Web Articles Research Articles

Dyslexia Articles Unboxed: Analyzing Their Readability Level.

Dyslexia is characterized by difficulties with fluent word recognition, decoding, or spelling, and it has been linked to family history. Given the impact of dyslexia on broad academic activities and well-being, ensuring that information about dyslexia is accessible to affected children and their families is vital. This study aims to assess the readability levels of dyslexia-related websites, with the hypothesis that such websites should be written at an appropriate readability level to accommodate those who may also have reading challenges. This study analyzes the readability of 50 web articles on dyslexia using 6 readability formulas: Flesch-Kincaid Reading Ease, Flesch-Kincaid Grade Level, Gunning Fog Score, Simple Measure of Gobbledygook (SMOG) Index, Coleman Liau Index, and Automated Readability Index. The search term "What is dyslexia" was used on Google. Each article was analyzed using the online calculation website WebFX. The readability goal for these websites was set at fifth grade, a level recommended for patients with reading challenges. The study found that among the 50 websites, the lowest median readability score was 11.8 (corresponding to a 12th-grade level) on the SMOG Index, while the highest scores were 15.5 on both the Gunning Fog Score and the Coleman Liau Index (indicative of college-level readability). Almost none of the websites had scores below a fifth-grade level. Most websites related to dyslexia are too complex. Tools such as readability metrics and sentence restructuring by AI can help make the information more accessible and understandable to the stakeholders.

Research on the Differences Between the Laws Designed to Protect Brands and Traditional Trademark Laws

Brand protection is an important and challenging issue in the contemporary market, as brands are valuable and influential intangible assets that create and sustain competitive advantage. However, there is a lack of a clear and comprehensive legal category that can adequately address the diverse and complex aspects of brand protection. This paper aims to explore how a law designed to protect brands might differ from traditional trademark law, which mainly focuses on the registration and protection of distinctive signs that identify the source and quality of goods or services. The paper adopts a qualitative and comparative approach, using online sources, such as web articles, research papers, and guides, as well as examples of famous brands and cases, to illustrate and analyze the possible ways, characteristics, challenges, and benefits of brand protection. The paper concludes that brand protection is a useful or viable legal category that recognizes and respects the value and importance of brands as intangible assets that create and sustain competitive advantage in the market, adapts and innovates to changing market trends, consumer preferences, and competitive forces, and harmonizes and cooperates with the existing trademark laws and standards across different countries and regions.

Exploring the impact of ChatGPT on education: A web mining and machine learning approach

ChatGPT, an artificial intelligence model, has garnered significant interest within education. This study examined public sentiment regarding ChatGPT's influence on education by utilizing web mining and natural language processing (NLP) techniques. By adopting an empirical approach and leveraging machine learning models to process 2003 web articles, the study extracts valuable insights. The results indicate that ChatGPT has emerged as a crucial educational tool, offering advantages for both students and educators. Notably, the study emphasized ChatGPT's role in enhancing students' writing abilities and fostering dynamic, interactive learning environments. ChatGPT's capacity to address a broad spectrum of questions demonstrates its versatility and adaptability, contributing to more inclusive and personalized educational experiences. However, the study also uncovered challenges tied to academic integrity, such as plagiarism and cheating, which stem from incorporating AI-driven tools like ChatGPT into education. This raises concerns regarding ethical aspects, including responsible AI usage and data privacy, and highlights the need for institutions to develop guidelines and policies for AI tool implementation in education. This study's findings hold theoretical and practical implications for integrating ChatGPT into educational settings. It is the first to employ web mining and NLP techniques to analyze public opinions on ChatGPT's impact on education comprehensively.

Attracting digital nomads: Smart destination strategies, innovation and competitiveness

Digital nomadism, as a new form of tourist mobility, brings opportunities and challenges for destination management. To attract this new market, smart destinations need to innovate to develop readiness and competitiveness. This research examines 225 digital nomad destination web articles, from multiple sources and different continents. The study aims to identify innovative strategies and practices using semantic content analysis and hierarchical network analysis. It explores relevant stakeholders and their importance, and pinpoints digital nomad trends. Findings suggest that smart destinations cater for the work, travel, social, financial and basic-living needs of digital nomads. These are different from those of short-term leisure and business tourists. Destinations tend to portray digital nomads as a homogenous group, although different segments have been identified. The long-term impacts of digital nomads on local economies and societies have yet to be fully explored. The theoretical significance of this study lies in the provision of an agency-structural perspective of destination innovation and competitiveness. Practically, the study contributes to digital nomad management and marketing within smart tourist destinations.

