Text Documents Research Articles

AN ANALYTICAL STUDY OF THE DIVERSITY AND VARIABILITY OF CRITICAL APPROACHES IN HAZM AL-QARTAJANNI’S “MINHAJ AL-BULAGHA WA SIRAJ AL-UDABA”

The research aims to analyze one of the significant works in Arabic rhetoric and critical studies, Minhaj al-Bulaghā’ wa Sirāj al-Udabā’ by the Andalusian critic and poet Hazim al-Qartajanni. The study seeks to clarify and demonstrate the author's methodology in addressing linguistic, rhetorical, and critical issues, as well as his approach to analyzing and interpreting them. It highlights the integration of knowledge and methodologies through the use of induction and textual documentation as a systematic method to compile argumentative evidence. This approach underscores the uniqueness of the book's author by deconstructing its structural and semantic components and describing them to reach conclusions, analyze content, interpret it, and compare it with Arab and Greek heritage to highlight the findings. To achieve this, two research methodologies were adopted: First, the integrative approach, which emphasizes the interconnectedness of linguistic sciences and rhetorical critical issues by employing tools that study the research topic from all knowledge dimensions and eliminate barriers between specialized divisions. Second, the descriptive-analytical approach, which involves analyzing the critical issues presented in the book based on observation and research mechanisms to collect information and data from the primary source, Minhaj al-Bulaghā’ wa Sirāj al-Udabā’. The analysis aims to explain and interpret the content, draw conclusions, and provide commentary. The findings of the research reveal the diversity and complexity of critical topics addressed by al-Qartajanni. He adopts a logical perspective that integrates Greek and Arabic cultural elements in his analyses, uncovering the principles and foundations upon which rhetoric is built within the framework of a discipline supported by logic and wisdom in Arabic rhetoric.

Accuracy of Electronic Health Record Phenotypes to Detect Recognition of Hypertension in Pediatric Primary Care.

To evaluate the accuracy of extractable electronic health record (EHR) data to define clinician recognition of hypertension in pediatric primary care. We used EHR data to perform a cross-sectional study of children aged 3-18 years at well-visits in Connecticut from 2018-2023 (n=50,290) that had either: (1) incident hypertension (hypertensive BP at the well-visit and ≥2 prior hypertensive BPs without prior diagnosis of hypertension); or (2) isolated hypertensive BP at the well-visit without necessarily having prior hypertensive BPs. We tested the accuracy of EHR phenotypes to detect recognition of incident hypertension or hypertensive BP using structured elements, including diagnosis codes, problem list entries, number of BP measurements, orders, and follow-up information. The primary outcome of hypertension recognition was determined by chart review. Among 239 children with incident hypertension and a random sample of 220 children with hypertensive BP, 13% in each sample had clinician recognition of hypertension and hypertensive BP, respectively. An algorithm using ICD-10 encounter diagnosis code, ICD-10 problem list, or multiple BPs during the visit had the highest AUC for attention to incident hypertension (AUC, 0.84; sensitivity, 71.9%; specificity, 95.7%). Adding follow-up BP information to this algorithm had the highest AUC for attention to hypertensive BP (AUC, 0.85; sensitivity, 75.9%; specificity, 93.2%). For patients with hypertension recognition by chart review, ~20% had only free text documentation of hypertension without any structured elements. EHR phenotypes for hypertension recognition have high specificity and moderate sensitivity and may be used in clinician decision support to improve guideline-recommended care.

The Practice of Body Power and Masculine Resistance of Male Actors in Indonesian Comedy Films of the Reform Era

The practice of power over male actors' bodies in comedy films is understood not as a neutral process where factual reality is conveyed directly through text or images, but as a social praxis related to the deconstruction of gender, resulting in new understandings of masculinity depicted in films from the Reform Era. To address this question, the researcher employs Norman Fairclough's critical discourse approach to comedy films as the main theoretical framework, combined with Michel Foucault's perspective on power relations and Maurice Merleau-Ponty's theory of body language. The paradigm used in this research is the critical paradigm, with data collection techniques obtained through film text documentation studies. The research results show that the male actor's body does not merely function as a tool for visual narration but also as a powerful medium for expressing deeper themes related to power, identity, and social dynamics. For instance, in the film Arisan! 2, the narrative highlights sexual freedom and emotional vulnerability. Meanwhile, Bebas emphasizes physical changes and social symbolism through the male body.

