bluuebunny/crossref_metadata_2025 huggingface dataset:
Generating Phonetic Embeddings for Bulgarian Words with Neural Network
Authors:   Faculty of Mathematics and Informatics Sofia University, ”St. Klimenth Ohridski”, Karev Lyuboslav , Koychev Ivan ,   Faculty of Mathematics and Informatics Sofia University, ”St. Klimenth Ohridski”
Published: November 2024

Word embeddings can be considered the cornerstone of modern natural language processing. They are used in many NLP tasks and allow us to create models that can understand the meaning of words. Most word embeddings model the semantics of the words. In this paper, we create phoneme-based word embeddings, which model how a word sounds. This is accomplished by training a neural network that can automatically generate transcriptions of Bulgarian words. We used the Jaccard index and direct comparison metrics to measure the performance of neural networks. The models perform nearly perfectly with the task of generating transcriptions. The model’s word embeddings offer versatility across various applications, with its application in automatic paronym detection being particularly notable, as well as the task of detecting the language of origin of a Bulgarian word. The performance of this paronym detection is measured with the standard classifier metrics - accuracy, precision, recall, and F1.
Classifying Multi–Word Expressions in the Latvian Monolingual Electronic Dictionary Tēzaurs.Lv
Authors:   Institute of Mathematics and Computer Science, University of Latvia, Rituma Laura , Rituma Laura ,   Institute of Mathematics and Computer Science, University of Latvia, Nespore-Berzkalne Gunta ,   Institute of Mathematics and Computer Science, University of Latvia, Klints Agute ,   Institute of Mathematics and Computer Science, University of Latvia, Lokmane Ilze ,   Institute of Mathematics and Computer Science, University of Latvia, Stade Madara ,   Institute of Mathematics and Computer Science, University of Latvia, Paikens Peteris ,   Institute of Mathematics and Computer Science, University of Latvia
Published: November 2024

The electronic dictionary Tezaurs.lv contains more than 400,000 entries from which 73,000 entries are multi-word expressions (MWEs). Over the past two years, there has been an ongoing division of these MWEs into subgroups (proper names, multi-word terms, taxa, phraseological units, collocations). The article describes the classification of MWEs, focusing on phraseological units (approximately 7,250 entries), as well as on borderline cases of phraseological unit types (phrasemes and idioms) and different MWE groups in general. The division of phraseological units depends on semantic divisibility and figurativeness. In a phraseme, at least one of the constituents retains its literal sense, whereas the meaning of an idiom is not dependent on the literal sense of any of its constituents. As a result, 65919 entries of MWE have been manually classified, and now this information of MWE type is available for the users of the electronic dictionary Tezaurs.lv
Complex Word Identification for Italian Language: A Dictionary–Based Approach
Authors:   University of Bologna, Italy, Occhipinti Laura
Published: November 2024

Assessing word complexity in Italian poses significant challenges, particularly due to the absence of a standardized dataset. This study introduces the first automatic model designed to identify word complexity for native Italian speakers. A dictionary of simple and complex words was constructed, and various configurations of linguistic features were explored to find the best statistical classifier based on Random Forest algorithm. Considering the probabilities of a word to belong to a class, a comparison between the models’ predictions and human assessments derived from a dataset annotated for complexity perception was made. Finally, the degree of accord between the model predictions and the human inter-annotator agreement was analyzed using Spearman correlation. Our findings indicate that a model incorporating both linguistic features and word embeddings performed better than other simpler models, also showing a value of correlation with the human judgements similar to the inter-annotator agreement. This study demonstrates the feasibility of an automatic system for detecting complexity in the Italian language with good performances and comparable effectiveness to humans in this subjective task.
Assessing Reading Literacy of Bulgarian Pupils with Finger–Tracking
Authors:   Biomedical Campus University, Rome Italy, Lento Alessandro ,   Italian National Research Council, Institute for Computational Linguistics, Nadalini Andrea ,   Italian National Research Council, Institute for Computational Linguistics, Ferro Marcello ,   Italian National Research Council, Institute for Computational Linguistics, Marzi Claudia ,   Italian National Research Council, Institute for Computational Linguistics, Pirrelli Vito ,   Institute for Bulgarian Language, Bulgarian Academy of Sciences, Dimitrova Tsvetana ,   Institute for Bulgarian Language, Bulgarian Academy of Sciences, Kukova Hristina ,   Institute for Bulgarian Language, Bulgarian Academy of Sciences, Stefanova Valentina ,   Institute for Bulgarian Language, Bulgarian Academy of Sciences, Todorova Maria ,   Institute for Bulgarian Language, Bulgarian Academy of Sciences, Koeva Svetla
Published: November 2024

The paper reports on the first steps in developing a time-stamped multimodal dataset of reading data by Bulgarian children. Data are being collected, structured and analysed by means of ReadLet, an innovative infrastructure for multimodal language data collection that uses a tablet as a reader’s front-end. The overall goal of the project is to quantitatively analyse the reading skills of a sample of early Bulgarian readers collected over a two-year period, and compare them with the reading data of early readers of Italian, collected using the same protocol. We illustrate design issues of the experimental protocol, as well as the data acquisition process and the post-processing phase of data annotation/augmentation. To evaluate the potential and usefulness of the Bulgarian dataset for reading research, we present some preliminary statistical analyses of our recently collected data. They show robust convergence trends between Bulgarian and Italian early reading development stages.
Educational Horizons: Mapping the Terrain of Artificial Intelligence Integration in Bulgarian Educational Settings
Authors:   University of Plovdiv “Paisii Hilendarski”, Kurshumova Denitza
Published: November 2024

