Traditional Text Research Articles

Legal Confrontation of the Cyber Blackmail: a Comparative Study

Objective: Current Research addresses “Threats and Electronic Blackmail in the Egyptian and Emirati Laws” as a vital issue in several ways. First of importance comes from the expanding user circle via Modern Technological Means of Communication. Indeed, Sales Systems established by Service Providers are not restricted to one Social Group or Class, which can reflect many Crimes committed through these systems. Secondly, the Psychological Impact caused by the Crime of Electronic Blackmail seriously harms people, threatening the Human Right to enjoy tranquility and a sense of secure practices. Third, the Penal Legislation of different countries is not entirely consistent in confronting such crimes. Some have already designed Special Penal legislation to combat Modern Electronic Crimes, while others still rely on Traditional Texts included in the Penal Code. Methods: This paper relied mainly on a descriptive approach to examine the Crime of Electronic Blackmail in addition to studying some legal frameworks that regulate the Crime of Electronic Blackmail. The comparative perspective was also used to identify aspects of the Crime of Electronic Blackmail in Egypt and the United Arab Emirates. Results and disscution: This type of contradiction is embodied in the Emirati Law, a good example of the first trend, whereas Egyptian law simply represents the second trend. Research Implications: We are obliged to wonder about the adequacy of the General Penal Code in confronting this new type of Crime. Originality/Value: We are committed to addressing Criminal Confrontation Effectiveness as implemented by Legal Legislation represented in the Penalties imposed on committing these crimes, thus protecting Victims of Electronic Blackmail.

The impact of platform affordance on the representation of iconic architecture: a case study of Markthal across visual social media

PurposeThis paper explores how platforms shape the representation of iconic architecture across visual social media platforms, particularly how their unique features and affordances impact these representations.Design/methodology/approachThis paper develops an integrated framework connecting iconic architecture representation, platform affordance and triadic spatial theory. Taking Rotterdam’s Markthal as a case study and collecting multimodal data from TikTok, Instagram and Google Maps, the paper uses a mixed-methods approach that integrates content analysis with qualitative coding and quantitative image/video label detection and image clustering.FindingsTikTok is more associated with enriching lived space by enabling users to share vibrant, personal experiences and activities. Instagram influences perceived space more by shaping how users view and experience the physical environment through curated visual content. Meanwhile, Google Maps effectively shapes conceived and perceived space by users’ feedback of place ratings and reviews.Research limitations/implicationsUnderstanding how platform affordances influence the representation of iconic architecture helps designers and researchers generate design strategies and guides marketers in strategically selecting effective social media platforms for architecture promotion.Originality/valueThis research addresses the gap in understanding the impact of platform affordances on social media representations, especially through comparisons across multiple visual social media platforms. Its novel contribution is introducing the concept of affordance from media studies to architecture and urban studies while enhancing traditional text analysis with computational methods for analysing videos and images.

Pantograph: A Fluid and Typed Structure Editor

Structure editors operate directly on a program’s syntactic tree structure. At first glance, this allows for the exciting possibility that such an editor could enforce correctness properties: programs could be well-formed and sometimes even well-typed by construction. Unfortunately, traditional approaches to structure editing that attempt to rigidly enforce these properties face a seemingly fundamental problem, known in the literature as viscosity . Making changes to existing programs often requires temporarily breaking program structure—but disallowing such changes makes it difficult to edit programs! In this paper, we present a scheme for structure editing which always maintains a valid program structure without sacrificing the fluidity necessary to freely edit programs. Two key pieces help solve this puzzle: first, we develop a novel generalization of selection for tree-based structures that properly generalizes text-based selection and editing, allowing users to freely rearrange pieces of code by cutting and pasting one-hole contexts; second, we type these one-hole contexts with a category of type diffs and explore the metatheory of the system that arises for maintaining well-typedness systematically. We implement our approach as an editor called Pantograph , and we conduct a study in which we successfully taught students to program with Pantograph and compare their performance against a traditional text editor.