Accelerating and standardising IUCN Red List assessments with sRedList

The IUCN Red List of Threatened Species underpins much decision-making in conservation and plays a key role in monitoring the status and trends of biodiversity. However, the shortage of funds and assessor capacity slows the uptake of novel data and techniques, hampering its currency, applicability, consistency and long-term viability. To help address this, we developed sRedList, a user-friendly online platform that assists Red List assessors through a step-by-step process to estimate key parameters in a standardised and reproducible fashion. Through the platform, assessors can swiftly generate outputs including species' range maps, lists of countries of occurrence, lower and upper bounds of area of occupancy, habitat preferences, trends in area of habitat, and levels of fragmentation. sRedList is compliant with the IUCN Red List guidelines and outputs are interoperable with the Species Information Service (SIS; the IUCN Red List database) in support of global, regional and national assessments and reassessments. sRedList can also help assessors prioritise species for reassessment. sRedList was released in October 2023, with a complete documentation package (including text documentation, ‘cheatsheets’, and 15 video tutorials), and will soon be highlighted in the official Red List online training course. sRedList will help to bridge the gap between extinction risk research and Red List assessment practice, increase the taxonomic coverage and consistency of assessments, and ensure the IUCN Red List is up-to-date to best support conservation policy and practice across the world.

Deep sight: enhancing periprocedural adverse event recording in endoscopy by structuring text documentation with privacy-preserving large language models

Background and aimsThe assessment of adverse events from endoscopic procedures is essential for successful interventions, ensuring accurate follow-up, adverse event management and processing for quality control. Despite the critical need for structured documentation, the current practice often relies on free-text recordings, which poses challenges for scalable intervention analysis; however, the introduction of Large Language Models (LLMs) offers a promising solution by enabling the automatic extraction of adverse event details from procedural reports, without altering existing documentation practices. MethodsWe analyzed 672 endoscopy reports, using OpenAI’s GPT-4 and Llama-2 based models to structure the data in JSON for efficient analysis. We used an automated LLM-pipeline to extract adverse events such as bleeding, perforation, and aspiration. The dataset was divided into a proof of concept set (PoC-S) with n=171 reports, on which we explored prompt engineering to improve the performance of the models. The final analysis was run on an additional external test set of 501 reports (TS). ResultsGPT-4 showed high accuracy, with a sensitivity of 97% and specificity of 92% in the PoC-S and 91% and 96% respectively in the TS. GPT-4 use in real-world settings is limited by privacy concerns. Conversely, Llama-2 based models, especially the Llama-2 variants fine-tuned for German language, demonstrated comparable performance (PoC-S: sensitivity 94%, specificity 92%, CS: sensitivity 89%, specificity 93%) and offered a viable, privacy-compliant alternative. These models' effectiveness was further influenced by the method of prompt engineering, with experiments showing that the specificity and sensitivity could vary substantially based on the inclusion of specific prompt features, underscoring the importance of tailored prompt design. ConclusionApplying LLMs to extract structured medical information, particularly from endoscopy reports, offers an efficient, scalable, and adaptable documentation method that captures adverse events accurately with low error rate. It facilitates immediate quality reporting and reduces manual documentation efforts.

Environmental Wisdom Reflected in Uluan Pantun from a Symbolic Interactionism Perspective

Traditional oral literature has long served to preserve and pass down cultural values and wisdom. In the Uluan society of South Sumatra, pantun, a traditional Malay poetic form, plays a central role in communicating messages related to societal norms and environmental stewardship. This study explores the environmental wisdom embedded in Uluan pantun, using a symbolic interactionism perspective to examine how these oral traditions convey ecological messages. The research employs a qualitative methodology with an ethnographic communication approach. Data were collected through documentation of ancient pantun texts, in-depth interviews with cultural practitioners and local community members, participatory observation in key Uluan regions, and focus group discussions (FGD) to provide a comprehensive view of how pantun is actualized in contemporary environmental conservation efforts. The results show that pantun is an important medium for conveying explicit and implicit messages about the natural environment, reflecting the community’s deep connection with nature. However, modern challenges such as deforestation and land degradation have threatened the sustainability of these traditions. The novelty of this research lies in its examination of pantun as an instrument for ecological communication, an area that has received little attention in previous studies. The findings imply that revitalizing the ecological messages within pantun could significantly promote environmental awareness and community-driven conservation in Uluan society today.