The role of artificial intelligence in education (AIEd) has recently become a major topic of discussion and future planning. This article presents data from a large-scale survey involving 1463 Bulgarian educators in primary, secondary, and high schools. The results revealed that 70.30% of the teachers were familiar with or somewhat familiar with the existence of AI applications. Chatbots were the most popular among the surveyed teachers, with ChatGPT ranking as the most familiar. The teachers were almost equally split between those who reported use and those who declared nonuse of AI technology for instructional purposes. A significant association was found between the teachers’ familiarity with and use of AI technology and their age-related generational traits. The younger educators (up to 40 years of age) were associated with higher use of AI technology as a support tool for creating lesson plans, lesson content, tests, and exams. The outlined tendencies can be used to inform policy, professional development, and future research in the realm of AI-driven education.
Evidential Auxiliaries as Non–Reliability Markers in Bulgarian Parliamentary Speech
Authors:   Sofia University Saint Kliment Ohridski, Tarpomanova Ekaterina
Published: November 2024

In the evidentiality system of Bulgarian, there are three evidential auxiliaries that form complex verbal forms. The paper analyzes their potential to mark non-reliability in political discourse by using the ParlaMint-BG corpus of parliamentary debates. The method of the study includes detection, categorisation and context analysis of the evidentials formed with auxiliaries. The results prove that the evidential auxiliaries function as markers of non reliability, especially in argumentative text type such as political discourse.
Lexical Richness of French and Quebec Journalistic Texts
Authors:   Université du Québec en Outaouais, Dankova Natalia
Published: November 2024

This paper presents some results of a quantitative study that focuses on the variety and word frequency in texts from a comparative perspective. The study aims to analyze and compare French and Quebec journalistic texts on political and cultural topics written in French and recently published in major newspapers such as Le Monde, le Figaro, Le Devoir, etc. The statistical analysis concerns the number of different words in the text, the number of different adjectives, the number of different verbs (and also passive structures, participles and gerunds which contribute to syntactic and stylistic sophistication), and the number of hapaxes. French texts from France exhibit greater lexical richness and sophistication: they contain more adjectives, a greater variety of adjectives, as well as more participles and gerunds compared to French texts from Quebec. The originality of the study lies in the fact that it analyzes variation in French using a lexicometric approach.
A Corpus of Liturgical Texts in German: Towards Multilevel Text Annotation
Authors:   St Petersburg State University, Khokhlova Maria , Koryshev Mikhail ,   St Petersburg State University
Published: November 2024

The aim of the study is to create a “documented” literary and theological history of German Catholic hymnography. The paper focuses on the creation of a corpus of liturgical texts in German and describes the first stage of annotation dealing with the metatextual markup of Catholic hymns. The authors dwell in detail on the parameters of the multi-level classification of hymn texts they developed, which allows them to differentiate hymns on different grounds. The parameters include not only characteristics that represent hymns (the period and the source of their origin, rubrics, musical accompaniment), but also ones that are inherent for strophes. Based on the created markup, it is possible to trace general trends in texts divided according to certain meta-features. The developed scheme of annotation is given on the example of the hymnbook Gotteslob (1975). The results present statistics on different parameters used for hymn description.
On a Hurtlex Resource for Bulgarian
Authors:   Department of Bulgarian Language Sofia University ”St. Kl. Ohridski”, Osenova Petya
Published: November 2024

The paper reports on the cleaning of the Hurtlex lexicon for Bulgarian as part of the multilingual Hurtlex resource. All the challenges during the cleaning process are presented, such as: deleting strings or lexica that are clear errors from the automatic translation, establishing criteria for keeping or discarding a lexeme based on its meaning and potential usages, contextualizing the lexeme with the meaning through an example, etc. In addition, the paper discusses the mapping of the offensive lexica to the BTB-Wordnet as well as the system that has been used.
Deep Learning Framework for Identifying Future Market Opportunities from Textual User Reviews
Authors:   Bulgarian Academy of Sciences, Kralev Jordan
Published: November 2024

The paper develops an application of design gap theory for identification of future market segment growth and capitalization from a set of customer reviews for bought products from the market in a given past period. To build a consumer feature space, an encoded-decoder network with attention is trained over the textual reviews after they are pre-processed through tokenization and embedding layers. The encodings for product reviews are used to train a variational auto encoder network for representation of a product feature space. The sampling capabilities of this network are extended with a function to look for innovative designs with high consumer preferences, characterizing future opportunities in a given market segment. The framework is demonstrated for processing of Amazon reviews in consumer electronics segment.
Look Who’s Talking: The Most Frequently Used Words in the Bulgarian Parliament 1990-2024
Authors:   GATE Institute Sofia University “St. Climent Ohridsky”, Margova Ruslana , Bruinsma Bastiaan ,   Chalmers University of Technology
Published: November 2024