Development of a model to form reading literacy of primary schoolchildren involving media design technology in a booktrailing format

Problem and aim. The formation of reading literacy of primary schoolchildren is one of the priorities of the modern education system. There are new indicators emerging in materials for testing the reading literacy of schoolchildren, including an assessment of test takers' readiness for independent learning in the digital space. The purpose of the article is to scientifically substantiate the effectiveness of the model to form reading literacy of primary schoolchildren by means of media design technology in a booktrailing format. Research methods. During the analysis and selection, a number of services for media design in the booktrailing format (Liveworksheets, Story, text and graphics editors, video editing programs) were used. The experiment involved 68 students of the second grades of Lyceum No. 21 in Kirov (Russian Federation). The students were engaged in media design as part of their extracurricular activities. The methodology for assessing the quality of primary education (authors G. S. Kovaleva, L. A. Ryabinina, T. Y. Chaban) was applied at the stage of determining the level of formed reading literacy of primary schoolchildren. The χ 2 -Pearson criterion was used in statistical data processing. Results. Features of the proposed model are as follows: taking into account changes in the reading literacy assessment programs; organising materials according to the extent of the used techniques; using texts of various literary genres, a new structure and format that differ from traditional linear text presentation. The structural blocks of the model are described: organizational and methodological, forming, activity-based, intellectual and creative. 11 stages when working on a booktrailer are formulated: motivation to choose works, selection of works on a certain topic, the process of reading, determining the author's idea, writing a video presentation script, distribution of voice-over roles, etc. Statistically significant differences in qualitative changes that occurred in the pedagogical system (χ 2 = 8.488; p < 0.05) are revealed. Conclusion. Identifies possible difficulties in implementing the model: tracking changes in reading literacy assessment programs; choosing digital services; supporting high cognitive activity of students; searching for artistic expressive means.

Character/Word Modelling: A Two-Step Framework for Text Recognition in Natural Scene Images

Text recognition from images is a complex task in computer vision. Traditional text recognition methods typically rely on Optical Character Recognition (OCR); however, their limitations in image processing can lead to unreliable results. However, recent advancements in deep-learning models have provided an effective alternative for recognizing and classifying text in images. This study proposes a deep-learning-based text recognition system for natural scene images that incorporates character/word modeling, a two-step procedure involving the recognition of characters and words. In the first step, Convolutional Neural Networks (CNN) are used to differentiate individual characters from image frames. In the second step, the Viterbi search algorithm employs lexicon-based word recognition to determine the optimal sequence of recognized characters, thereby enabling accurate word identification in natural scene images. The system is tested using the ICDAR 2003 and ICDAR 2013 datasets from the Kaggle repository, and achieved accuracies of 79.8% and 81.5%, respectively.

Digital reading, digital reader: In search of the definitions

The author undertakes to classify digital reading and produces the criteria for classifying digital readers. She refers to the traditional classifications of readers, i. e. by reading culture, structure of reading interests, reading motives. The author reviews Russian and foreign studies of digital and traditional reading, identifies trends and distinctions. Based on the reviewed literature analysis, the following patterns are specified: apprehension and retention of traditional texts are much higher; digital reading is very popular with the young; increasing demand for audio books, in China, in particular. The positive and negative features are recognized (decrease of cognitive capabilities of modern readers, psychological problems in communication functions). The author introduces the definition for digital readers, develops additional indicators for classification: by sensitive qualities of information perception, search methods, information hygiene, and by the capability of building critical attitude toward the information one read.

Historiographical Encounters in Colonial South India

The impact of the colonial encounter on local historiographical practices in India has been at the center of several debates, often characterised by polarised positions. By analysing the reception of versions of the Malayalam Kēraḷōlpatti by British administrators and a missionary in the beginning of the nineteenth century, the article argues that these successive textual encounters produced several hybrid forms of history, mingling local traditions with historiographical practices common in Europe. In addition, local traditions often acquired new 'mediatic' characteristics that helped them reach new audiences and gain new significance, thus advantaging some textual traditions at the expense of others. In turn, the promotion of these texts made them privileged targets for the development of counter-narratives about the past.