Text Document Clustering Using Chaotic Northern Goshawk Optimization with K-means Algorithm

Text Document Clustering Using Chaotic Northern Goshawk Optimization with K-means Algorithm

Translation Equivalence Degrees among Indonesian EFL Undergraduate Students

PurposeThe way to produce an equivalent translation text appears hard that every translation work should engage with diverse language and cultural systems. The issues are expected to affect both translation students and professional translators. Therefore, this current work aims to discover in-depth information about translation equivalence degrees among Indonesian EFL undergraduate students.MethodThis study employed qualitative content analysis. The research data included documentation of the translation texts from English into the Indonesian language, which resulted in 22 students majoring in English education at a public university in Banten Province, Indonesia. The source language texts were derived from the news-item texts published in national newspapers. The data analysis procedure comprised comparing the two texts, classifying, discussing, drawing conclusions, and making interpretations. Results/findingsThe study of the translation texts revealed that 11 texts (50%) referred to near-optimal translation, six texts (27%) to partial translation, and five texts (23%) to poor translation.ConclusionGiven that none of the students' translation outputs achieved the optimal equivalency; this conclusion suggests that students' translation knowledge and skills still need to be improved by regular practice and discussion at each translation course meeting.

Generating Actionable Insights from Patient Medical Records and Structured Clinical Knowledge.

While adherence to clinical guidelines improves the quality and consistency of care, personalized healthcare also requires a deep understanding of individual disease models and treatment plans. The structured preparation of medical routine data in a certain clinical context, e.g. a treatment pathway outlined in a medical guideline, is currently a challenging task. Medical data is often stored in diverse formats and systems, and the relevant clinical knowledge defining the context is not available in machine-readable formats. We present an approach to extract information from medical free text documentation by using structured clinical knowledge to guide information extraction into a structured and encoded format, overcoming the known challenges for natural language processing algorithms. Preliminary results have been encouraging, as one of our methods managed to extract 100% of all data-points with 85% accuracy in details. These advancements show the potential of our approach to effectively use unstructured clinical data to elevate the quality of patient care and reduce the workload of medical personnel.

Text Summarization and Document summarization using NLP

Background: Automatic text summarization has become increasingly crucial in navigating the ever- growing ocean of textual information. This research delves into exploring the potential of Natural Language Processing (NLP) techniques for creating efficient and informative summaries. We implemented and evaluated models based on Long Short-Term Memory (LSTM) networks, Sequence-to-Sequence (Seq2Seq) architectures, and transformer-based approaches. By leveraging these powerful algorithms, we aimed to generate concise summaries that capture the essence of the original text. The evaluation highlighted the strengths and limitations of each approach, showcasing the potential of NLP for text summarization while acknowledging the remaining challenges. This research not only contributes to the ongoing discussion on textsummarization techniques but also opens doorsfor further exploration, including integrating domain-specific knowledge, personalizing summaries based on user preferences, and applying these techniques to real-world information overload situations. Ultimately, this work underscores the promise of NLP-driven text summarization in facilitating efficient information access, comprehension, and utilization across various domains. Keywords: Natural Language Processing(NLP), Automatic Text Summarization, Real-world applications.