In this study we identify the most frequently used words and some multi-word expressions in the Bulgarian Parliament. We do this by using the transcripts of all plenary sessions between 1990 and 2024 - 3,936 in total. This allows us both to study an interesting period known in the Bulgarian linguistic space as the years of “transition and democracy”, and to provide scholars of Bulgarian politics with a purposefully generated list of additional stop words that they can use for future analysis. Because our list of words was generated from the data, there is no preconceived theory, and because we include all interactions during all sessions, our analysis goes beyond traditional party lines. We provide details of how we selected, retrieved, and cleaned our data, and discuss our findings.
Mitigating Hallucinations in Large Language Models via Semantic Enrichment of Prompts: Insights from BioBERT and Ontological Integration
Authors:   Sofia University “St. Kliment Ohridski”, Penkov Stanislav
Published: November 2024

The advent of Large Language Models (LLMs) has been transformative for natural language processing, yet their tendency to produce "hallucinations"—outputs that are factually incorrect or entirely fabricated—remains a significant hurdle. This paper introduces a proactive methodology for reducing hallucinations by strategically enriching LLM prompts. This involves identifying key entities and contextual cues from varied domains and integrating this information into the LLM prompts to guide the model towards more accurate and relevant responses. Leveraging examples from BioBERT for biomedical entity recognition and ChEBI for chemical ontology, we illustrate a broader approach that encompasses semantic prompt enrichment as a versatile tool for enhancing LLM output accuracy. By examining the potential of semantic and ontological enrichment in diverse contexts, we aim to present a scalable strategy for improving the reliability of AI-generated content, thereby contributing to the ongoing efforts to refine LLMs for a wide range of applications.
‘A “Dipdive” into Motion: Exploring Lexical Resources towards a Comprehensive Semantic and Syntactic Description
Authors:   Institute for Bulgarian Language, Bulgarian Academy of Sciences, Svetlozara Leseva
Published: November 2024

In this paper I illustrate the semantic description of verbs provided in three semantic resources (FrameNet, VerbNet and VerbAtlas) in comparative terms with a view to identifying common and distinct components in their representation and obtaining a preliminary idea of the resources’ interoperability. To this end, I provide a comparison of a small sample of motion verbs aligned with semantic frames and classes in the three resources. I also describe the semantic annotation of Bulgarian motion verbs using the framework defined in the Berkeley FrameNet project and its enrichment with information from the other two resources, which has been enabled by the mapping between: (i) their major semantic units – FrameNet frames, VerbNet classes and VerbAtlas frames, and (ii) their ’building blocks’ – frame elements (FrameNet )and semantic roles (VerbNet, VerbAtlas).
Large Language Models in Linguistic Research: The Pilot and the Copilot
Authors:   Institute for Bulgarian Language, Bulgarian Academy of Sciences, Koeva Svetla
Published: November 2024

In this paper, we present two experiments focussing on linguistic classification and annotation of examples, using zero-shot prompting. The aim is to show how large language models can confirm or reject the linguistic judgements of experts in order to increase the productivity of their work. In the first experiment, new lexical units evoking a particular FrameNet semantic frame are selected simultaneously with the annotation of examples with the core frame elements. The second experiment attempts to categorise verbs into the aspectual classes, assuming that only certain combinations of verbs.
Identifikasi Elemen Arsitektur Neo-Vernakular pada Perancangan Hotel Resort di Pantai Kuta, Bali
Authors: Karim Abdul , Kridarso Etty R. , Iskandar Julindiani
Published: November 2024

Abstrak
Arsitektur Neo Vernakular  adalah salah satu paham atau aliran yang berkembang pada era Post-Modern, yaitu aliran arsitektur yang muncul pada pertengahan tahun 1960-an. Post-Modern lahir disebabkan pada era modern timbul protes dari para arsitek terhadap pola-pola yang berkesan monoton (bangunan berbentuk kotak-kotak). Sedangkan gaya Arsitektur Tradisional Bali adalah corak penampilan arsitektur yang dapat memberikan citra/nuansa arsitektur berlandaskan budaya Bali yang dijiwai oleh agama Hindu melalui penerapan berbagai prinsip bentuk yang mengandung identitas maupun nilai-nilai arsitektur. Pengaplikasian Arsitektur Neo Vernakular pada bangunan bangunan di bali tidak terlepas dari usaha untuk menjaga arsitektur lokal agar tidak terlupakan akibat perkembangan zaman. Penelitian ini mengambil kasus hotel resort di kabupaten Badung sebagai objek yang diteliti mengadaptasikan bentuk Arsitektur Tradisional Bali di masa kini. Penelitian ini menggunakan metode kualitatif data di peroleh dari sumber sekunder berupa literatur dan dokumen lain selanjutnya  dianalisis secara  deskriptif dengan menilai hasil design dalam konteks arsitektur neo vernakular. Dengan menganalisis unsur unsur element neo vernakular pada  bangunan hotel resort yang saya rancang disimpulkan bahwa secara umum kriteria, ciri dan prinsip tema Arsitektur Neo Vernakular adalah Usaha memberikan nilai kebaruan terutama terlihat dari reinterpretasi terhadap bentuk-bentuk detail, hiasan, prinsip struktur dan ornamen serta pemakaian beton ekspos bersanding dengan bahan-bahan lokal. Bentuk dasar bangunan persegi yang sangat kuat dan dominan merupakan unsur yang paling  tidak berubah dari bentuk aslinya.Pada penerapan nya sudah memenuhi 75%  design memenuhi konsep arsitketur neo vernakular
Pengaruh Revolusi Digital Dalam Peningkatan Kreativitas Arsitektur Dan Interior
Authors: Widiastuti Santi , Purwanto L.M.F. , Sanjaya Ridwan , Satwiko Prasasto
Published: November 2024

