bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigating Türkiye’s financial nexus: A wavelet coherence analysis of sovereign CDS spreads, bond yields, stock index, and FX rates
Authors: Tüysüz Şükriye , Gül Mert
Published: January 2025

This article investigates the intricate relationships between sovereign credit default swaps (CDS) and various Turkish financial assets, including the US Dollar to Turkish Lira exchange rate (USDTRY), the Borsa Istanbul 100 (XU100) stock index, and government bond yields. Employing a rigorous wavelet coherence analysis that captures the timefrequency domain, this study utilizes daily data from November 2008 to July 2022 period containing important financial, economic and global health crises, such as Great Recession, European Debt Crises, and COVID-19 pandemic. The wavelet coherence results uncover that the causality between variables is contingent on both the frequency domain and evolves dynamically over time, with the most significant interdependencies manifesting in the medium term. Moreover, the analysis reveals that government bond yields, and their respective volatilities positively impact CDS spread and its volatility. Similarly, the USDTRY rate leads to positive changes in the CDS spread. By contrast, the volatility of CDS spreads positively influences foreign exchange volatility and the XU100 index volatility. The CDS spread negatively affects the XU100 index. Overall, the findings elucidate the direction of causality between Turkish CDS spread and retained Turkish financial assets and then provide valuable information on the predictive power of those securities for investors, financial risk managers, and policymakers.
Convergence of AI, blockchain and pharmacoeconomics in building adaptive pharmaceutical supply chains: A novel paradigm shift for equitable global drug access
Authors: Adeleke Damilola Adekola  , Rinji Goshit Kassem  , Akachukwu Obianuju Mbata
Published: January 2025

The convergence of Artificial Intelligence (AI), blockchain technology, and pharmacoeconomics presents a transformative opportunity to revolutionize pharmaceutical supply chains, fostering equitable global drug access. Traditional supply chains are often plagued by inefficiencies, including limited transparency, suboptimal resource allocation, and susceptibility to counterfeit drugs, which exacerbate disparities in drug availability. This paper explores a novel paradigm where AI-driven analytics, blockchain's immutable ledgers, and pharmacoeconomic principles synergize to create adaptive pharmaceutical supply chains tailored to global needs. AI facilitates predictive analytics for demand forecasting, inventory optimization, and real-time decision-making, reducing wastage and ensuring timely drug delivery. Blockchain enhances transparency and traceability across the supply chain, ensuring the authenticity of pharmaceutical products and fostering stakeholder trust. Concurrently, pharmacoeconomics evaluates the cost-effectiveness of supply chain strategies, balancing affordability with accessibility. This interdisciplinary framework enables equitable distribution of essential medications, particularly in underserved regions, by addressing systemic challenges such as logistical inefficiencies, pricing disparities, and regulatory compliance. The proposed approach leverages AI to identify demand patterns and optimize supply routes, while blockchain ensures secure, verifiable records of drug production, distribution, and delivery. Integrating pharmacoeconomic assessments informs pricing models and reimbursement strategies that align with socio-economic realities, thus promoting affordability without compromising sustainability. Case studies from pilot implementations highlight the potential for reduced operational costs, enhanced drug traceability, and improved access to life-saving medications. By combining the strengths of AI, blockchain, and pharmacoeconomics, this framework offers a scalable, resilient, and adaptive model for pharmaceutical supply chains, addressing global health inequities. It underscores the importance of collaboration among stakeholders, including governments, healthcare providers, and technology innovators, in advancing healthcare outcomes. Future research should explore the ethical implications, technological scalability, and policy frameworks necessary to ensure the widespread adoption of this integrated paradigm.
PEMERTAHANAN BAHASA HELONG MELALUI PENERJEMAHAN CERITA RAKYAT BERBASIS IDEOLOGI PEMERASINGAN
Authors: Niron Yakobus M Langkelang , Kami Patrisius , Usfal Nofriana
Published: January 2025

Bahasa Helong saat ini mengalami degradasi dan bahkan terancam menuju kepunahan. Berkurangnya penutur, adanya alternatif pilihan bahasa lain, dan meningkatnya bidang pariwisata menjadi penyebab permasalahan ketahanan bahasa terhadap bahasa Helong. Penelitian ini bertujuan memunculkan kosakata unsur budaya dalam penerjemahan yang dapat menjadi salah satu solusi dalam upaya pemertahanan bahasa Helong melalui cerita rakyat. Proses penerjemahan menggunakan Strategi SL-Emphasis (Model Diagram-V Nemark) dan prosedur penerjemahan konten budaya Newmark sebagai bentuk penerjemahan berbasis ideologi pemerasingan. Pendekatan kualitatif dengan Metode analisis isi (content analysis) digunakan untuk menggali berbagai informasi secara mendalam terkait tuturan cerita rakyat, pemaknaan kosakata budaya, dan penerjemahan bahasa Helong melalui tokoh adat dan berbagai literatur budaya sebagai input pendukung penelitian. Hasil Penelitian ini mengarah pada ideologi pemerasingan dalam penerjemahan dari lima cerita rakyat masyarakat Helong yang mengandung unsur budaya ekologi, budaya material, budaya sosial, organisasi sosial, kial dan kebiasaan yang memunculkan 74 kosakata unsur budaya bahasa sumber (Bahasa Helong) dalam 92 kalimat  bahasa sasaran (Bahasa Indonesia).
PENINGKATAN MOTIVASI BELAJAR DAN KERJASAMA DALAM KELOMPOK MENGGUNAKAN MEDIA WORDWALL
Authors: Lamanepa Agustina S.P , Nai Firmina Angela , Pono Chatrina
Published: January 2025

