand the idea of HDT. This was achieved by using Random Forest for clustering the question data base and matching new questions. K-nearest neighbor was also applied for sentiment analysis.

Keywords: human digital twin, sentiment analysis, topic extraction, supervised machine learning, unsupervised machine learning, classification, clustering

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Authors: Subhra Prosun Paul, Shruti Aggarwal

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Now a days Routing Protocol in Wireless Sensor Network has become a promising technique in the different fields of the latest computer technology. Routing in Wireless Sensor Network is a demanding task due to the different design issues of all sensor nodes. Network architecture, no of nodes, traffic of routing, the capacity of each sensor node, network consistency, service value are the important factor for the design and analysis of Routing Protocol in Wireless Sensor Network. Additionally, internal energy, the distance between nodes, the load of sensor nodes play a significant role in the efficient routing protocol. In this paper, our intention is to analyze the research trends in different routing protocols of Wireless Sensor Network in terms of different parameters. In order to explain the research trends on Routing Protocol in Wireless Sensor Network, different data related to this research topic are analyzed with the help of Web of Science and Scopus databases. The data analysis is performed from global perspective-taking different parameters like author, source, document, country, organization, keyword, year, and a number of the publication. Different types of experiments are also performed, which help us to evaluate the recent research tendency in the Routing Protocol of Wireless Sensor Network. In order to do this, we have used Web of Science and Scopus databases separately for data analysis. We have observed that there has been a tremendous development of research on this topic in the last few years as it has become a very popular topic day by day.

Keywords: analysis, routing protocol, research trends, wireless sensor network

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Authors: Zilola Kozimova

Abstract:

Humans are highly social creatures, and our social surroundings create a large part of our daily experiences. Feeling connected and belonging at school have been studied a lot, especially in the period up to college. The need to feel connected becomes even more vital when people choose to study abroad. The number of published research in the field has increased recently, creating sufficient studies for a systematic literature review. The current study was conducted to find out existing trends and central themes in the field regarding international student connectedness. Using PRISMA 2020 and Shariff et al.’s work as the guidelines, I conducted a systematic literature review of studies regarding international student connectedness in higher education. Three steps of inclusion/exclusion criteria were used to determine the final studies to be included. The results show an increasing trend in the field as the number of related studies drastically rose after 2017. the results showed that there are three phases in the research regarding the connectedness of international students: a rejection period, a sudden increase of interest in the topic, and merging as an essential part of the mental well-being of international students. There is also a change in the themes regarding the topic, as there is a rise in the number of research published regarding international students’ mental health in recent years, connectedness being a sub-topic.

Keywords: international students, connectedness, mental well-being of international students, trends, higher education

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Authors: H. C. Laltleipuii, Lalruatdiki Siakeng

Abstract:

Mizo is a language spoken by the natives of Mizoram in North-East India. The Mizo society is a patriarchal society and hence is encumbered with trails of sexism in its language. Sexist language expresses discrimination on the basis of gender. While women are primarily affected, it is not however limited to just the female gender. This paper focuses on the sexist language that reflects the discrimination of women in the male-dominated, male-centered society of the Mizo. The main purpose of this paper is to emphasize with details, sexism that can be found in three aspects of language: in the naming of animate and inanimate objects or words in general, in the idioms and phrases and proverbs. This study will also take into account the gender neutral terms that are in use in the language.

Keywords: gender, Mizo, patriarchy, sexism

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Authors: Bashaiar Al-Sanaa

Abstract:

Class has always been a vital distinguishing factor among people within any society. Clear borders between social layers; such as royals, nobles, aristocrats, the bourgeoisie, and working class; have been minimized and blurred due to the advent of social media. Unprecedented access to information has played a significant role in teaching different individuals about the nature of other social layers, hence, allowing for imitation and integration. This study aims to fill the void in research conducted on such topic. The research explores how social media may be slowly but surely dissolving apparent and rigid borderlines of social class. In order to present an overview of the topic, the study surveys individuals in Kuwait to measure how using social media changed their views and style of social class. It also draws a framework through which implications and suggestions for future research may be discussed to better serve the advancement of human communication.

Keywords: class, communication, Kuwait, social media

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Authors: Vadim Kulikov

Abstract:

The classical Stroop effect is the phenomenon that it takes more time to name the ink color of a printed word if the word denotes a conflicting color than if it denotes the same color. Over the last 80 years, there have been many variations of the experiment revealing various mechanisms behind semantic, attentional, behavioral and perceptual processing. The Stroop task is known to exhibit asymmetry. Reading the words out loud is hardly dependent on the ink color, but naming the ink color is significantly influenced by the incongruent words. This asymmetry is reversed, if instead of naming the color, one has to point at a corresponding color patch. Another debated aspects are the notions of automaticity and how much of the effect is due to semantic and how much due to response stage interference. Is automaticity a continuous or an all-or-none phenomenon? There are many models and theories in the literature tackling these questions which will be discussed in the presentation. None of them, however, seems to capture all the findings at once. A computational model is proposed which is based on the philosophical idea developed by the author that the mind operates as a collection of different information processing modalities such as different sensory and descriptive modalities, which produce emergent phenomena through mutual interaction and coherence. This is the framework theory where ‘framework’ attempts to generalize the concepts of modality, perspective and ‘point of view’. The architecture of this computational model consists of blocks of neurons, each block corresponding to one framework. In the simplest case there are four: visual color processing, text reading, speech production and attention selection modalities. In experiments where button pressing or pointing is required, a corresponding block is added. In the beginning, the weights of the neural connections are mostly set to zero. The network is trained using Hebbian learning to establish connections (corresponding to ‘coherence’ in framework theory) between these different modalities. The amount of data fed into the network is supposed to mimic the amount of practice a human encounters, in particular it is assumed that converting written text into spoken words is a more practiced skill than converting visually perceived colors to spoken color-names. After the training, the network performs the Stroop task. The RT’s are measured in a canonical way, as these are continuous time recurrent neural networks (CTRNN). The above-described aspects of the Stroop phenomenon along with many others are replicated. The model is similar to some existing connectionist models but as will be discussed in the presentation, has many advantages: it predicts more data, the architecture is simpler and biologically more plausible.

Keywords: connectionism, Hebbian learning, artificial neural networks, philosophy of mind, Stroop

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