Karya ini berkaitan dengan studi tentang keterampilan dan kemampuan mengembangkan imajinasi dan kreativitas mahasiswa seni serta peran revolusi dan desain digital ide untuk virtual arsitektur di mana ruang virtual ditentukan oleh ruang yang dirancang secara elektronik dan disajikan dalam bentuk kompetisi, termasuk bisnis beberapa diantaranya sudah dilaksanakan dan ada pula yang belum dilaksanakan. Hal tersebut mencerminkan upaya untuk mengubah fantasi menjadi kenyataan dengan penciptaan solusi yang lebih fleksibel untuk desain ruang non-tradisional masa depan dengan yang baru ide desain. Masalah penelitiannya adalah menghubungkan perkembangan teknis dengan pengembangan pemikiran desain generasi muda dan mahasiswa arsitektur interior melalui pengujian ide-ide desain baru. Studi ini menyoroti hal tersebut merancang pemikiran hipotetis dan efek imajinasi sebagai turunannya pengembangan kemampuan kreatif desain bagi mahasiswa arsitektur interior sesuai aturan dan ketentuan yang mengatur proses desain menggunakan modern teknik digital untuk mencapai hasil terbaik, dimana kreativitas saat ini menjadi sebuah industri yang dapat diterapkan pada mahasiswa seni arsitektur pada umumnya dan interior khususnya, untuk merangsang dan mengembangkan mereka serta melepaskan imajinasi mereka untuk mencapai hasil terbaik selain rehabilitasi generasi baru yang berbakat desainer untuk menghadapi perkembangan desain di sekitar kita karena keterampilan adalah anugerah yang memerlukan pengembangan berkelanjutan. Dengan mempelajari unsur kreativitas, maka rasio karya kreatif tidak melebihi 4% yang memerlukan peninjauan ulang mekanisme pengembangan ide desain untuk merangsang ide-ide kreatif anak muda. Revolusi digital telah berhasil mengintegrasikan banyak teknologi aplikasi dan meluncurkannya ke aplikasi yang lebih kompleks, sehingga menghasilkan pergeseran dramatis dalam media yang digunakan dalam arsitektur dan desain interior, baik sebagai sistem atau praktik dari sketsa hingga desain. Proses desain yang sampai akhir-akhir ini sepertinya tidak terpengaruh dengan intrusi sarana elektronik yang kini bermunculan siap untuk mendefinisikan ulang metodologinya untuk berintegrasi dan menyatu dengan komputer. Hal tersebut merupakan perubahan desain yang tidak dapat dianggap sebagai fenomena sementara dan cepat berlalu. Komputer akan menempati tempat yang menonjol sebagai bagian dari lingkungan desain itu mencirikan abad ke-21. Selain itu, perkembangan seni desain akan berhubungan erat dengan komputer di tahun-tahun mendatang.
Perencanaan Lanskap Kampus Itera untuk Menciptakan Ruang Ekosistem yang Lenting dan Menyembuhkan
Authors: Lesmana Tasya Salsabila , Pratiwi Rian Adetiya
Published: November 2024

Institut Teknologi Sumatera (ITERA) pada saat ini masih dalam tahap pembangunan beberapa area baru, yang bisa berdampak terhadap ekosistem dari lanskap kampus. Hal tersebut dapat berpengaruh terhadap visi ITERA sebagai forest campus. Dengan begitu, diperlukan upaya untuk menciptakan resiliency pada lanskap Kampus ITERA. Selain berdampak pada ekosistem, kesehatan civitas akedemika ITERA juga sangat dipengaruhi oleh kondisi lingkungan kampus, dimana lingkungan kampus dapat menjadi ruang pemulihan di tengah padatnya jadwal, baik secara fisik, maupun mental. Untuk mengatasi permasalahan tersebut, maka diperlukan perencanaan kawasan dengan tujuan mendukung ITERA sebagai forest campus yang resilien dan menciptakan wadah healing bagi civitas akademika ITERA dengan menggunakan pendekatan aspek kebudayaan dari Pulau Sumatera, yaitu seloko dari Suku Anak Dalam sebagai pedoman konsep, dan pelestarian tanaman etnobotani yang digunakan oleh Suku Pepadun. Metode yang digunakan dalam perencanaan terdiri dari beberapa tahap persiapan, yaitu inventarisasi dan analisis, rencana konsep pengembangan, dan rencana pengelolaan. Dari proses tersebut didapatkan hasil berupa masterplan perencanaan kawasan dengan tema “ITERA as a Resilient and Healing Campus Ground”. Penerapan aspek kebudayaan Sumatera efektif dalam menciptakan kondisi yang resilien pada kampus ITERA yang heterogen.
Proactive decisions and stochastic discounting models in risk treatment operations
Authors: Artikis Constantinos T. , Artikis Panagiotis T.
Published: November 2024