AN ATTAINMENT OF SUSTAINABLE DEVELOPMENT GOALS: A CASE STUDY ON SANGAMA

Background/Purpose: The pursuit of the Sustainable Development Goals (SDGs) has become a global imperative, requiring greater scrutiny of initiatives and organizations that actively contribute to these goals. In this context, Sangama, a non-profit organization that defends the rights of sexual and gender minorities, emerges as a compelling case. The purpose of this study is to comprehensively analyse the achievement status of the Sustainable Development Goals (SDGs) using the case of Sangama. Methodology: This study uses secondary data analysis using data from Sangamas website, various academic papers, and web articles to explore the achievement of Sustainable Development Goals (SDGs) through a case study focused on Sangama. It presents a comprehensive analysis. Findings/Result: Sangama plays a pivotal role in advocating for the rights and welfare of sexual minorities, transgender individuals, sex workers, and the urban poor. Sangamas dynamic approach to promoting sustainable development and social justice manifested through grassroots-level initiatives, innovative projects, and advocacy efforts, showcases a noteworthy impact. Originality/Value: By leveraging information available on Sangamas website, this study aims to provide valuable insights into the effectiveness of grassroots organizations in achieving the SDGs. The results are expected to inform policymakers, researchers, and practitioners about the role of community-based initiatives in promoting sustainable development and promoting inclusiveness.

The dynamics of argumentations in favour of college admission in online journalism

The article tells about the motives of admission of the ninth grade graduates to college. The research topic is relevant because it is important to study popular educational routes of Russian children, ways of accumulating educational and professional capital, orientation of young people to obtain technical specialties, the relevance of the «document analysis» method in empirical sociology. The materials of Internet journalism were analyzed, specifically posted on the web articles that justify the advantages of leaving school and studying at college. The author presents ratings of motives for choosing secondary special education in texts for 2018 and 2023. The content of journalistic materials was studied using qualitative methods, content analysis and with the support of relevant computer services. It has been established that the most stable and frequent argumentations in Internet journalism in 2018 and 2023 are the possibility of not passing the unified state exam, obtaining a profession, preparing for university admission. The prevailing motives are related to the lengthening of the student's educational route and the acceleration of professionalization. From the rating of reasons for choosing a college in 2023, the opinion about the availability of budget training disappeared, but there was a justification to continue the family dynasty of technical specialists. Compared to 2018, the rank of the motive for the optimal organization of the educational process in colleges has decreased. Also, the hope for individual attention to the student from the teachers has weakened. The results of the research can be applied in social policy in the fields of education and employment, especially to assess the readiness of school graduates to obtain a technical profession. The methodological conclusions of the project on the analysis of documents in empirical research are useful for students of sociological specialties.

Social Processes that Shaped Sinhala Folk Music and its Characteristics Based on the Purposes of Usage

Folk music is the music of the people. People have used folk songs to express different emotions. This research paper argues that the social processes that have shaped Sinhala folk music are multifaceted and have significant cultural and historical implications. By exploring the different categories of Sinhala folk music and their purposes of usage, this study aims to fill the research gap in understanding the characteristics and functions of this musical tradition, highlighting its role in preserving the cultural heritage of the Sinhalese people. Brief explanations of why these songs were used, including how lyrical characteristics and meanings are applied for grouping and naming, are included. Literature on Sri Lankan Sinhala Folk Music that has been published over the years in journals, books, research reports, web articles, and other materials was analysed using qualitative content analysis. It was found that people sing these songs mainly to express their feelings and emotions in addition to a range of other purposes such as communication, passing the time, motivating people, and entertainment. The existing classifications are made mainly considering activities or work-related aspects and meanings of lyrics demonstrating that they are influenced by social interactions. The authors suggest several methods to conserve Sri Lankan Sinhalese traditional music elaborating on the importance of ensuring such preservations.