Fokus penelitian ini adalah “Peningkatan motivasi belajar dan kerjasama dalam kelompok menggunakan media wordwall”. Tujuan dari penelitian ini adalah untuk mengetahui dan mendeskripsikan bagaimana meningkatkan motivasi belajar dan kerjasama dalam kelompok dengan menggunakan media wordwall. Penelitian ini dilaksanakan di kelas XI-7 SMA Negeri 2 Kupang sebanyak 3 siklus. Pada observasi awal, peneliti menggunakan media teks berupa Lembar Kerja Peserta Didik yang dikerjakan oleh peserta didik dengan jumlah anggota kelompok 5-6 orang, namun selama diskusi peserta didik kurang aktif dalam kelompok. Dari permasalahan ini, peneliti menerapkan media wordwall dalam pembelajaran. Wordwall adalah salah satu media pembelajaran interaktif yang dapat digunakan guru. Pada Siklus 1 peneliti menggunakan wordwall roda acak, peserta didik dibentuk dalam kelompok dengan jumlah anggota 4 orang. Bersama kelompok mereka akan memutar roda acak tersebut sampai roda berhenti dan akan muncul pertanyaan yang akan dijawab secara langsung. Lalu pada siklus 2 wordwall yang digunakan adalah membuka kotak, dimana peserta didik bersama kelompoknya mengerjakan kuis yang disediakan sebanyak 10 nomor dan hasil yang terlihat peserta didik sudah mulai aktif bahkan sudah mulai saling berkolaborasi dalam menentukan jawaban yang benar. Kemudian pada siklus 3 yaitu wordwall mencari kata, peserta didik sudah sangat aktif bahkan sudah membagi tugas kepada masing-masing anggota kelompok untuk menemukan kata yang dicari. Penggunaan media wordwall dalam pembelajaran ini mendapatkan hasil belajar yang baik dan memuaskan. Hal ini dilihat langsung refleksi pengalaman belajar dan dapat dibuktikan dengan hasil presentasi peserta didik yang tuntas dengan presentase 75%, dan peserta didik yang tidak tuntas sebesar 25%.
Manajemen Peserta Didik Sekolah Dasar: Konsep, Implementasi, dan Strategi Optimalisasi
Authors: Nalle Anselmus , Unggin Elisabet Angela , Wadu Juanita Aristia , Molum Januario Jacsem , Rizmawan Yosef Cendy , Dua Lehan Andriyani A. , Dethan Jimylton
Published: January 2025

Manajemen peserta didik memainkan peran penting dalam membangun lingkungan belajar yang efektif di sekolah dasar. Artikel ini bertujuan untuk membahas konsep, penerapan, dan strategi optimalisasi manajemen peserta didik di tingkat sekolah dasar. Dengan menggunakan pendekatan deskriptif kualitatif, artikel ini membahas terkait  proses pengelolaan yang meliputi perencanaan, pelaksanaan, dan evaluasi dari manajemen peserta didik termasuk tantangan yang dihadapi. Kesimpulan dari artikel ini menekankan pentingnya kerja sama antara sekolah, orang tua, dan masyarakat untuk mencapai tujuan pendidikan yang menyeluruh dan holistik.
Meningkatkan Keaktifan Belajar Siswa Kelas XI-5 SMAN 2 Kupang Melalui Media Wordwall
Authors: Adu Aron Fresli , Nai Firmina Angela , Pono Chatrina
Published: January 2025

Masalah dalam penelitian ini adalah kurangnya keaktifan siswa dalam belajar. Penilitian ini bertujuan melihat apakah Wordwall dapat meningkatkan keaktifan belajar siswa. Studi ini dilaksanakan 3 siklus dengan meningkatkan berbagai upaya meningkatkan keaktifan pembelajaran. Subjek yang diteliti berjumlah 30 siswa kelas XI-5 di SMA Negeri 2 Kupang. Observasi, lembar aktivitas, dan dokumentasi adalah sumber data penelitian. Hasil menunjukkan bahwa delapan indikator siklus 1 sampai dengan 3 menunjukkan peningkatan keaktifan belajar peserta didik, pada siklus satu jumlah rata 14, 3 dengan presentase 42 persen, siklus dua jumlah rata-rata 16, 8 dengan presentase 52, 5 persen dan pada siklus 3 jumlah rata-rata 18, 5 dengan presentase 57,9 persen. Wordwall telah terbukti berhasil sebagai media untuk meningkatkan partisipasi siswa, keaktifan siswa dalam belajar, dan minat mereka dalam pelajaran. Ini juga memungkinkan Anda membuat lingkungan pembelajaran yang lebih interaktif dan menarik.
PENGGUNAAN MEDIA POP UP DAN VIDEO LAWAKAN DALAM MENINGKATKAN KETERAMPILAN BERBICARA SISWA KELAS X SMAN 3 KUPANG
Authors: Napa Maol Priska Kusuma Wardani , Djawa Alex , Ga Adrinika H.
Published: January 2025