Протекционистская языковая политика в Министерстве обороны Российской федераци

The article substantiates the role of protectionist language policy in the light of modern problems of language safety and the need to preserve and maintain the Russian language as the state language. It is proposed to generalize positive experiences. As a part of this task, a set of measures is considered to maintain and use the Russian language, functioning as the state language, applied in the central apparatus of the Ministry of Defense of the Russian Federation. The Regulations of the Russian Ministry of Defense, the Instructions for office work in the Armed Forces of the Russian Federation, methodological manuals for the preparation of documentation have been studied, and the everyday practice of submitting documents and the organizational component of the army language policy have been examined. The presence (and the compliance) of strict requirements for the normative use of the Russian language, the functioning and consistency and stability of terminology, the practice of documentation and genre features of texts, the difficulties of the Russian language, stable phrases and abbreviations has been established. The wording of the rules is concise and accompanied by detailed examples of their use. Particularly noted is the extremely significant resistance to translingualism (and, in fact, to pidginization) in the context of the globalization reduction of languages. Opposition to pidginization is expressed by a ban on foreign language inclusions in texts, a negligible number of borrowings, and the almost exclusive use of the Cyrillic alphabet. A conclusion is drawn about the positive role of the Ministry of Defense in preserving and maintaining the Russian language, functioning as a state language.The article substantiates the role of protectionist language policy in the light of modern problems of language safety and the need to preserve and maintain the Russian language as the state language. It is proposed to generalize positive experiences. As a part of this task, a set of measures is considered to maintain and use the Russian language, functioning as the state language, applied in the central apparatus of the Ministry of Defense of the Russian Federation. The Regulations of the Russian Ministry of Defense, the Instructions for office work in the Armed Forces of the Russian Federation, methodological manuals for the preparation of documentation have been studied, and the everyday practice of submitting documents and the organizational component of the army language policy have been examined. The presence (and the compliance) of strict requirements for the normative use of the Russian language, the functioning and consistency and stability of terminology, the practice of documentation and genre features of texts, the difficulties of the Russian language, stable phrases and abbreviations has been established. The wording of the rules is concise and accompanied by detailed examples of their use. Particularly noted is the extremely significant resistance to translingualism (and, in fact, to pidginization) in the context of the globalization reduction of languages. Opposition to pidginization is expressed by a ban on foreign language inclusions in texts, a negligible number of borrowings, and the almost exclusive use of the Cyrillic alphabet. A conclusion is drawn about the positive role of the Ministry of Defense in preserving and maintaining the Russian language, functioning as a state language.

Toward the Adaptive Reuse of Vernacular Architecture: Practices from the School of Porto

Strategies for the adaptive reuse of vernacular architecture are of utmost importance in the current context of social, economic, and environmental vulnerability. This article examines the design strategies of adaptive reuse in three cases of renowned architects of the so-called School of Porto developed across the second half of the 20th century, specifically between 1956 and 1991. The paper aims to introduce a new and deeper knowledge of the selected practices by critically documenting the whole process of the intervention (before, during, after) and not only the final result, as is common practice in specialized publications. The research methodology combines the bibliographical and archival research and interpretation of diverse graphic, photographic, and textual documentation with the production of analytical drawings. The demolitions/additions color code (black/yellow/red) is applied to plans, sections, and elevations as an essential tool for understanding and communicating the transformations undertaken. The selected case studies are Além House (1956–1967) by Fernando Távora, Alcino Cardoso House (1971–1973; 1988–1991) by Álvaro Siza, and the House in Gerês (1980–1982) by Eduardo Souto de Moura. These projects show different strategies of intervention in built heritage, providing lessons on the reactivation of obsolete or abandoned rural constructions with new functions that are compatible with the preservation of their values (historical, landscape, constructive, social, and aesthetic) and guidelines for sustainable reuse.

From Field to Circular Economy: Evaluating Kenaf’s Potential Through Environmental Economics and Design

Circularity collaboration between economics and design is crucial to work together towards a common goal of sustainability through the exploration of renewable resources such as kenaf (Hibiscus cannabinus), a fast-growing and versatile plant that has great potential as a sustainable raw material. However, the full potential of kenaf has not yet been fully explored, especially in terms of its economic and environmental benefits, as well as its application in circular design principles. Hence, the study aims to demonstrate the availability, technological processing, and socioeconomic implications of kenaf. Although numerous research has been undertaken on this plant, it is vital to revisit its potential from various viewpoints to maximize its application. This paper evaluates the role of kenaf from its early cycle into the production process in promoting its potential for environmental economics by considering circular design principles. By analyzing case studies and current market applications, the methodology used in this study involves reviewing the previous study and text documentation that provides insights into the potential of kenaf usage. The findings suggest that kenaf, when utilized effectively, can significantly contribute to resource efficiency, waste reduction, and overall environmental sustainability, positioning it as a key component in the shift towards a circular economic and circular design framework. Exploration of kenaf potential in this study not only focuses on recycling, reuse, and regeneration but also proposes a redevelopment approach for its underdeveloped materials requires collaboration between economic and design principles. Interdisciplinary studies through these field combinations can develop an efficient, productive, and sustainable economic system that would expedite the shift toward a circular economy and support the development of sustainability goals.