E-learning: Revolution in Learning Genre

E- Education or E-learning is the delivery of education or any type of training by electronic teaching methods. This electronic method can be a computer or a smart phone where teaching material is accessed by use of internet usually. E-Learning has been an invaluable support for learners around the world. Earlier the access to knowledge was not accessible to all. Students with economic constraints, geographical boundaries or physical disabilities had scarce opportunities in the academic province. The same now hold access to consistent education. The modern learning method fetches you a refreshed version of knowledge accessible at convenience and shared with millions of people from different boroughs. It’s an ecstatic learning period for scholars far and wide. E-learning also offer greater collaboration and global opportunities to the learners. The present study is an attempt to study the usefulness of e-learning and has evolved in India. The study is based on the secondary data which is collected through various reports and web articles.

Credit Card Fraud Detection using Machine Learning and Data Mining Techniques - a Literature Survey

Purpose: To understand the algorithms used in Credit Card Fraud Detection (CCFD) using Machine Learning (ML) and Data Mining (DM) techniques, Review key findings in the area and come up with research gaps or unresolved problem. To become knowledgeable about the current discussions in the area of ML and DM. Design/Methodology/Approach: The survey on CCFD using ML and DM was conducted based on data from academic papers, web articles, conference proceedings, journals and other sources. Information is reviewed and analysed. Results/Findings: Identification of credit card fraud is essential for protecting a person's or an organization's assets. Even though we have various safeguards in place to prevent fraudulent activity, con artists may develop a method to get around the checkpoints. We must create straightforward and efficient algorithms employing ML and DM to anticipate fraudulent activities in advance. Originality/Value: Study of ML and DM algorithms in CCFD from diverse sources is done. This area needs study due to recent methods by fraudsters in digital crime have developed. The information acquired will be helpful for creating new methodologies or improving the outcomes of current algorithms. Type of Paper: Literature Review.

Pesantren and the Human Development Index in Indonesia Post Law Number 18 of 2019

This research intends to determine the extent to which the potential of pesantren is based on the mandate contained in Law no. 18 in 2019 about Pesantren in an effort to increase the Human Development Index (IPM) in Indonesia. This research is qualitative research using a literature study approach in the data collection process, both primary and secondary. The primary data in the form of the Pesantren Law was then analyzed in terms of the Human Development Index indicators with the assistance of several secondary sources such as journal articles, web articles, and books. The results of this research indicate that Pesantren has the potential in efforts to increase the Human Development Index (HDI) in Indonesia through two dimensions: 1) Pesantren have the potential to increase the Knowledge dimension (Expected School Length and Average School Length) in its function as an educational institution through the provision of formal education Pesantrens in the form of the Satuan Pendidikan Muadalah (SPM), Pendidikan Diniyah Formal (PDF), and Ma'had Aly; 2) Pesantren have the potential to increase the dimension of a Decent Standard of Living through their function in community empowerment with various training programs and economic empowerment and entrepreneurship.

Similarity Detection of Time-Sensitive Online News Articles Based on RSS Feeds and Contextual Data

This article tackles the problem of finding similarity between web time-sensitive news articles, which can be a challenge. This challenge was approached with a novel methodology that uses supervised learning algorithms with carefully selected features (Semantic, Lexical and Temporal features (content and contextual features)). The proposed approach considers not only the textual content, which is a well-studied approach that may yield misleading results, but also the context, community engagement, and community-deduced importance of that news article. This paper details the major procedures of title pair pre-processing, analysis of lexical units, feature engineering, and similarity measures. Thousands of web articles are being published every second, and therefore, it is essential to determine the similarity of these articles efficiently without wasting time on unnecessary text processing of the bodies. Hence, the proposed approach focuses on short contents (titles) and context. The conducted experiment showed high precision and accuracy on a Really Simple Syndication (RSS) dataset of 8000 Arabic news article pairs collected automatically from 10 different news sources. The proposed approach achieved an accuracy of 0.81. Contextual features increased the accuracy and the precision. The proposed algorithm achieved a 0.89 correlation with the evaluations of two human judges based on Pearson’s Correlation Coefficient. The results outperform the state-of-the-art systems on Arabic news articles.

