• Journal of Korean Medical classics
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• v.34 no.1
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• pp.67-87
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• 2021

Objectives :The purpose of this paper is to evaluate the significance of the 『Joseonbogeonsa』 by examining North Korea's perspective in its documentation of the history of medicine, and to further understand North Korea's perception of Korean Traditional Medicine. Methods : The focus of examination was on the perspective of historical description as shown in the first chapter of the 『Joseonbogeonsa』. Its unique features were made clear through comparison with historical texts of medicine of South Korea such as the 『History of Medicine in Korea』, and the 『History of Korean Medicine』. In order to grasp the current of historical research in North Korea, various Traditional Medicine related dictionaries and academic journals of North Korea along with the 『Joseontongsa』 were examined. Results & Conclusions : The historical views of the 『Joseonbogeonsa』 could be categorized as nation-focused, materialistic, and nationalistic. These are core elements that make up North Korea's self-reliance ideology, which influenced the interpretation of medical facts. While the text is valuable in that it introduced new historical material along with its interpretation, and argued for a more independent development of Traditional Medicine, its limitation of interpreting historical material from a conclusive, pre-determined standpoint cannot be overlooked. The North Korean 'Goryeo Medicine' is defined by its historical nature rather than academic characteristics, and its significance is determined by its clinical efficacy rather than theoretical value.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.333-342
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• 2021

In this study, we analyzed the vocabulary, lemmas, keywords, and n-grams in 『Treasure Island』 to identify certain linguistic features of this British-American children's adventure novel. The current study found that, contrary to the popular claim that frequently-used words are important and essential to a story, the set of frequently-used words in 『Treasure Island』 were mostly function words and proper nouns that were not directly related to the plot found in 『Treasure Island』. We also ascertained that a list of keywords using a statistical method making use of a corpus program was not good enough to surmise the story of 『Treasure Island』. However, we managed to extract 30 keywords through the first quantitative keyword analysis and then a second qualitative keyword analysis. We also carried out a series of n-gram analyses and were able to discover lexical bundles that were preferred and frequently used by the author of 『Treasure Island』. We hope that the results of this study will help spread this knowledge among British-American children's literature as well as to further put forward corpus stylistic theory.

• Journal of Digital Convergence
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• v.19 no.4
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• pp.291-303
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• 2021

The study tried to examine the characteristics of transcription culture on YouTube through narrative analysis methods. The study found five meaningful features in YouTube's transcription culture. YouTube's transcription culture was first characterized by efficient writing and learning skills. Second, there was a characteristic of a transcription to read and understand text more deeply. Third, it had the characteristics of five strategies to advance my writing. Fourth, YouTubers had time to self-heal and comfort through transcription. Fifth, YouTube's transcription culture has expanded and developed into left-handed writing and digital writing. The characteristics of these YouTubers' transcription culture are expected to enrich the transcription culture that has been handed down for many years.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.43-50
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• 2022

For high-quality education of the modern generation of students, forms of organizing the educational process and the latest methods of obtaining knowledge that differ from traditional ones are necessary. The importance of multimedia teaching tools is shown, which are promising and highly effective tools that allow the teacher not only to present an array of information in a larger volume than traditional sources of information, but also to include text, graphs, diagrams, sound, animation, video, etc. in a visually integrated form. Approaches to the classification of multimedia learning tools are revealed. Special features, advantages of multimedia, expediency of use and their disadvantages are highlighted. A comprehensive analysis of the capabilities of multimedia teaching tools gave grounds for identifying the didactic functions that they perform. Several areas of multimedia application are described. Multimedia technologies make it possible to implement several basic methods of pedagogical activity, which are traditionally divided into active and passive principles of student interaction with the computer, which are revealed in the article. Important conditions for the implementation of multimedia technologies in the educational process are indicated. The feasibility of using multimedia in education is illustrated by examples. Of particular importance in education are game forms of learning, in the implementation of which educational elements based on media material play an important role. The influence of the game on the development of attention by means of works of media culture, which are very diverse in form and character, is shown. The importance of the role of multimedia in student education is indicated. In the educational process of multimedia students, a number of educational functions are implemented, which are presented in the article. Recommendations for using multimedia are given.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.67-80
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• 2023