Converting Text Documents into Graph-based Documents with Local Discourse Structure and Semantic Hierarchy

Graph-based documents are anticipated to offer improved ease of creation and interpretation for both human and machine entities compared to textual counterparts, leading to an expected increase in societal adoption. However, graph-based documents tend to become more complex than textual documents, posing challenges in the transitioning from text to graph formats. The objective of this paper is to elucidate a methodology for efficiently creating large graph-based documents while managing their complexity. We propose a method to convert textual documents into graph-based documents through iterative localized operations, using directed discourse relations and a semantic hierarchy provided by a transformation algorithm. Empirical findings validate that this method effectively regulates complexity and enables graph creation for large texts. Additionally, we conducted extractive summarization from the generated graphs, verifying that the semantic structure is effectively integrated into the graph.

Managing “the shapeless mass” in the digital age

In his 1927 “Archeion” article, On issues of modern Polish archival science (Z zagadnień nowożytnej archiwistyki polskiej), the renowned Polish archivist Kazimierz Konarski wrote of the challenge of managing the “shapeless mass” of modern archives in the 20th century. In this presentation, Canadian archival consultant and independent scholar Laura Millar examines the records and archives management challenge of the 21st century: managing the “shapeless mass” of electronic records inundating governments and organizations in the digital age. The “flood” of physical and textual documentation that Dr. K. Konarski faced a century ago has become a torrent of invisible, omnipresent, elusive electronic records – photographs, audio recordings, databases, AI-generated data, and more – stored in countless computer hard drives, cloud storage systems, and personal digital devices. How can the archivist manage digital sources that are both ephemeral and eternal at the same time? To ensure society has the documentary evidence it needs, L. Millar argues that archivists must our shift attention away from the care of static, “old” archives and focus more directly on the work of capturing and recording the present. The digital age may transform our methods, but our mission remains the same: to help society capture, protect, and make available for use essential sources of documentary proof.

Improved Meta-Heuristic Model for Text Document Clustering by Adaptive Weighted Similarity

This paper intends to develop a novel framework for text document clustering with the aid of a new improved meta-heuristic algorithm. Initially, the features are selected from the text document by subjecting each word under Term Frequency-Inverse Document Frequency (TF-IDF) computation. Subsequently, centroid selection plays a vital role in cluster formation, which is done using a new Improved Lion Algorithm (LA) termed as Cross over probability-based LA model (CP-LA). As a novelty, this paper introduced a new inter and intracluster similarity model. Moreover, this centroid selection is made in such a way that the proposed adaptive weighted similarity should be minimal. Based on the characteristics of the document, the weights are automatically adapted with the similarity measure. The proposed adaptive weighted similarity function involves the inter-cluster, and intra-cluster similarity of both ordered and unordered documents. Finally, the superiority of the proposed over other models is proved under different performance measures.