It is known the strong practical support of the consideration of fundamental probabilistic concepts as structural factors for the implementations of stochastic modeling operations. It is widely acknowledged that random sums, stochastic integrals, and stochastic models are probabilistic concepts of exceptional significance. The paper focuses on the development of stochastic models by establishing interconnections between the very important probabilistic concepts of random sums and stochastic integrals. In addition, the paper demonstrates how such stochastic models can be implemented to incorporate the crucial concept of proactivity in decision making related to risk treatment operations. Clearly, evidence is presented regarding the effectiveness of making proactive decisions in facilitating the design and implementation of risk treatment.
A topological and 3D-geometrical study about an initial skeleton of the 2MASS Pleiades nucleus with DR2 distances
Authors: Castillo F. J. Marco , Usó M. J. Martínez , Ortí J. A. López
Published: November 2024

The appearance of successive versions of the Gaia Data Release has prompted the realization of many works on the Pleiades, whose objectives range from the identification of new stars to the study of the cluster dynamics. Our study has a different focus, although we start by identifying a subset by imposing geometric restrictions on the m45 file from the Gaia website itself. We consider only the 2MASS stars in the file and use the stellar distances adopted in EDR3, applying restrictions concerning a high density in the spatial distribution and small distances between stars. With this denser nucleus, we carry out a study of the three-dimensional point cloud with Topological Data Analysis (TDA) techniques. We investigate its topological and geometrical structure using two TDA methods that provide different results. To clarify this problem, we introduce a dual method over a net of points where null densities are obtained and will be used to discuss loops and voids. Also, two connected components are found, and finally, we will relate the astrophysical properties of these stars for each connected component with the deduced topological-geometrical results. The small set can subsequently be expanded with stars from DR2, not 2MASS.
The Hamilton-Jacobi treatment of complex fields as constrained conformable fractional systems
Authors: Al-khamiseh Bashar. M. , Almalki Adel , Alawaideh Samer
Published: November 2024

We examine the fractional complex scalar field within a limited system and apply the Hamilton-Jacobi method to it. As a result, we obtain the simplified stage space Hamiltonian density excluding needing additional gauge fixing constraints or conformable fractional Lagrange multipliers. We also explore the quantization of this system. Alternatively, we can derive the path integral for these systems by integrating over the canonical phase space coordinates (φ,A), which eliminates the need for any gauge fixing constraints. On another note, our motivation to investigate the parameterization of conformable fractional time stems from the drawbacks of the conventional Hamiltonian approach in classical fields. Although the Lagrangian formulation maintains relativistic covariance, the unique role of time prevents the construction of a Hamiltonian formulation that treats x, y, z, and time symmetrically.
Convergent piecewise series solutions of ordinary differential equations
Authors: Pakdemirli Mehmet
Published: November 2024

The series approximations of ordinary differential equations usually possess a limited validity range. Outside the convergence interval, the solution does not comply with the real solution. A technique is proposed in this work to expand the validity interval of the series approximations. Solutions are constructed in the vicinity of several points and are joined to each other with satisfaction of the continuity conditions. By employing the piecewise series solutions, the validity range of the approximations can be made to cover the whole domain of interest. In constructing a single analytical expression from the piecewise series, the Gamma Interval function is used. Sample problems of first, second and third order are attacked with the proposed method and comparisons with the numerical and exact solutions are given. It is shown that the method can be effectively used in constructing approximate solutions of ordinary differential equations.
Touring a Sequence of Spheres in R3
Authors: Chou Chang-Chien
Published: November 2024

How do you touring a sequence of different size of balls and returning to the starting point with a minimum Euclidean travelling path? We present an efficient algorithm to answer the question in this paper. One may say that the above mentioned minimum path, a shortest n‒gon of n‒spheres in three dimensions. Accompanied by three other competing methods: the genetic algorithm, the nearest neighbor algorithm and the random test, all have shown up our proposed algorithm dominates the results in every aspects of spheres distribution. Empirical results have also shown the effectiveness and the quick convergent property about the proposed algorithm. The proposed algorithm can be conducted for the coverage problem of sensor deployment. In addition, it is also called the shortest n‒gon of n‒spheres (particles with necessary volume). Since, practitioners in the fields of computational geometry, material science, solid modeling, 3D printing, computer graphics, or any other kinds of CAD/CAM applications may find merits from this paper.
Bridging economic insights through fixed point theory and game theory applications
Authors: Hajioui Khalid El , Azennar Radouane
Published: November 2024

The purpose of this paper is to contribute to research on fixed point theory and its applications to the game theory. Indeed, we show, under qualification conditions, the existence of a common fixed point for tow multivalued mappings as well as the existence of the solution of a game.
Bayesian prediction intervals for the exponential-type distributions under multiply Type-II censoring data
Authors: Kotb Mohammed S. , Abdel-Aty Yahia
Published: November 2024

In this article, Bayesian predictions (point and interval) for a certain class of exponential-type distributions based on a general multiply type-II censored sample are discussed. The Bayesian prediction intervals are studied under a general conjugate family of prior density functions and the predictive cumulative function is obtained in a one-sample case. For the illustration of the developed results, the Rayleigh and Pareto distributions are used as examples and completed with numerical results.
Improved generalized exponential estimators in simple random sampling without replacement using some transformations
Authors: Singh Poonam , Singh Rajesh
Published: November 2024