Keberhasilan dalam menyampaikan esensi materi pembelajaran dipengaruhi dari media pembelajaran. Dalam pembelajaran Bahasa, media yang menarik cenderung meningkatkan keterampilan berbahasa. Video lawakan dapat meningkatkan kemampuan berpikir kritis siswa dalam memetik pesan dan kritik dari lawakan serta teks lawakan yang dikemas dalam pop up membantu siswa berimprovisasi dalam menampilkan lawakan. Tujuan dari penelitian ini adalah menggunakan media untuk meningkatkan keterampilan berbicara peserta didik pada materi menampilkan lawakan Tunggal berbantuan media pop up dan video lawakan. Penelitian ini merupakan Penelitian Tindakan Kelas (PTK). Data penelitian disajikan secara deskriptif. Subjek penelitian merupakan para siswa kelas X B SMAN 3 Kupang berjumlah 36 siswa. Data yang disajikan dalam penelitian ini berupa 1) hasil tes performansi guru dan siswa, dan hasil tes berbicara peserta didik. Pada siklus I ketuntasan klasikal hanya memperoleh 69,44% lalu meningkat pada siklus II menjadi 100%. Dilihat dari data hasil observasi guru dan siswa pada siklus I adalah 42,10% dan 45,05% lalu meningkat pada siklus II menjadi 80,26% dan 84,21%.  Berdasarkan pencapaian tersebut, dapat disimpulkan bahwa penggunaan media pop up dan video pembelajaran dapat meningkatkan keterampilan berbicara dalam materi teks lawakan tunggal pada siswa kelas X B SMAN 3 Kupang telah berhasil diterapkan.
Crónica
Authors: Lagarrigue Luis
Published: January 2025

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Sociedad Chilena de Filosofía.
Authors: Facultad de Filosofía y Humanidades Universidad de Chile
Published: January 2025

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WŁAŚCIWOŚCI KATALITYCZNE I BIOMEDYCZNE ZWIĄZKÓW ZAWIERAJĄCYCH JONY RUTENU(II) ORAZ RUTENU(III)
Authors: Pobłocki Kacper , Pawlak Marta , Walczak Juliusz , Drzeżdżon Joanna , Jacewicz Dagmara
Published: January 2025

Ruthenium complexes appear in scientific publications mainly as catalysts in the olefins metathesis process. In this review, we want to indicate the research niche regarding the use of ruthenium(II) and ruthenium(III) complexes in other catalytic processes, i.e. polymerization or epoxidation of olefins and depolymerization. We would like to combine the catalytic properties of ruthenium(II,III) complex compounds with their biomedical activity due to the growing problem of drug resistance (including antibiotic resistance). Scientists have been designing new metallopharmaceuticals exhibiting biological activity for several years, therefore this requires a critical review of the literature. The main goal of designing new metallodrugs is to create compounds with new or stronger biological properties compared to free ligands. Ruthenium compounds are considered potential substitutes for known drugs. In particular, Ru(II) and Ru(III) based complexes have reduced toxicity and can be tolerated in vivo. In addition, a wide spectrum of ruthenium oxidation states, a different mechanism of action and the kinetics of ligand substitution increase the advantage over coordination complex compounds based on platinum. In conclusion, in this review, we will focus on the latest reports from the literature on the catalytic properties and biomedical activity of ruthenium(II) and ruthenium(III) chemical compounds
FURANOKUMARYNY – NATURALNE ZWIĄZKI ORGANICZNE O WIELU WŁAŚCIWOŚCIACH
Authors: Piechocka Justyna , Owczarek Paulina , Chwatko Grażyna
Published: January 2025

Psoralen and angelicin are organic, natural chemical compounds, belonging to the furanocoumarin group, which are quite common in nature. Among others, these compounds are present in plants of the celery, rutaceae, mulberry and bean families, such as celery, carrot, lemon and fig. Interestingly, they exhibit a variety of biological activities, for instance insecticidal, anticonvulsant, anticancer, and antioxidant properties. For this reason, they are commonly used in different area of life. For example, psoralen is used in photochemotherapy as a photosensitizer in the treatment of psoriasis or acquired vitiligo (PUVA therapy). However, there is evidence that overexposure to psoralen and angelicin can also cause adverse effects. For these reasons, a number of analytical methods have been developed for their determination in environmental samples, while the vast majority of them are based on separation techniques. This paper discusses issues related to psoralen and angelicin and their analytics
NOWE STRATEGIE W WYSOKOCIŚNIENIOWEJ MANOMETRII LUMINESCENCYJNEJ
Authors: Runowski Marcin
Published: January 2025

Optical pressure sensors, namely luminescent manometers, offer new possibilities for studying and monitoring changes in the physicochemical properties of materials under extreme conditions in a remote and non-invasive manner. This can be achieved through the monitoring and analysis of selected spectroscopic parameters, such as band intensity ratios, emission line shifts, or luminescent lifetimes. However, a limitation for optical readings usually arises from the quenching of the luminescent signal in the given material, i.e., in the active part of the sensor under elevated pressure conditions. In this article, new strategies for the development of advanced and ultra- sensitive luminescent pressure sensors, mainly based on inorganic materials doped with lanthanide or d-block metal ions, will be presented and analyzed. Factors influencing the enhancement of luminescent signal intensity and sensor sensitivity will be discussed. These objectives can be achieved through the appropriate selection of the soft host matrices (of high compressibility), doping with various lanthanide and d-block metal ions, using interionic energy transfer, pressure-driven configurational crossover, as well as the use of materials exhibiting both photo- and mechanoluminescence phenomena. Finally, the development of bi-functional pressure and temperature sensors operating under extreme conditions will also be discussed.
WŁAŚCIWOŚCI KATALITYCZNE ZWIĄZKÓW KOORDYNACYJNYCH JONÓW WANADU W PROCESIE POLIMERYZACJI OLEFIN
Authors: Pobłocki Kacper , Pawlak Marta , Drzeżdżon Joanna , Jacewicz Dagmara
Published: January 2025