A study on Dongba manuscripts from the perspective of cultural geography

Dongba manuscripts are traditional Chinese texts written in pictographic Dongba script. The Dongba script likely originated in the early Tang dynasty, and no later than the Northern Song dynasty in the 11th century. The distribution of the Dongba manuscripts corresponds to the distribution of the eastern and western dialects of the Naxi ethnic group. Dongba manuscripts from different regions exhibit significant differences in character forms and writing styles, displaying regional characteristics. Dongba manuscripts are categorized into four regions based on their distribution: the first region features small characters, simple strokes, and a rustic style; the second region features round and delicate characters with even strokes; the third region mainly features three-line scripts with concise strokes and clear writing and with varying spacing; the fourth region features more annotated characters, denser lines, reduced spacing between characters, and a variety of ways to convey meaning and pronunciation. The geographical distribution of Dongba manuscripts is closely related to surrounding ethnic groups such as the Han, Tibetan, Bai, and Lisu.

Scene Text Detection and Recognition Using Maximally Stable Extremal Region

In recent years, scene text detection and recognition have become important research areas in computer vision and machine learning. Traditional text detection and recognition methods may struggle with detecting and recognizing text in images with low resolution, complex backgrounds, and varying font sizes. The proposed methodology addresses these challenges by combining multiple algorithms and using deep learning techniques. In this paper, we propose a method for scene text detection based on Maximally Stable Extremal Regions (MSER) combined with Stroke Width Transform (SWT) and recognition using Convolutional Recurrent Neural Networks (CRNN). Our method consists of two stages: text detection and text recognition. To detect text, we use MSER and SWT to extract candidate text regions from the input and then, we eradicate non-text regions using image to image translation. Finally, to recognize text, CRNN is used to recognize the text present in the detected regions. Our CRNN architecture consists of convolutional and recurrent layers, which enable us to capture both spatial and temporal features of the text. The methodology is evaluated on various benchmark datasets and has obtained good results with accuracy of 96% when compared to existing methods.

Designing Local Culture-based Canva Narratives to Enhance Reading Skills for Junior High School Students

The study aimed to develop culturally relevant reading materials for eighth-grade students at one of the state junior schools in Ponorogo, Indonesia, using Canva as a digital platform. The primary objective was to improve students' reading comprehension by integrating local cultural narratives, such as the stories of Reog Ponorogo and Lake Ngebel, into narrative texts. The research employed the ADDIE model to systematically design and implement these materials, with phases including analysis, design, development, implementation, and evaluation. In the Analysis phase, student needs were assessed through questionnaires, revealing that students struggled with narrative structure and found traditional reading materials disengaging. The Design and Development phases involved creating visually engaging, culturally relevant narrative materials using Canva. The materials were then tested in the classroom, where students interacted with the content through reading tasks and quizzes. Findings showed significant improvements in students' engagement and reading comprehension. Over 80% of the participants reported that the materials were more relatable and easier to understand than traditional texts. The study concluded that integrating local culture into reading materials through digital platforms like Canva enhances both student motivation and learning outcomes.