THE CONTRIBUTION OF MEDIEVAL MUSLIMS TO THE DEVELOPMENT OF MODERN SCIENCE: A REVIEW OF ALKHWARIZMI

Muslim scholars had reached the pinnacle of scientific culture for more than five centuries. There is no denying that it was the Muslim scholars of the day who shed light on the biological sciences of medieval Europe. If the Nobel Prize had been introduced at that time, only one Muslim would have won the Nobel Prize many times. Prominent mathematician Al Quarizmi has also received numerous awards. The purpose of this study is to identify the contributions of alKhwarizmi, one of the intellectuals of medieval Muslims, to the fields of astronomy, geography and mathematics. The study, which is based on characteristic descriptive methodology, analyzes secondary data such as research articles, texts, journals, and web articles related to the research topic. It is undeniable in today's modern world that medieval Muslim scholars brought the European Dark Ages to the light of knowledge and rose to its zenith. Muhammad ibn Musa alKhwarizmi who was a Persian geographer, trader, mathematician and the pioneer in the field of geography founded algebra in mathematics, algorithms, and algorithms. Hundreds of contributions to the introduction of Indian numerology to Europe and the field of commerce through his book, Arithmetic, further enrich his scholarly contributions. It is therefore irrefutable that his scholarly contributions became known as the results of this study and that his contributions of knowledge will still be talked about in future society.

Entrepreneurship to Private Limited Company: SLN Coffee Pvt. Ltd. Co's Success Story on Creating a Successful Brand Levista

Background/purpose: The context in which entrepreneurship in the cultural and creative industries (CCI) occurs was the focus of this study. Entrepreneur inspiration is a type of motivation that allows creative ideas to be transformed into creative products. The company SLN Coffee Pvt. Ltd. Co., which started with the acquisition of a coffee plantation and later entered the trade of green coffee beans before becoming a brand coffee business in 2004, has experienced rapid and steady growth. This success can be attributed to a variety of factors worth discussing. Objective: To examine the development of SLN Coffee Pvt. Ltd. Co. and the factors that contributed to this growth into a brand. Design/Methodology/Approach: Information gathered from primary and secondary data is analyzed and presented. utilizing the SWOC framework, numerous scholarly articles, web articles, company websites, and interviewing techniques. Findings/result: It has been found, findings of a study conducted using a variety of resources and the analysis of data, that competing in a market is a challenging endeavour that calls for the application of multiple methods and processes. creativity and innovation. Research limitations/implications: The evaluation and solutions presented in this paper are only applicable to industries with a limited to similar business model, yearly revenue, and level of expertise to SLN Coffee Pvt. Ltd. Co. Originality/value: This paper focuses on the various factors and scenarios that have enabled the SLN Coffee Pvt. Ltd. Co to grow and be labelled as a brand in the coffee industry. Paper type: A Research Case study paper on journey of SLN Coffee Pvt. Ltd. Co in becoming the successful coffee Brand in comprehensive coverage of the coffee Industry.

Translation Mistakes of Arabic Poem into Tamil: The Undergraduates of the Department of Arabic Language, South Eastern University of Sri Lanka as a Model

This study intends to pinpoint the mistakes made when translating the selected poetry into Tamil and to highlight the translation techniques used by South Eastern University of Sri Lanka's Department of Arabic language students. This research uses descriptive analytical methods. The data for this research was collected through the field and library. The primary data was collected from the questionnaires distributed among 100 third-year students from the Department of Arabic Language randomly. The library method consists of books, research, articles, and web articles. To obtain accurate scientific results, MS Excel is used. The findings of this study show that the students translated the poems to a medium level accurately. And they erred in these areas: selecting the appropriate words based on the poetic text's context; providing the proper meaning; determining the pronoun's reference; and considering the context of the source and target languages. They studied this poetry line by line, but regrettably missed the chance to apply. Due to this circumstance, they have limited knowledge of poetic works and a reluctance to study Arabic literature. Arabic literature lecturers must be proficient in the use of proper teaching strategies and get classroom work when studying poetic texts. For them to completely comprehend poetry texts, it is preferable to include background knowledge. This research finds that that students' mastery of translation criteria or requirements helps them to translate correctly.