Recently, there has been an increased interest in designing new catalytic systems for olefin polymerization reactions. Scientists' research focuses on the design of cheap, green precatalysts based on transition metal ions, i.e. vanadium(III), and vanadium(IV). This review summarizes recent reports on the catalytic properties of vanadium coordination compounds in olefin polymerization reactions. Additionally, the latest publications on using heterogeneous metal-organic frameworks (MOFs) based on vanadium in the coordination polymerization of olefins will be presented
WYBRANE KIERUNKI W ZAKRESIE MODYFIKACJI POLIOLEFIN
Authors: Białek Marzena , Bosowska Kornelia , Groch Paweł , Ochędzan-Siodłak Wioletta , Czaja Krystyna
Published: January 2025

Polyolefins, which include various types of polyethylene and polypropylene and, to a much lesser extent, higher polyolefins and olefin copolymers, have been the dominant group of polymers for years. This is due to both the significant development of their production technology, which has become environmentally friendly over the years, and their diverse physicochemical properties. Additionally, the properties of polyolefins, and therefore their areas of application, can be significantly extended by copolymerizaton of olefins with other vinyl compounds, changing their topology and microstructure as well as by modifying their surface or making composite materials. This review reports the state of the art in the field of copolymerization of olefins with alkenylsilsesquioxanes, polar monomers and cycloolefins, which give the resulting materials favorable characteristics in terms of thermal resistance, adhesion and others properties. The next subjects of consideration were the synthesis of multiblock olefin copolymers by chain shuttling polymerization and the synthesis of telechelic polyolefins using, among others, anionic and coordination polymerization. Finally, the modification of polyolefins towards obtaining antibacterial materials and their use in the field of medicine and the packaging industry were discussed
Analisis Faktor Penyebab Kesulitan Belajar Matematika Siswa Sekolah Dasar
Authors: Mahardiyanti Taurinda
Published: January 2025

Students continue to face learning difficulties during the process of learning mathematics. Disturbances in one or more basic psychological functions, such as understanding and using spoken or written language, are known as learning disabilities. The purpose of this study was to identify the elements that contribute to children's challenges in learning mathematics and to outline strategies to overcome these problems for students in grade II of Elementary School. Data for this qualitative descriptive study were collected through documentation, unstructured interviews, and observations. Triangulation and increased persistence were the data validity strategies used. On the other hand, data analysis involved collecting, reducing, presenting, and drawing conclusions from data. Students' poor attitudes towards learning mathematics, lack of interest in learning, low motivation to learn, and less than ideal physical health are internal influencing factors that come from within the students. External influences include the use of less than ideal learning materials, less diverse teaching strategies, classrooms that are still full of trash, lack of infrastructure and equipment, especially teaching aids, and the home environment. Low motivation and interest of students, as well as family and environmental conditions, are the root causes of learning challenges. Organizing additional and remedial lesson programs, motivating children verbally, and giving them rewards are the best efforts that can be made.
Efficient Resource Allocation in Cloud Environment: A Hybrid Circle Chaotic Genetic Osprey Solution
Authors: K T Rajgopal , T Gadiyar H Manoj , H Nagesh Shenoy , R H Goudar
Published: January 2025

Organizations and individuals now access and use computing resources in a completely new way due to cloud computing. However, efficient resource allocation remains a significant challenge in cloud environments. Existing techniques, such as static, dynamic, heuristic, and meta-heuristic, often lead to locally optimal solutions, suffering from slow convergence rates that hinder the achievement of global optimality. To address this challenge, this paper presents a novel Hybrid Circle Chaotic Genetic Osprey Optimization Algorithm (HC2GOO). This innovative approach synergizes the strengths of the Osprey Optimization Algorithm (O2A) and Genetic Algorithm (GA) to significantly enhance resource allocation efficiency in cloud environments. The HC2GOO incorporates a circle chaotic map to replace the random initialization values in the Osprey population update phase. Furthermore, the integration of the GA effectively balances the exploration and exploitation processes of the osprey optimization, facilitating the discovery of optimal solutions. The effectiveness of the HC2GOO algorithm is assessed using the GWA-T-12 Bitbrains dataset and is benchmarked against established algorithms. The results indicate that HC2GOO outperforms existing methods, achieving significant improvements in key performance indicators: energy consumption (36 kWh), host utilization (13,800), SLA violations (7.2), average execution time (16.2 ms), service cost ($12.5), number of migrations (3,050), and throughput (28.6%) based on 100VMs. Overall, the HC2GOO algorithm represents a substantial advancement in the field of cloud resource allocation, offering more effective solutions for optimizing computing resource management.
Enhancing Data Protection and Covert Communication in Cloud Environments with Isogeny Based Cryptography and Spread Spectrum Steganography
Authors: D Shivaramakrishna , M Nagaratna
Published: January 2025