SikuGPT: A Generative Pre-trained Model for Intelligent Information Processing of Ancient Texts from the Perspective of Digital Humanities

The rapid development of generative artificial intelligence has brought significant opportunities for the advancement of digital humanities research. Intelligent processing of ancient texts, as an essential part of digital humanities, is also undergoing a transformation in research methodologies in the wave of AIGC. The integration of generative pre-trained models with Chinese ancient texts, a vital carrier of Chinese culture, allows for deep mining of the content of these texts and provides services that make ancient texts more understandable and accessible to the general public. In this research, we propose a method that combines the most renowned Chinese anthology, the “Siku Quanshu,” with generative pre-trained models. We developed the SikuGPT model, a generative model for ancient text processing tasks, based on GPT-type language models by continued pretraining. This model was tested on two typical tasks of ancient text processing: translation between classical and modern Chinese, and classification of ancient texts. The findings reveal that our model achieves advantages in understanding and generating scenarios of ancient texts. The capability of SikuGPT in processing traditional Chinese texts helps to promote the organization of ancient information and knowledge services, and advances the international dissemination of traditional Chinese culture.

Stylo-Textual Strategies in Psalm 51

Psalm 51, attributed to King David, stands as a profound expression of repentance and restoration within the biblical tradition. This paper presents a thorough examination of the stylo-textual strategies employed in Psalm 51, focusing on its linguistic, stylistic, and textual dimensions. Through meticulous analysis, the study reveals the intricate interplay between rhetorical devices, linguistic features, and textual structures in conveying the psalmist's plea for divine mercy and spiritual renewal. Stylistically, the psalm employs parallelism, imagery, repetition, metaphor, and irony to evoke emotional resonance and rhetorical impact. Textually, the psalm unfolds a coherent structure, progressing from confession to petition and affirmation, reflecting the psalmist's journey from contrition to transformation. Moreover, the psalmist's engagement with textual traditions and cultural norms enriches the text's interpretive depth and theological significance. Through this analysis, readers gain deeper insights into the stylo-textual strategies employed in Psalm 51, inviting reflection on its enduring relevance and profound insights into the human experience of sin, forgiveness, and redemption.

How Good Is GPT’s “Emojinal Intelligence”? Investigating Emoji Patterns in LLM-Generated Social Media Text

Recent advancement in Large Language Models (LLMs) has opened the prospect of generating text for social media content that mimics human writing. The misuse of these tools presents urgent dilemmas, motivating the need to better understand the structure and patterns of LLM-generated content. Human communication on the Internet has developed relevant linguistic adaptations, including the use of emoji to augment traditional text. This study investigates the ability of one LLM, OpenAI’s GPT-3.5, to replicate human emoji usage in social media contexts. Drawing upon a dataset of nearly three thousand US English human-written tweets, we employed GPT-3.5-Turbo to generate social-media-style content and analyzed the use of emoji in the resulting text. We compared the patterns of emoji usage between the LLM-generated and the human-written datasets, particularly frequency, types of emoji commonly used, and emoji sequences (n-grams). Our results revealed notable differences in all categories. While human-written tweets were more likely to use faces, hearts, and repetitive sequences of emoji, LLM-created content had a broader variety of emoji, with a preference for literal representations of the text’s subject matter, producing diverse and unique emoji combinations.

Breath Characteristics of Volitional Yoga Breathing and Breath Awareness.

Changes in breathing during pranayama (yoga breathwork) are usually inferred from practice guidelines in traditional texts or contemporary writings. These changes point to understanding the effects of pranayama and indicate applications of pranayama in health. Previously, a pilot study on a single participant suggested that each pranayama changes breathing uniquely. To extend this research in the present study, 23 yoga practitioners (mean age 28.1 ± 3.8; 12 men, 11 women) who were able to practice the pranayama consistently were each studied in a 48-minute session with five pranayama practices-(1) alternate-nostril yoga breathing, (2) bellows yoga breathing, (3) bumblebee yoga breathing, (4) high-frequency yoga breathing, and (5) hissing yoga breathing-as well as (6) breath awareness for 3 minutes each. From strain gauge-recorded respiratory movements, the breath frequency, depth/amplitude of breathing, and inspiration:expiration were obtained. Compared to the baseline, breath rate increased during high-frequency breathing (373.3%) and decreased during bumblebee breathing (75.3%), hissing breathing (63.0%), and alternate-nostril breathing (55.3 %). The depth of breathing increased in alternate-nostril breathing (141.0%), bellows breathing (136.0%), bumblebee breathing (307%), high-frequency breathing (275.0%), and hissing breathing (95.0%). The inspiration:expiration increased in high-frequency breathing (177.0%) and decreased in bumblebee breathing (74.3%) and alternate-nostril breathing (39.0%). There were no changes during breath awareness. The changes in breathing (although limited by the small sample size) support previous reports of high-frequency breathing as being activating while enhancing attention, and of bumblebee and alternate-nostril breathing (hissing and bellows breathing to a lesser extent) as calming, with increased vagus nerve activity.