This article suggests three generalized exponential estimators using an auxiliary variable for estimating population mean with some transformations. The mean squared error expressions are derived up to the first order approximation for comparing the efficiency of the proposed estimators with the existing estimators in literature. We compared the efficiency of the proposed estimators with the usual mean estimator, [2] ratio estimator, [1] ratio type exponential estimator, [15] and [9] usual regression estimator. It is found that our proposed estimators perform better than these existing estimators in the literature. Findings are empirically verified using three real data sets and a simulation study.
The half-logistic (Type-I)-skew-t model : Comparison of different estimation approaches using monte carlo simulations
Authors: Adubisi O. D. , Abdulkadir A. , Chiroma H.
Published: November 2024

In the paper, we looked at the problem of employing several non-Bayesian estimation approaches to estimate the parameters of the Type-I half-logistic skew-t (TIHLST) model. The maximum likelihood, least squares, weighted least squares, Anderson-Darling, maximum product of spacing, and Cramer-von Mises are the six methods for TIHLST parameter estimation that we examined. The Monte Carlo simulations were used to assess the TIHLST parameter estimations’ finite sample performance. The partial and overall ranks of the estimating techniques for every combination of parameters were used to determine the ordering performance of the six criteria. Based on the overall ranks, the results indicate that the criteria performance is ranked from best to worst using the following estimators: maximum likelihood, weighted least squares, maximum product of spacing, least squares, and Cramer-von Mises for all parameter combinations. Based on an overall rank of 34, we infer that the maximum likelihood criterion fared better than all other criteria. For the TIHLST model, we thereby affirm the supremacy of the maximum likelihood criterion with an overall rank of 34 and the Anderson-Darling criterion with an overall rank of 57.5.
The Marshall-Olkin-exponentiated half logistic-G family of distributions : Model, properties and applications
Authors: Makubate Boikanyo , Chipepa Fastel , Oluyede Broderick , Moagi Gaoganwe
Published: November 2024

A new generalization of the exponentiated half-logistic-G distribution is developed to produce a new family of distributions referred to as the Marshall-Olkin-exponentiated half logistic-G distribution. The new family of distributions is an infinite linear combination of the exponentiated-G family of distributions. We considered some special cases of the new distribution and we conclude that the distribution can handle heavy tailed data and nonmonotonic
hazard rate functions. A simulation study was conducted to assess the consistency of the maximum likelihood estimates. Real data examples are provided to demonstrate the usefulness of the proposed model in comparison with other competing models.
Innovations and Trends in Modern Computer Science Technology – Overview, Challenges and Applications
Authors: Pandikumar S , Thakur Manish Kumar
Published: November 2024

The 21st century stands as a testament to the transformative power of modern computer science, where groundbreaking innovations like Artificial Intelligence (AI), Quantum Computing, the Internet of Things (IoT), Blockchain, and 5G networks have redefined the boundaries of human potential. These technologies are not just theoretical constructs; they are actively shaping industries, revolutionizing economies, and reshaping how society interacts with the digital world.
This book aims to provide readers with a comprehensive understanding of these pivotal advancements, delving into both their theoretical foundations and practical applications. Each chapter serves as a gateway to exploring the intricate nuances of these innovations, from AI's role in redefining healthcare to the influence of quantum computing on cybersecurity. Topics such as IoT and its role in creating smart cities, the integration of 5G in connected systems, and the ethical dilemmas posed by emerging technologies are examined with a balanced perspective.
Evolution and Analysis of Modern Plagiarism Detection Methods: A Systematic Review
Authors: Pandikumar S , Menaka C , T Kiran , Paul Antony T John
Published: November 2024

This systematic review examines the advancement and effectiveness of plagiarism detection methodologies in academic and professional contexts from 2000 to 2024. Through comprehensive analysis of 87 research papers and technical implementations, we evaluate three primary approaches: string-based detection, semantic analysis, and machine learning integration. Our research demonstrates a significant evolution from basic pattern matching to sophisticated neural network-based systems, with modern methods achieving detection accuracy rates up to 98\%. The study reveals that while machine learning approaches show superior performance in complex cases, traditional methods maintain relevance for specific applications. This review contributes to the field by providing a detailed comparative analysis of detection methodologies and identifying critical areas for future development.
A LIME-based Explainable AI for Healthcare IoT: Building Trust in Clinical Decision-Making
Authors: Maharajpet Sheela S , H P Abhilash , Bedre Shrihari R
Published: November 2024

The integration of Artificial Intelligence (AI) and Internet of Things (IoT) devices in healthcare offers vast potential for personalized medicine, remote monitoring, and early disease detection. However, complex Machine Learning (ML) models embedded in these systems often operate as "black boxes," hindering trust and transparency in critical medical decisions. Explainable AI (XAI) emerges as a key solution, aiming to demystify ML models and build trust in healthcare IoT applications. This paper explores the current challenges and opportunities in implementing XAI for healthcare IoT, proposing an architecture and methodologies for explainable clinical decision-making. We discuss promising XAI techniques, the integration of user interfaces for interactive explanations, and potential future directions for this crucial field.
Recognition of Brain Tumors Using Deep Neural Networks Models
Authors: Shivanandhuni Rashmi , Krishna B , Chauhan Gulab Singh , Manasa K , Mohmmad Sallauddin , . Shabana
Published: November 2024