A qualitative framing analysis of how firearm manufacturers and related bodies communicate to the public on gun-related harms and solutions

There is a growing understanding that the producers and sellers of harmful products directly and indirectly affect population health and policy, including through seeking to influence public understanding about the nature of harms and their solutions. However, the firearm industry and related organisations have not to date been the subject of this type of enquiry. This study sought to address this evidential gap through examining the ways in which the firearm industry and industry-associated organisations frame firearms, firearm-related harms and possible solutions to gun violence. This was a thematic qualitative documentary analysis of materials from 7 of the largest firearm manufacturers and associated organisations. Two authors independently extracted textual material from web articles, press releases, annual reports and shareholder communications between 1st April 2019 to 1st April 2020 (302 documents). A hybrid approach combining both deductive and inductive coding was adopted, guided by the literature on the commercial determinants of health and using NVivo version 12. The firearm industry and firearm industry-funded organisations use framings about the safety and role of guns, evidence on associated harms and solutions that align with the industry's business interests, consistent with evidence on other harmful product manufacturers. This study identified framing strategies employed by the firearm industry and related organisations. These included attempts to undermine evidence, linking regulation to a dystopian future, minimising some of the most common harms, placing the responsibility for harms on individuals, and attempting to foster a heightened sense of risk to personal safety.

Suitability: a longitudinal study of adult-focused physical activity promotion web articles

A cross-sectional design has often been used to study the quality of health-related educational materials meant for lay adults (e.g., patients, the public). The present study addressed this research limitation. We documented the proportion of online physical activity promotion (PAP) material revised within a given time period and how quality was affected, if at all. PAP web articles (N = 139) meant for lay adults, written in English, and first sampled in July 2018, were resampled in July 2020. Mean publication year at timepoint 1 was 2016.82 (±1.24). At timepoint 2 it was 2018.78 (±1.39). At both timepoints, suitability for lay use was appraised using five dimensions of the suitability assessment of materials (SAM) protocol: i.e., content, literacy demand, graphics, layout and typography, and learning stimulation/motivation. There were 61 web articles (43.9%) with indicated revision and analyzed in the present study. Articles were distributed across four organizational subgroups: commercial (n = 21), government (n = 13), professional association (n = 10), and voluntary health agency (n = 17). In the aggregate sample, two SAM dimensions significantly improved: literacy demand (e.g., more active voice) and layout & typography (e.g., formatting). Often, organizational subgroups mirrored the aggregate sample. Although the overall suitability remained within the satisfactory range across the dimensions, a moderate-to-large number of articles remained unsatisfactory at timepoint 2 within several subdomains (e.g., reading grade level, summary section). This study’s findings further evidence PAP materials are somewhat suitable and the need to study suitability subdomains in addition to overall suitability.

A Case Study on Coronary Heart Disease using Machine Learning Techniques

Background/Purpose: We have seen an increase in coronary heart disease and heart attack risk in recent years. This is a case study on Sri Jayadeva Institute of Cardiovascular Sciences and Research, Bengaluru to get a better understanding of the heart related ailments and their related symptoms. The hospital specializes in cardiology, cardiothoracic surgery and paediatric cardiology. Based on the symptoms various ailments are diagnosed and treated with different treatments like angioplasty, placement of stent, lifestyle changes and medicines. As part of the research, various health parameters will be collected and analyzed for diagnosing heart related ailments using Machine Learning methods. Determining the appropriate Machine Learning technique to achieve maximum accuracy is the key to achieve a better treatment and prevention of mortality. Design/Methodology/Approach: This study was undertaken using secondary sources, such as website of Sri Jayadeva Institute of Cardiovascular Science and Research, journals, conference articles, the internet and scholarly articles. The SWOT framework is used to analyse, and present, the information acquired from web articles, scholarly papers and other sources. Findings/Results: Heart ailments can be predicted using a few key parameters which can help in avoiding mortality. For this purpose machine learning algorthims, Neural Networks, Particle Swarm algorithm and many more can be applied on those medicial parameters. Originality/Value: This paper reports an exhaustive and comprehensive overview of Coronary Heart Diseases and the treatment provided by Jayadeva Cardiology Hospital on different data collected. Paper Type: Case study-based Research Analysis