Rice is an important food crop for most of the population in Nowadays, psychologists consider social media an important tool to examine mental disorders. Among these disorders, depression is one of the most common yet least cured disease Since abundant of writers having extensive followers express their feelings on social media and depression is significantly increasing, thus, exploring the literary text shared on social media may provide multidimensional features of depressive behaviors: (1) Background: Several studies observed that depressive data contains certain language styles and self-expressing pronouns, but current study provides the evidence that posts appearing with self-expressing pronouns and depressive language styles contain high emotional temperatures. Therefore, the main objective of this study is to examine the literary cyber writers' posts for discovering the symptomatic signs of depression. For this purpose, our research emphases on extracting the data from writers' public social media pages, blogs, and communities; (3) Results: To examine the emotional temperatures and sentences usage between depressive and not depressive groups, we employed the SentiStrength algorithm as a psycholinguistic method, TF-IDF and N-Gram for ranked phrases extraction, and Latent Dirichlet Allocation for topic modelling of the extracted phrases. The results unearth the strong connection between depression and negative emotional temperatures in writer's posts. Moreover, we used Naïve Bayes, Support Vector Machines, Random Forest, and Decision Tree algorithms to validate the classification of depressive and not depressive in terms of sentences, phrases and topics. The results reveal that comparing with others, Support Vectors Machines algorithm validates the classification while attaining highest 79% f-score; (4) Conclusions: Experimental results show that the proposed system outperformed for detection of depression trends in literary cyber writers using sentiment analysis.

• Smart Media Journal
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• v.12 no.6
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• pp.27-34
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• 2023

As Netflix usage has increased due to the COVID-19 pandemic, users' experiences with the service have also increased. Therefore, this study aims to conduct topic modeling analysis based on Netflix review data to explore the changes in Netflix user experience and service before and after the COVID-19 pandemic. We collected Netflix app review data from the Google Play Store using the Google Play Scraper library, and used topic modeling to examine keyword differences between app reviews before and after the pandemic. The analysis revealed four main topics: Netflix app features, Netflix content, Netflix service usage, and Netflix overall reviews. After the pandemic, when user experience increased, users tended to use more diverse and detailed keywords in their reviews. By using Netflix review data to analyze users' opinions, this study shows the changes in user experience of Netflix services before and after the pandemic, which can be used as a guide to strengthen competitiveness in the competitive OTT market.

• Journal of English Language & Literature
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• v.57 no.3
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• pp.515-527
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• 2011

Miss Pettigrew Lives for a Day, Winifred Watson's novel of 1938, is a fairytale in novel form. Set in London of 1938, the story revolves around a one-day adventure of an ill-starred but truthful governess who is granted a second chance. This light-hearted comedy of manners was turned into a film by director Bharat Nalluri in 2008. An Anglo-American collaboration, co-scripted by Simon Beaufoy and David McGee, the film converts Watson's quaint novel into an edged heritage piece that encapsulates the 1930s, the problematic decade between the two World Wars. The film, while sustaining the narrative core of Watson's Cinderella story, attempts to place it firmly within a wider current of the novel's setting or London in 1938, tapping into the major concerns of the interwar years that engage with characters in one way or another. Stylistically, the film presents Art Deco as a main visual idiom to convey the prevailing mood of nihilism and decadence of the day. The setting here takes on significance in that it offers a telling counterpoint to the giddy superficial world of the novel. The 1930s was a highly charged decade under the threat of fascism and the Great Depression, fraught with economic and socio-political tensions and apprehensions. The film makes an explicit reference to the dismal context which is suppressed in the original text. The thirties is, therefore, portrayed as a decade of contradiction. It features gay buoyant festivity, rampant consumerism, and shifting morals and attitudes towards love, marriage and sexuality. Yet lurking beneath the surface glamour are the symptoms of crises and the deep-seated anxieties on the eve of World War II. In this way, Watson's novel of manners has been recreated into a defining film on the 1930s with its period feel propped by the atmospheric lighting, the exuberant Jazz score, and the splendid Art Deco costume and production design.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.101-112
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• 2024