The rise of cloud computing has changed how individuals and organizations store and communicate data, but it additionally caused significant concerns about information security and confidentiality. In order to improve data protection and allow covert communication in cloud environments, this research suggests a unique approach that combines spread spectrum steganography with isogeny-based cryptography as a solution to these problems. The main goal is to make it less difficult for two users, User 1 and User 2, to communicate private data that is kept in a cloud infrastructure through safe and covert data transfer. This technology depends on isogeny-based cryptography, which creates safe channels of communication between users by taking use of the mathematical features of isogenies of elliptic curves. Additionally, this technique provides protection from quantum assaults, consequently boosting data security. Spread Spectrum Steganography (SSIS), the second element, is used to secretly include shared secrets inside digital images. To protect secrets, SSIS encrypts, duplicates, interleaves, and employs pseudorandom noise sequences as carriers. The noise in the stegoimage is then removed with a filter to approximate the original image. By performing this, the stegoimage is made integrate in with the original, thereby hiding the secrets. Users 1 and 2 can safely share information by combining spread spectrum steganography and isogeny-based cryptography, reducing potential risks associated with parties that are unreliable. Spread spectrum steganography provides the covert hiding of transmitted secrets inside digital images, while isogeny-based cryptography provides secure communication channels. These methods are combined to build an effective structure for private and secure data sharing in cloud settings. This novel method solves important concerns about data security, secrecy, and covert communication, and thus makes a significant addition to the developing field of cloud computing security.
Data-Driven Innovations: Transforming Healthcare through Machine Learning Integration
Authors: Kandimalla Purna Chandra Rao , T Anuradha
Published: January 2025

Today's healthcare sector generates an unprecedented amount of data, creating a promising junction between data mining and machine learning. This research aims to achieve two key healthcare goals. First, it effortlessly integrates AI into clinical decision-support systems to improve treatment regimens. The emphasis is on individualizing medicines, increasing effectiveness, and minimizing side effects. This main goal is to optimize treatment methods using AI. The research also examines how data mining and machine learning may improve hospital operations. This objective involves improving logistical administration, planning, and resource allocation to boost operational efficiency, lower healthcare costs, and enhance access to high-quality care. The study rigorously investigates how data-driven approaches may revolutionize healthcare system operations. This study examines the synergy between data-driven methods and medicine, focusing on current trends and advances. The research examines medical applications that demonstrate machine learning's ability to change healthcare delivery. The study aims to illuminate data-driven approaches' promising potential to advance patient-centeredness, financial sustainability, and operational efficiency in healthcare.
Integrating Homomorphic Encryption with Blockchain Technology for Machine Learning Applications
Authors: Paul Subhra Prosun , S V N Sreenivasu , Md Shafikul Islam , B Raghunath , Dhote Kanchan , D Vetrithangam
Published: January 2025

Leveraging cutting-edge technology like blockchain and machine intelligence, smart healthcare systems have emerged as a potential strategy for enhancing healthcare services. In order to secure health data, this study offers a unique design and analysis of a smart healthcare system that applies blockchain technique and the paillier homomorphic encryption algorithm in addition to a machine learning algorithm to detect cardiological disease. The suggested method seeks to solve the problems with predictive analytics and safe health data exchange in the medical field. Sensitive information is encrypted during transmission and storage using the Paillier Homomorphic Encryption technique, guaranteeing its confidentiality. By providing traceability and accountability in data access and sharing, blockchain technology is used to construct a safe and transparent record of health transactions. In addition, a machine learning algorithm is used to forecast cardiac illness based on the encrypted data, giving medical practitioners insightful information to help them make judgments. The integration of these technologies and their advantages in improving healthcare services are highlighted in the discussion of the proposed scheme's constructional and operational specification section. Simulation experiments are used to assess the suggested method’s efficiency and reflect its efficacy in terms of data security, detection accurateness, and computing proficiency. Comparing the integrated approach to conventional approaches, the results demonstrate a considerable improvement in prediction accuracy and security of health data. To sum up, the suggested smart healthcare system provides a thorough approach to guaranteeing the security of patient data and enhancing predictive analytics in the medical field. Machine learning, blockchain technology, and Paillier homomorphic encryption are all integrated into it, which shows promise for improving healthcare services and developing the field of smart healthcare systems.
A Lightweight and Federated Machine Learning Based Intrusion Detection System for Multi Attack Detection in IoT Networks
Authors: Mani Prathap , D Arthi , K Periyakaruppan , S Surenderkumar
Published: January 2025

The quick growth of Internet of Things (IoT) devices has increased the amount of cybersecurity threats, requiring the creation of increasingly complex intrusion detection systems (IDS). The available IDS concentrate on specific threats, rely on restricted datasets, or fail to take into account the resource-constrained of IoT networks. A unique IDS that is lightweight, scalable, and real-time is suggested to detect many types of attacks, including distributed denial of service (DDoS), botnet, and denial of service (DoS) attacks. The suggested approach, which combines hybrid feature selection methods, is used to optimize feature sets. These techniques include Genetic Algorithm (GA), Mutual Information, and Principal Component Analysis (PCA). In addition, federated learning is used for anomaly detection that is responsible for individuals' privacy. Lightweight supervised machine learning models are constructed and assessed using multiple datasets, including IoTID20 and other publicly available benchmarks. The scalability, low latency, and energy efficiency of the proposed system are evaluated by real-time testing in an environment that simulates the Internet of Things for testing purposes. From the simulation results, the proposed approach does a better job than conventional IDS in terms of detection accuracy, computing efficiency, and flexibility to a wide variety of IoT scenarios.
Beyond The Gradebook: Machine Learning and LMS Data for True Student Performance
Authors: Ganesh Varsha , S Umarani
Published: January 2025