The identification of brain tumors is a significant issue in healthcare. A brain tumor is an abnormal tissue mass where cells multiply rapidly and uncontrollably. Image segmentation helps identify the tumor regions in the brain using MRI scans. Early detection of brain tumors is essential, which can be achieved with machine learning and deep learning algorithms. Our research used different deep learning methods, including VGG-16, ResNet-152, Inception-V3, Inception ResNet-V2, and a Custom Convolution neural networks model to categorize brain tumors. The sample dataset for our research consisted of 1085 tumorous and 980 non-tumorous images from the Kaggle online database. Among all the models, VGG-16 performed the best and achieved 98\% accurateness in classifying brain tumors.
The Intersection of 5G and IoT: Unlocking the Future of Connectivity
Authors: Nambiar Anila R , K V Shaheena , T Kiran
Published: November 2024

The combination of 5G and the Internet of Things (IoT) will revolutionize industries as well as society due to more efficient connectivity, faster speed, security or scalability up to a billion devices. This paper looks at how 5G can help in furthering IoT towards critical applications like healthcare, manufacturing and smart cities for which ultra-reliable low latency communication (URLLC) services with massive machine type communications (mMTC) are required. We look at how these features can enhance efficiency, automation, and innovation by analysing the technical aspects of 5G-IoT integration through detailed perspective on enhanced mobile broadband(eMBB), ultra-reliable low-latency communication (URLLC) as well as massive machine type communications(mMTC). Our analysis also identifies new issues, including security flaws, data privacy issues, and the high infrastructure costs necessary for widespread 5G deployment, even though 5G greatly expands the potential of IoT by enabling larger device networks and real-time operations. We also talk about the possible socioeconomic effects of this convergence and suggest future lines of inquiry to solve the problems found and make the most of 5G-enabled IoT systems.
Sosyo-ekonomik faktörlerin ekonomik karmaşıklık üzerindeki etkilerinin incelenmesi
Authors: Eteman Volkan , Veysikarani Dilek
Published: November 2024

Bu çalışma, ekonomik karmaşıklık endeksi (ECI) ile çeşitli sosyo-ekonomik değişkenler arasındaki ilişkileri incelemektedir. Ekonomik karmaşıklık, bir ülkenin üretim kapasitesini ve bilgi birikimini yansıtan önemli bir göstergedir. Yüksek ECI değerine sahip ülkeler, genellikle daha çeşitli ve sofistike üretim yapısına, daha yüksek eğitim seviyesine, daha iyi gelir dağılımına ve daha gelişmiş teknoloji kullanımına sahiptir. Çalışmada, ECI ve sosyo-ekonomik değişkenler arasındaki ilişkiler, kanonik korelasyon analizi yöntemi kullanılarak analiz edilmiştir. 2021 yılı verileri kullanılarak yapılan analizde, sosyo-ekonomik değişkenler olarak GSYİH, doğrudan yabancı yatırımlar, siyasal istikrar endeksi, inovasyon endeksi ve ortalama yaşam beklentisi ele alınmıştır. Ekonomik karmaşıklık ise ticaret, teknoloji ve araştırma boyutlarıyla incelenmiştir. Analiz sonuçları, ECI ile sosyo-ekonomik değişkenler arasında güçlü pozitif ilişkiler olduğunu göstermektedir. İnovasyon endeksi, ekonomik karmaşıklık ile en güçlü pozitif korelasyona sahipken, GSYİH ve yaşam beklentisi de ekonomik karmaşıklık ile pozitif korelasyon göstermektedir. Doğrudan yabancı yatırımların ise ekonomik karmaşıklık değişkenleriyle daha zayıf ama yine de pozitif bir ilişkiye sahip olduğu gözlemlenmiştir.
Türk genel sağlık sigortası kapsamında sunulan sağlık hizmetlerinin sosyal koruma tabanları yaklaşımına göre finansman bakımından değerlendirilmesi
Authors: Açık Duygu , Alper Yusuf
Published: November 2024

The Social Protection Floors Recommendation No. 202, adopted on 14 June 2012, was approved by tripartite consensus with the acceptance vote of 452 of the government, employee and employer representatives from 185 countries participating in the 101st Labour Conference of the ILO (Işık, 2012, s. 240; ILO, 2014, s. 1-4). Social Protection Floors established according to the Recommendation were designed by ILO as a three-tier structure. Accordingly, while the first tier includes basic income and health insurance, the second tier consists of premium social security guarantees and the third tier consists of voluntary social security guarantees. The aim of the Recommendation is to provide a roadmap for Member States to build up their social protection floors and to achieve universal social security standards, even at a minimum level. In this way, social protection can be provided to as many individuals as For the abstract text, select possible and social inequalities and extreme poverty can be prevented. In this context, one of the important factors in achieving the main objective expressed in the Recommendation.
Saberes e práticas pedagógicas do professor
Authors: Iolanda Maria Iolanda Demeneck de Figueiredo
Published: November 2024

O artigo é uma reflexão sobre os saberes e práticas pedagógicas do professor, discutindo conceitos basilares. Recorre-se à práxis do professor como uma atividade docente que está inserida no contexto do ensinar, mostrando que ela exige a aplicação de diferentes estratégias em sala de aula. Para revisitá-la, ressaltamos a necessidade da formação continuada, trazendo a sua complexidade, mostrando que essa é uma condição necessária para que os educadores reflitam sobre sua ação e a melhorem. A discussão é balizada em pesquisa bibliográfica que dialoga com estudiosos da área, visando compreender o fenômeno da prática pedagógica e a sua reflexão que dá base à ação do professor
Understanding Student Suicide in India: An Analysis of Root Causes, Consequences, and Preventive Strategies
Authors: Sarkar Dr. Ratan , Mondal Kuheli
Published: November 2024

Background: Student suicide in India constitutes a significant public health concern, with over 10,000 cases reported annually. This alarming trend underscores the substantial pressure exerted on students within the competitive educational environment of the country. Factors contributing to this issue encompass academic stress, parental expectations, societal pressures, and inadequate mental health support.