Telugu language is considered as fourth most used language in India especially in the regions of Andhra Pradesh, Telangana, Karnataka etc. In international recognized countries also, Telugu is widely growing spoken language. This language comprises of different dependent and independent vowels, consonants and digits. In this aspect, the enhancement of Telugu Handwritten Character Recognition (HCR) has not been propagated. HCR is a neural network technique of converting a documented image to edited text one which can be used for many other applications. This reduces time and effort without starting over from the beginning every time. In this work, a Unicode based Handwritten Character Recognition(U-HCR) is developed for translating the handwritten Telugu characters into English language. With the use of Centre of Gravity (CG) in our model we can easily divide a compound character into individual character with the help of Unicode values. For training this model, we have used both online and offline Telugu character datasets. To extract the features in the scanned image we used convolutional neural network along with Machine Learning classifiers like Random Forest and Support Vector Machine. Stochastic Gradient Descent (SGD), Root Mean Square Propagation (RMS-P) and Adaptative Moment Estimation (ADAM)optimizers are used in this work to enhance the performance of U-HCR and to reduce the loss function value. This loss value reduction can be possible with optimizers by using CNN. In both online and offline datasets, proposed model showed promising results by maintaining the accuracies with 90.28% for SGD, 96.97% for RMS-P and 93.57% for ADAM respectively.

• Journal of Preventive Medicine and Public Health
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• v.57 no.1
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• pp.47-54
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• 2024

Objectives: This study was conducted to systematically summarize trends in research concerning patients with coronavirus disease 2019 (COVID-19) as reported in Korean medical journals. Methods: We performed a literature search of KoreaMed from January 2020 to September 2022. We included only primary studies of patients with COVID-19. Two reviewers screened titles and abstracts, then performed full-text screening, both independently and in duplicate. We first identified the 5 journals with the greatest numbers of eligible publications, then extracted data pertaining to the general characteristics, study population attributes, and research features of papers published in these journals. Results: Our analysis encompassed 142 primary studies. Of these, approximately 41.0% reported a funding source, while 3.5% disclosed a conflict of interest. In 2020, 42.9% of studies included fewer than 10 participants; however, by 2022, the proportion of studies with over 200 participants had increased to 40.6%. The most common design was the cohort study (48.6%), followed by case reports/series (35.2%). Only 3 randomized controlled trials were identified. Studies most frequently focused on prognosis (58.5%), followed by therapy/intervention (20.4%). Regarding the type of intervention/exposure, therapeutic clinical interventions comprised 26.1%, while studies of morbidity accounted for 13.4%. As for the outcomes measured, 50.7% of studies assessed symptoms/clinical status/improvement, and 14.1% evaluated mortality. Conclusions: Employing a systematic approach, we examined the characteristics of research involving patients with COVID-19 that was published in Korean medical journals from 2020 onward. Subsequent research should assess not only publication trends over a longer timeframe but also the quality of evidence provided.

• International Journal of Computer Science & Network Security
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• v.24 no.7
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• pp.108-117
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• 2024

The selection and recommendation of a suitable job applicant from the pool of thousands of applications are often daunting jobs for an employer. The recommendation and selection process significantly increases the workload of the concerned department of an employer. Thus, Resume Classification System using the Natural Language Processing (NLP) and Machine Learning (ML) techniques could automate this tedious process and ease the job of an employer. Moreover, the automation of this process can significantly expedite and transparent the applicants' selection process with mere human involvement. Nevertheless, various Machine Learning approaches have been proposed to develop Resume Classification Systems. However, this study presents an automated NLP and ML-based system that classifies the Resumes according to job categories with performance guarantees. This study employs various ML algorithms and NLP techniques to measure the accuracy of Resume Classification Systems and proposes a solution with better accuracy and reliability in different settings. To demonstrate the significance of NLP & ML techniques for processing & classification of Resumes, the extracted features were tested on nine machine learning models Support Vector Machine - SVM (Linear, SGD, SVC & NuSVC), Naïve Bayes (Bernoulli, Multinomial & Gaussian), K-Nearest Neighbor (KNN) and Logistic Regression (LR). The Term-Frequency Inverse Document (TF-IDF) feature representation scheme proven suitable for Resume Classification Task. The developed models were evaluated using F-Score_M, Recall_M, Precission_M, and overall Accuracy. The experimental results indicate that using the One-Vs-Rest-Classification strategy for this multi-class Resume Classification task, the SVM class of Machine Learning algorithms performed better on the study dataset with over 96% overall accuracy. The promising results suggest that NLP & ML techniques employed in this study could be used for the Resume Classification task.