Предчувствие любви и смерти в традиционных личных песнях западных эвенков

Evenki musical folklore has long attracted the attention of researchers. The earliest publication of traditional Evenki song texts was produced by G. Hut at the beginning of the 20th century. The first audio recording of Evenki songs was made using a phonograph by L. Y. Sternberg in 1910. The Phonogramme Archive of the Pushkin House in St. Petersburg includes extensive collections of traditional Evenki personal and shamanic songs, which were recorded in the first quar­‑ ter of the 20th century and still need to be transcribed and analyzed. Since then, a number of articles and monographs dedicated to Evenki songs, both traditional and modern, have been published. However, these publications have not included many actual texts of traditional Evenki songs. Collections of Evenki songs, published regularly since the 1930s, primarily reflect the “new wave” of songs written under the influence of the Russian/Soviet and global pop music traditions. This is the type of songs that we have had the opportunity to record since the turn of the 21st century among not only the Wes­­­­‑ tern, but also Eastern Evenkis. Therefore, the two traditional songs presented in this article are rare exceptions among our Evenki field data. They were recorded in 1999 in Turukhansk, the district centre, performed by Maria Fedorovna Bezrukikh (Kurmatova), an 80-year-old Evenki woman from the Arctic village of Sovetskaya Rechka. These are traditional personal songs, not of the performer herself, but of her elder relatives. The first one is the song of a young girl who dreams of meeting a yet unknown man with whom she could spend the rest of her life. The second song is that of an old woman anticipating her approaching death.

P. Gen. inv. 376 – Ein neues Fragment von Isokrates’ Panegyrikos

Abstract The article presents an edition of the yet unidentified P. Gen. inv. 376 containing Isoc. 4.108-109. Remarkable is a variant in the margin (l. 26), which indicates a process of collation between different ancient textual traditions.

Potential Role of Ayurveda Interventions in the Management of Grade II Non Alcoholic Fatty Liver Disease: A Case Report

Non Alcoholic Fatty Liver Disease (NAFLD) represents a growing global health concern, particularly driven by rising obesity rates, with prevalence ranging from 11.2 to 37.2% in the general population. Ayurveda classifies NAFLD under Yakrit Roga (liver disease) and Medoroga (obesity), with traditional texts attributing its development to lifestyle factors that lead to imbalances in tridosha. Hereby, the authors present a unique case of 59-year-old male that highlights the therapeutic effects of Ayurveda interventions in managing grade II NAFLD, adding valuable insights to the scientific literature by demonstrating effective treatment in the absence of a standard care protocol. The patient presented with symptoms of indigestion and liver enlargement consistent with grade II NAFLD, confirmed through ultrasonography evaluation. Clinical findings included liver steatosis and mild hepatomegaly. The intervention involved Ayurveda-based therapies tailored to the patient’s condition, focusing on balancing Rakta-Kapha Dushti and dietary modifications based on classical Ayurveda guidelines. Following treatment, the patient experienced complete relief from symptoms of indigestion, and follow-up ultrasonography showed significant improvement, as there was no NAFLD. The present case report illustrates the potential of Chitrakadi Vati and Phaltrikadi Kashaya ghan vati as effective management strategies for NAFLD, particularly in the absence of established standard care. The takeaway lesson is that individualised Ayurveda treatment may offer a viable therapeutic approach for NAFLD, highlighting the importance of integrating traditional medicine into the broader clinical context of liver disorders.