The Giant of the Global Software Industry - WIPRO: A Case Study

Background/Purpose: Wipro is a market leader in business process outsourcing, consulting, and information technology worldwide. Wipro helps clients succeed in the digital world by utilising cognitive computing, hyper-automation, robots, the cloud, analytics, and emerging technologies. They have more than 2 lakh committed people serving customers on six continents and are well-known throughout the world for their extensive service portfolio, strong commitment to sustainability, and outstanding corporate citizenship. They generate original concepts and make connections to forge a brighter and riskier future. Objective: To examine Wipro's growth and problems, as well as the contributing factors that aided this expansion. Design/Methodology/Approach: Information gathered from a variety of academic journals and web articles was analysed and presented using the SWOC framework. Findings/Result: Based on the examination of facts and numbers as well as the many scenarios of firm expansion in India, it is clear that the Wipro company has experienced significant growth and advancement in various areas such as job creation and the country's economy. A few suggestions are also made to expand on the notion. Research limitations/implications: The analyses and solutions presented in this article are only applicable to businesses with similar operations, yearly revenues, and levels of expertise to Wipro. Originality/Value: This article focuses on a number of variables and situations that allowed Wipro to expand and earn the title "Giant of Companies" in the process. Paper Type: A Research Case study paper on Wipro's success and contributing elements in India and becoming one of the top firms.

Representation of Siri’ in the Novel Tenggelamnya Kapal Van Der Wijck

This article examines how the Bugis-Makassar value of siri’ is depicted in the novel Tenggelamnya Kapal Van Der Wijck by Haji Abdul Malik Karim Amrullah (often shortened to “Buya Hamka,” or simply “Hamka”). Through framing analysis of select dialogue and narration depicting siri’ from the novel supplemented by relevant literature sourced from journals, books, and web articles, this examination found that, although the protagonist character of Zainuddin has both Makassar and Minang roots and was written with the intent to represent the Makassar perspective, Hamka’s own background as a Minangkabau ethnic (albeit one who lived in Makassar for an extensive period) results in incomplete depictions of the regional value of siri’ and Makassar customs.

One Vax Two Lives: a social media campaign and research program to address COVID-19 vaccine hesitancy in pregnancy

The COVID-19 pandemic has disproportionately affected pregnant people by increasing health risks of maternal morbidity and mortality, stillbirth, and preterm birth. Although numerous studies have supported the safety and efficacy of COVID-19 vaccination in pregnancy in preventing or mitigating the risk for these adverse outcomes, many pregnant people remain hesitant. Approximately half of US adults regularly consume news from social media platforms, which are a fertile ground for the spread of vaccine disinformation. The lack of information regarding COVID-19 vaccine safety early in the pandemic fueled vaccine myths targeting the fears of pregnant people about vaccination risks. Saddened by the spike in maternal deaths of unvaccinated individuals during the COVID-19 Delta variant surge in the fall of 2021, we created a social media campaign to promote scientific communication regarding the risks of COVID-19 disease in pregnancy and the benefits of vaccination. We called the campaign “One Vax Two Lives,” which refers to the ability of 1 maternal vaccine to benefit the health and lives of both the pregnant individual and their fetus. We present a blueprint of how we leveraged a large, interdisciplinary student workforce to create a social media campaign and research program studying vaccine hesitancy, which can be replicated by other groups. Community engagement and partnerships with key stakeholders, such as the Washington State Department of Health, were essential for amplifying the campaign and providing our team with feedback on content and approach. We present the analytics of our social media advertisements, web articles, and video content that helped inform the iterative design process of the multimedia content. Moving forward, we are launching collaborative research programs to study vaccine hesitancy and inform the development of new social media content designed for pregnant individuals who are: (1) Spanish-speaking Hispanic/Latina/x, (2) Black or Afro-Latinx, and (3) residents of rural communities in the State of Washington. Data from these mixed methods studies will inform new communication campaigns to reach vaccine-hesitant individuals. Finally, we discuss lessons learned and how the most impactful elements of the campaign can be translated to related areas of maternal public health.