Analyzing student’s behavior for performance prediction involves examining various data points and indicators to predict academic outcomes. This research uses the learner’s activity tracker tool collected dataset, which contains three different sets of features including demographic, academic background, and behavior features. This approach combines these data to predict students’ performance based on behavior, providing insights that can help in creating personalized learning experiences. A hybrid ML model is developed to improve the student’s performance prediction. The hybrid ML model combines the ensemble feature selector with Optimized with support vector machine (SVM) classifier. The Linear Neural network (NN) model is used to form a three-layered feature extraction (FE) model. This approach uses ensemble feature selector to select the influential features from the Linear NN extracted features map. Finally, an optimized SVM classifier is developed to predict the students’ performance. The optimized SVM model uses the GridSearchCV method to optimize the regularization parameter (‘C’-value) and kernel options of the SVM model to improve the prediction performance. The performance evaluation analysis shows that the LNN-Ensemble-Optimized SVM based students’ performance prediction approach achieves higher accuracy (98.12%), precision (98.51%), recall (99.23%), f-score (98.1%) rate than comparison approaches on LMS data.
An Ensemble Cognitive Model for Stroke Prediction Using Unstructured Health Information Powered by Machine Learning
Authors: Ghanimi Hayder M A , K Akilandeswari , A Hanumat Prasad , Sengan Sudhakar , Prakash Badde Praveen , Bommisetti Ravi Kumar
Published: January 2025

Machine Learning (ML) algorithms have procured a profound position in healthcare sectors, especially in diagnosis, treatments, and recommendation systems. The ML is evolving as an aiding tool for medical practitioners in disease diagnosis. Also, the feature selection reveals the latent relationships among the features, which emerge significant scope for clinical research. In the proposed study, a cognitive ensemble model (CEM) was developed to predict the probability of stroke among various subjects using highly raw clinical data. The optimal base learners are made in such a way that each of them complements one another. The proposed CEM is tested on a real-world dataset on important classification metrics. The results indicate that the CEM deployed in the healthcare sector forewarns patients regarding the probability of stroke.
Optimising The User Experience in E-Commerce Platforms Using Ergonomic Interface Design and Motion Analysis
Authors: Dadhabai Sundari , Ayasrah Firas Tayseer , Chaitanya Kancharla K , D Arivazhagan , P Jagadeesan , K Rahmaan
Published: January 2025

This study investigates how Motion Analysis (MA) and Ergonomic Interface Design (EID) can enhance the User Experience (UX) in e-commerce (E-comm) platforms. MA, including Eye-Tracking (ET) and Gesture Recognition (GR), was used to examine User Interfaces (UI) patterns, while EID principles were applied to optimize UI elements such as button size, layout spacing, and navigation. A total of 45 participants, considered by device preference and shopping habits, were observed across PC, mobile, and tablet platforms. Key findings indicate that mobile users engage in more frequent hand and wrist movements and UX higher discomfort levels due to smaller screens and touch-based UI, while PC users reported the highest comfort levels. Scroll depth analysis revealed that mobile users scrolled the deepest, especially during product discovery, while PC users engaged less with deeper content. GA showed heavy UI with more complex gestures, such as pinch-to-zoom and drag-and-drop, while light users relied on more straightforward gestures like tapping and scrolling. EID improvements significantly reduced movement frequency and increased comfort, particularly for mobile and tablet users. The study concludes that optimizing E-comm platforms through MA and EID leads to enhanced usability, reduced physical strain, and greater user satisfaction across devices.
Using AI And Machine Learning to Realize Information System Engineering of Smart Cities: Accurate Weather Forecasting and Emergency Response
Authors: Ye Jiahao , Masseran Nurulkamal Bin
Published: January 2025

This paper discusses the contribution of AI and ML in the information systems of a smart city, particularly being concerned with enhancing the precision of weather forecasts and the effectiveness of emergency responses. Satellite imagery forms part of the complex data sets incorporated in the study, along with historical data regarding emergencies. The datasets were analyzed with the help of AI and ML models, such as LSTM and CNNs. Results show that the AI-based systems performed better than the traditional method, as it accounted for 92% of accuracy in short-range weather forecasting, while the legacy model only accounted for 78%. During extreme events such as heat waves and wildfires, AI models produced more timely and accurate warnings, cutting the response time for emergencies by as much as 25%. The paper also touches on broader implications of AI in relation to its potential and contribution toward the betterment of enhanced urban resilience, sustainability, and public safety. Although there are considerable merits with AI, the issues of data privacy and ethical concerns along with computational overheads pose challenges and drawbacks. Such a research effort is hoped to conclude in hybrid AI models and advanced IoT sensor networks as possibleF futures toward optimizing the smarts for smart city applications.
A proposed cooperative approach for edge detection based multi-agent system (MAS) using heterogeneous RGB images
Authors: Kholladi Nedjoua Houda , Bechkoum Kamal , Hamoud Meriem
Published: January 2025