Book review: Taniya Roy, Representations of Marriage and Beyond: An Investigation of Early Buddhist Textual Traditions (c. Sixth Century bce to Fifth Century ce)

Taniya Roy, Representations of Marriage and Beyond: An Investigation of Early Buddhist Textual Traditions (c. Sixth Century bce to Fifth Century ce) (New Delhi: Primus Books), 2022, x + 233 pp., ₹1050 (Hb).

The Implications of Digital Culture for Contemporary Literature: Navigating New Narratives, Forms, and Reader Engagement in the Digital Age

This research examines the impact of digital culture on contemporary literature, particularly focusing on narrative structures, reader engagement, and comprehension in digital formats. As digital media continue to reshape how literature is consumed, this study explores the effects of interactive and multimedia-rich digital texts on reader behavior and cognitive engagement. Using a quantitative approach, the research combined surveys with 500 participants and content analysis of 20 digital texts, including hypertext fiction and multimedia narratives. Descriptive statistics revealed that participants spent 32% more time engaging with interactive formats than traditional digital texts, with younger readers showing higher engagement levels. The analysis also found a significant positive correlation (r = 0.45, p < 0.05) between digital media familiarity and preference for interactive narratives. However, comprehension scores varied, with some readers finding it difficult to follow non-linear, branching storylines. Content analysis showed that 75% of the selected digital texts contained multimedia elements, while 65% included hyperlinks, reflecting the prevalence of these features in contemporary digital literature. The results support the hypothesis that interactive formats enhance engagement, but suggest challenges in comprehension, especially with complex, non-linear narratives. This study provides key insights for authors, publishers, and educators on the evolving landscape of digital literature and reader interaction. It highlights the need for more research on the long-term effects of digital reading on comprehension and cognitive development, as well as a deeper comparison between digital and traditional reading experiences.

Consistency Verification Method of Chinese and Russian Traditional Culture Translation Text Corpus Based on CNN-BiGRU

China and Russia have completely different cultural backgrounds, historical traditions and ways of thinking, which makes it difficult to directly correspond or accurately convey many culturally unique concepts, customs and expressions during the translation process. For example, some idioms, sayings or cultural symbols may have completely different meanings or no equivalents in the two cultures. Therefore, there are problems such as poor verification resulting in the consistency verification of Chinese and Russian traditional cultural external publicity translation text corpus. In order to solve this problem, this paper designs a consistency verification method for Chinese and Russian traditional cultural external publicity translation text corpus based on CNN-BiGRU. Through the part-of-speech correspondence of the Chinese and Russian traditional cultural external publicity translation text corpus, it is represented by vectors, the feature weights of the Chinese and Russian traditional cultural external publicity translation text corpus are calculated, the collocation information between the feature items is determined, and the maximum likelihood of the features is calculated using data smoothing technology. The rules are adjusted to extract the characteristics of the Chinese and Russian traditional cultural external publicity translation text corpus. Preprocess the key feature source documents of each Chinese and Russian traditional culture external publicity translation text corpus, determine the source documents and their corresponding key features of the traditional culture external publicity translation text corpus, and use TF-IDF and IDF to calculate the key feature sources of the corpus. Based on the rarity of document data, the BERT model is introduced as an encoder to determine the key features of the Chinese and Russian traditional cultural external publicity translation text corpus, integrating the CNN-BiGRU algorithm to design a consistency verification algorithm for Chinese and Russian traditional cultural external publicity translation text corpus. Set up the convolution layer, weight sharing layer, pooling layer, and BiGRU verification layer to build a CNN-BiGRU model to achieve consistency verification of the Chinese and Russian traditional cultural external publicity translation text corpus. Experimental results show that this method can improve the consistency verification effect of Chinese and Russian traditional cultural external publicity translation text corpus.