Semantic Annotation Based Mechanism for Web Service Discovery and Recommendation

Web Mining is regarded as one among the data mining techniques that aids in fetching and extraction of necessary data from the web. Conversely, Web usage mining discovers and extracts essential patterns usage over the webs which are being further utilized by various web applications. In order to discover and explore web services that are registered with documents of Web Services-Inspection, Discovery and Integration registry, Universal Description wants specific search circumstance similar to URL, category and service name. The document of Web Service Description Language (WSDL) offers a condition of the web services customers to take out operations, communications and the service format of right message. Therefore, WSDL is being utilized together with semantic explanation dependent substantiation for the extraction of different web services for related purpose, other supporting operations and attributes. The reason is that there subsist different web services having corresponding functionalities however altered or changeable attributes that are non–functional. Resultant, recognize the preeminent web service become tiresome for the user. A method is projected which caters the analysis of service resemblance with the aid of semantic annotation and machine learning (ML) algorithms depending on the analysis intended for enhancing the classification through capturing useful web services semantics related with real world. The emphasizes on the research technique of choosing preeminent web service for the user based on the semantic annotation. The research work in turn recommends a web mining technique that determines the best web service automatically thus ranking concepts in service textual documentation and classifies services on behalf of particular domains. Parallel computation is made easy with web services. The different management stages in the system of recommendation entail collection of dataset through WSDL on the semantic annotation basis, thereby recognizing the best service with the DOBT-Dynamic operation dependent discovering method, ranking through mechanisms MDBR - Multi-Dimensional based ranking, recommendation and classification. In this work, it has been employed a combination of fundamental ML estimators, namely Multinomial Naive Bayes (MNB) and Support Vector Machines (SVM), as well as ensemble techniques such as Bagging, Random Forests, and AdaBoost, to perform classification of Web services. It was observed from the investigate work that the adapted system of best web services recommendation defers high performance in contradiction of the existing recommendation technique regarding accuracy, efficiency in addition to processing time.

Architect Hans Poelzig: a project for Ukraine

The paper examines one of the fragments of the creative heritage of the famous German architect Hans Poelzig: his competition project of the State Ukrainian Theatre of Mass Musical Action for 4000 seats for Kharkiv. The project is viewed through the prism of little-known competitive events of 1930, which makes it possible to decipher its architectural, compositional, urbanistic and functional ideas, to reveal its symbolism. The study is based on the architect’s original drawings preserved in the archive, primary sources of the early 1930s, biographical and critical works of other authors dedicated to the nominees of the Kharkiv competition, as well as on a comparative and meaningful analysis of architectural graphics and textual documentation.

Learning from West African storytellers

Several research works propose non-textual alternatives to textual documentation and similar forms of representing information in software development. This is because of the problems that stem from writing these documents, which range from incomprehensible requirements to ambiguous user stories. The various proposals of researchers often contain some trace of oral or visual communication. In this paper, we study the implications of eliminating textual communication and substituting unnecessary writing by extracting the values of West African oral storytellers. Traditional West African communities did not make use of writing for thousands of years and yet their legends, customs, beliefs, and knowledge were effectively transmitted across several generations. How did they manage to accomplish this? What can we learn from their storytellers? How can these lessons be applied to software products? These are all questions that this paper attempts to answer. Perhaps if we fully understand how they operated, then we can target our written communication to the activities where it is needed instead of spreading writing across plenty of tasks as it is currently. To achieve this, we performed an analysis of the two domains: West African oral storytelling and software development and found similarities, then selected some key elements from oral storytelling and explained how they can have relevance in software development. The theme directly encompasses diversity and inclusion by bringing into software engineering a perspective of a region where its literacy research is scarcely being explored. The study found that traditional oral storytelling can provide insights into effective communication and audience engagement, and identified four ways in which software development can be compared to oral storytelling. The study also found that certain elements of storytelling, such as audience relationship, story structure, parables and proverbs, and community relaxation and support, can be applied to writing tasks in software development.

An Efficient Information Extraction Mechanism with Page Ranking and a Classification Strategy based on Similarity Learning of Web Text Documents

Users have recently had more access to information thanks to the growth of the www information system. In these situations, search engines have developed into an essential tool for consumers to find information in a big space. The difficulty of handling this wealth of knowledge grows more difficult every day. Although search engines are crucial for information gathering, many of the results they offer are not required by the user because they are ranked according on user string matches. As a result, there were semantic disparities between the terms used in the user inquiry and the importance of catch phrases in the results. The problem of grouping relevant information into categories of related topics hasn't been solved. A Ranking Based Similarity Learning Approach and SVM based classification frame work of web text to estimate the semantic comparison between words to improve extraction of information is proposed in the work. The results of the experiment suggest improvisation in order to obtain better results by retrieving more relevant results.