Objectives: This study aims to investigate the underlying causes of student suicides in India, evaluate their impact on families and communities, and assess the efficacy of current prevention strategies.

Methods: A qualitative review-based approach was employed to synthesize existing literature, reports, and data regarding student suicides in both pre-COVID and post-COVID contexts. This approach facilitates a comprehensive exploration of the issues, transcending a singular temporal perspective. The analysis involved thematic and content analysis techniques to interpret the gathered data effectively.

Results: The primary factors identified as contributing to student suicides include academic pressure, familial expectations, financial burdens, relationship difficulties, and mental health stigma. The repercussions of these issues extend beyond individual students, affecting families and communities, underscoring the necessity for comprehensive support systems. While some prevention initiatives are in place, there are notable deficiencies in their implementation and effectiveness.

Conclusion: To effectively address student suicides in India, a multifaceted approach is essential, involving educational institutions, policymakers, mental health professionals, and community members. Recommendations include mitigating stigma, fostering open communication, integrating mental health services within educational institutions, and utilizing technology to enhance access to care.
Magnitude, Diversity and Prevalence of Antibiotic Resistant Bacteria in Pediatric Patients of Coastal Area at Khulna Region, Bangladesh
Authors: Kumar Saha Bijon , Alom SM Tushar , Ashraf Ayesha , Siddiqua Shaila
Published: November 2024

Antibiotic resistance is one of the biggest public health challenges around the world. A cross-sectional study was conducted to elucidate the magnitude, diversity and antibiotic resistant pattern of coastal pediatric patients. All isolates were characterized by routine bacterial culture, gram staining and biochemical tests. A total of 120 samples from various body fluids of pediatric patients were taken from 3 hospitals in Khulna city. Data were analysed by Excel 2016 and Graphpad Prism (8.0.2). 81 samples (67.5%) showed positive growth, among which 45 (75%) and 36 (60%) were coastal and non-coastal patient’s sample respectively. Out of 9 identified bacteria, 6 were found in both coastal and non-coastal pediatric patients namely, E.coli, Staphylococcus aureus, Klebsiella spp., Streptococcus spp., Salmonella spp., Pseudomonas spp. whereas, Corynebacterium spp. found only in coastal and Acinetobacter spp., & Shigella spp. were found in only non-coastal pediatric patients. Gram negative bacteria were most prevailed both in coastal (66.7%) and non-coastal (72.2%) patients. Moreover, Urinary Tract Infections (UTIs) were more prevalent at early childhood stage (2-5 years of age) in coastal area whereas, infants (28 days-12 months of age) were more prone to pneumonia in non-coastal area. Antibiotic resistance patterns for 10 commonly prescribed antibiotics through Kirby-Bauer disk diffusion method reveals, most of the bacterial strains showed multidrug resistant (≥ 80%) against 7 and/or more classes of antibiotics. Therefore, it is necessary to reduce the abundant use of antibiotics. Institutional antimicrobial resistance surveillance efforts and use of biogenic nanomaterials and microalgae-based technologies could decrease the occurrence.
UNDERSTANDINGS AND EXPRESSIONS ABOUT THE QUOTA SYSTEM AS AFFIRMATIVE POLICY ACTION BY HIGH SCHOOL STUDENTS
Authors: Francisca Lamarão Isabel , Couto Monteiro Stéfano , Regina Zasso Carla
Published: November 2024

This article deals with the understanding of high school students about the right to racial and social quotas as a public policy that allows the rise of socially disadvantaged populations to higher education. It is the result of research carried out with students from 3rd year high school classes at Colégio Estadual Professora Terezinha Scaramussa (CEPTS), located in the city of Santa Cruz Cabrália, state of Bahia. Data were obtained through the application of a didactic sequence involving exposition, a questionnaire with mixed questions – open and multiple choice, associated with an individual textual production. Based on the data analysis, the perspectives of content analysis were considered and, in a preliminary manner, it is possible to understand that it is necessary to promote differentiated and continuous strategies so that students are clear about the importance of appropriating public policies in their daily lives and, in this case more specifically, about racial and social quotas, as well as realizing that the observance of discursive practices about racial and social quotas in the subjects that make up the curriculum is not yet common in schools.
POLITICAL SCIENCE FOR THEORY AND ACTION
Authors: Pinho de Abreu Reginaldo
Published: November 2024

Given the undeniable contribution of Political Science to history, it is also necessary to understand the context in which its postulates were developed, as well as its most prominent figures. By exploring the main works and authors in the field, we can deepen our understanding of its content. From this perspective, this study aims to discuss the life and work of one of the most important international references in Political Science, the Italian scholar Gian Franco Pasquino, and the significant contributions he has made and continues to make to the field, with a focus on action-oriented approaches.