Image segmentation has become a growing research area in image processing, computer vision and pattern recognition. Despite decades of progress and significant accomplishments, challenges remain in feature extraction and model design for image segmentation which make it as complex system required to be solved by intelligent system. This manuscript systematically proposes a cooperative approach for images edge detection based on Multi-Agent System, the proposed approach advance addresses ongoing obstacles of existing image processing methods. Regarding to the image segmentation methods issues is extracting features and providing accurate segmented images. Often edges and regions belonging to the input image are confusing and intricate to extract, due to the proximity of the brightness levels of the images. Many technologies and approaches have been proposed for the identification, classifications, detection and segmentation of images. However, the optimal solution remains a challenging task in computer vision. Our proposed Multi-Agent System(MAS) framework adopts a bottom-up approach to enhance the Quadtree Algorithm while also leveraging a bottom-up strategy through a fusion process facilitated by dynamic aggregation process. This cooperative protocol among region and edge agents enables the framework to achieve more accurate and precise segmentation compared to state-of-the-art methods, even when applied to heterogeneous images from diverse benchmarks. Our approach out performs the compared state of the art techniques with PSNR of 19.2107 dB, MSE of 0.0059, and SSIM of 0.9602.
Pengaruh Kualitas Pelayanan dan Inovasi Layanan terhadap Kepuasan Pelanggan PT PLN
Authors: Feriansyah Manik  , Enda Surbakti  , Mardhiatul Husna  , Indra Siregar  , Jamardua Haro
Published: January 2025

Currently, competition is increasingly fierce, especially in service-oriented companies, which are becoming more competitive with numerous firms offering services to the public with varying characteristics. Companies that aim to survive and grow must provide the best quality of service to achieve customer satisfaction. This is in line with service quality theory, which states that a company deemed to be of high quality meets consumer expectations and even exceeds them.This study aims to analyze the influence of service quality and service innovation on customer satisfaction at PT. PLN (Persero) in Kabupaten Pakpak Bharat, specifically in the village of Penaggalen Binanga Boang. The research adopts a quantitative approach, utilizing a saturated sampling method with 98 respondents who are customers of PT PLN (Persero) in Kabupaten Pakpak Bharat, residing in the village of Penaggalen Binanga Boang. Data were collected through online questionnaires and analyzed using SPSS with multiple linear regression analysis.The results indicate that service quality partially and significantly influences customer satisfaction at PT PLN (Persero) in Kabupaten Pakpak Bharat (case study in the village of Penaggalen Binanga Boang). Similarly, service innovation also partially and significantly affects customer satisfaction at PT PLN (Persero) in Kabupaten Pakpak Bharat (case study in the village of Penaggalen Binanga Boang). Both service quality and service innovation together have a positive and significant influence on customer satisfaction, with an F-value of 35.261 exceeding the critical F-value of 3.092. The significance value of 0.000 is less than the significance level of 0.05 (0.000 < 0.05), leading to the rejection of the null hypothesis (H0) and acceptance of the alternative hypothesis (H1).
Pengaruh Disiplin Kerja dan Lingkungan Kerja Terhadap Kinerja Karyawan pada Kantor Pendidikan Diklat Damkar Provinsi DKI Jakarta
Authors: Ayu Ritma Ratri  , Ratnawati Marginingsih
Published: January 2025

The DKI Jakarta Provincial Fire and Rescue Training Education Office is a government building that serves the community in the field of fire prevention and control. One thing that is done is through discipline and the work environment for employees. This research aims to determine the influence of Work Discipline and Work Environment on Employee Performance at DKI Jakarta Province Fire and Rescue Education and Training Office companies. The research method used is a quantitative method approach with data collection techniques using a total sample or non-probability sampling where the entire population is sampled. The population in question is all employees of the civil service division of the DKI Jakarta Province Fire and Rescue Training Education office, totaling 40 respondents. This research instrument uses a questionnaire to collect data in Likert scale units. In managing data for analysis using the SPSS 20 application with multiple linear regression analysis techniques, the results of multiple linear regression analysis show that Y = 0.894, calculated 8.136 for the variable (X1), and 2.230 for the variable (X2), simultaneously the two independent variables obtained obtained an F count of 53.928. Based on the coefficient of determination test, it was found that the two independent variables had a 74.5% influence on employee performance.
Analisis Prosedur Temu Kembali Arsip Inaktif pada Divisi Corporate Secretary PT Taspen (Persero)
Authors: Elisabeth Setyani Krismawarti  , Christian Wiradendi Wolor  , Marsofiyati Marsofiyati
Published: January 2025

The management of inactive archives is crucial for companies, including PT Dana Tabungan dan Asuransi Pegawai Negeri (TASPEN), which has a large volume of documents. This study aims to understand the procedures for retrieving inactive archives in the Corporate Secretary Division, along with the tools and information systems used. The research employs a descriptive qualitative method through observation, interviews, and documentation. Findings indicate that inactive archives are stored in the Secretariat Department Room for 5 to 10 years. The retrieval procedure involves filling out a request form verified by staff, with search times ranging from 2 to 10 minutes. Challenges include human errors during data input and borrowers forgetting to return archives on time. To address these issues, TASPEN conducts regular training for employees and checks the list of transferred archives. Additionally, TASPEN is innovating by developing an E-Archive system to minimize errors and enhance integrated archive management.
Faktor-Faktor yang Mempengaruhi Sektor Pariwisata dalam Meningkatkan PDRB di Kota Langsa
Authors: Muhammad Furqan  , Sefi Ratiwi  , Fatima Baen  , Puti Andiny
Published: January 2025

This study aims to analyze the factors influencing the tourism sector in increasing Gross Regional Domestic Product (PDRB) in Langsa City. It uses secondary data in the form of time series for the period 2013-2022, published by the Central Statistics Agency (BPS) of Langsa City. The data analysis method applies multiple regression analysis using SPSS software. The results show that Wholesale & Retail Trade has a positive but insignificant effect on PDRB in Langsa City. Transportation & Warehousing also has a positive but insignificant effect on PDRB in Langsa City. Additionally, Accommodation & Food Services have a positive but insignificant effect on PDRB. Simultaneously, Wholesale & Retail Trade, Transportation & Warehousing, and Accommodation & Food Services have a significant effect on PDRB in Langsa City.
Analisis Aspek Pasar dalam Pengembangan Bisnis di Era Digital
Authors: Amelia Husna  , Nazryva Nur Muthia  , Sri Rahayu Ningsih  , Dini Vientiany
Published: January 2025

Market aspects analyze market potential, competition intensity, achievable market share, and marketing strategies that can be implemented to reach the desired market share. Through this analysis, business ideas can be effectively channeled to align with market needs and demands. The success of financial performance often depends on market and marketing capabilities, operations, accounting, human resources, and other functions. In the past, before marketing knowledge developed and became widely recognized as it is today, companies prioritized producing as much as possible before attempting to sell their products.In such circumstances, they ignored existing demand conditions, resulting in many producers experiencing failures and ongoing losses because production quantities did not align with market demand.
Current Status and Application of Laminar Flow Control Airfoil Design Technology
Authors: Wen Sen
Published: January 2025

Laminar flow control (LFC) airfoil design technology is a critical technology in modern aviation, it can significantly reduce drag and enhance fuel efficiency, which is increasingly crucial due to rising fuel prices and stringent environmental regulations. This review explores the advancements in LFC, focusing on its ability to optimize aerodynamic characteristics and reduce frictional resistance during flight. LFC techniques are categorized into active flow control (AFC), passive flow control (PFC), and hybrid methods, each with unique advantages. AFC employs external energy to manipulate flow characteristics, while PFC relies on airfoil design to maintain laminar flow without additional energy inputs. Recent developments have included extensive research using simulations and wind tunnel testing to investigate effective laminar flow strategies. Despite its potential, LFC faces challenges such as maintaining laminar flow across varying flight conditions and integrating these designs into modern aircraft concepts. The paper highlights successful applications of LFC in various aircraft, demonstrating significant improvements in aerodynamic performance and fuel efficiency. As the aviation industry prioritizes sustainability, ongoing research aims to overcome existing challenges and enhance the effectiveness of LFC technologies, paving the way for more efficient and environmentally friendly aircraft designs in the future.
Morden glider developments: technological advances and environmental challenges
Authors: Cai Jiaming
Published: January 2025

Gliders are improving performance and efficiency by using lightweight, high-strength composite materials in the application of materials technology. These materials not only reduce the weight of gliders and improve flight performance but also increase durability and safety. However, environmental challenges arise, mainly in the production and recycling of the materials. The production of traditional materials often consumes large amounts of resources and generates waste, while the recycling of composites still faces technical challenges. To address these challenges, sustainable materials and green production processes are being actively explored within the industry, to reduce environmental impact and advance the ultimate development of glider technology. These efforts not only provide new ideas for environmentally friendly processes in aviation but also lay the foundation for future glider innovations.
TE TO TÉ? COSTRUIRE E CONDIVIDERE L’ESPERIENZA LINGUISTICA
Authors: Varcasia Cecilia , Atz Emanuela
Published: January 2025

Il contributo riflette sull’educazione linguistica nel primo ciclo di istruzione, partendo dai repertori linguistici degli allievi per sviluppare percorsi interdisciplinari con obiettivi comuni. Dall’anno scolastico 2018-2019, queste attività si svolgono in un istituto comprensivo della provincia di Bolzano in un contesto di plurilinguismo endogeno (insegnamento in italiano e tedesco) ed esogeno (lingue degli allievi). I materiali utilizzati mostrano un percorso di organizzazione delle conoscenze tramite riflessioni metalinguistiche spontanee in un contesto plurilingue. Dalla scuola dell’infanzia alla secondaria di primo grado, le attività integrate favoriscono la riflessione metalinguistica esplicita attraverso racconti in lingue “inventate”, riflessioni semantico-lessicali e morfologiche in italiano, matematica e scienze. Il contributo evidenzia lo sviluppo delle capacità di ragionare sulla lingua ed esplicitare le riflessioni metalinguistiche.
 
Te To Tè? Constructing/building and sharing language experience
 The contribution gives insights on language education in primary and secondary school, starting from the learners’ linguistic repertoires to develop projects with common interdisciplinary objectives. The activities have been taking place from school year 2018-19 in a comprehensive school in South Tyrol, Italy, in a context of endogenous (subjects taught in Italian and German) and exogenous multilingualism (the students’ heritage languages). The materials show a path of knowledge organization through spontaneous metalinguistic reflections in a multilingual context. From kindergarten to lower secondary school, integrated activities promote explicit metalinguistic reflection through stories in “invented” languages, semantic-lexical and morphological reflections in Italian, mathematics, and science. The contribution highlights the development of learners’ ability to reason about language and articulate metalinguistic reflections.