bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development of an Econometric Model of the Relationship between Migration Dynamics and Demographic Factors in Azerbaijan
Authors: Vilayat Ismayilov  
Published: February 2025

Purpose: The purpose of the article is to build an econometric model of the relationship between the dynamics of migrants and the factors of the demographic process.
Theoretical basis: Individual counteracted equations are created to account for the components of demographic change -births, deaths, and net domestic and international migration. The fertility and mortality equations are easier to model because of the stable changes from period to period depending on income levels and national demographic trends. The net migration equations are more difficult to model because economic conditions, particularly labor market conditions, affect this process over time.
Method: The dialectical method was used to identify common approaches for studying a complex population. Methods of analysis and synthesis, comparison, induction and deduction, etc. were also used for demographic analysis. When developing regression models between the number of migrants and the three identified groups of factors directly influencing it, an econometric regression model was applied.
Results and discussion: A model of the relationship between the number of migrants and the system of demographic factors is built in a five-stage system. Independent variable demographic factors were combined in three groups. Based on the selected data, a correlation model of the relationship between the number of migrants and demographic factors was constructed and the adequacy of the model in the absence of autocorrelation was verified at the level of α=0.01 (1%), α=0.05 (5%).
Research results: The results of the study can be applied in regulating the flow of migrants and maintaining its pace at an optimal level.
Originality/value: The research contributes to the regulation of international migration, thanks to the theoretical and practical results obtained. The relevance and value of the study is confirmed by the influence of migration and demographic processes on the standard of living of the population.
Evaluation of Internal Management Information System Success at Indonesia’s National Zakat Agency: A DeLone and McLean Model Approach
Authors: Umi Masithoh  
Published: February 2025

Implementing Internal Management Information Systems (Intranets) varies in effectiveness across different organizations and is often influenced by system and information quality and utilization. This study evaluates the effectiveness of the Intranet system at Indonesia’s National Zakat Collection Agency, employing the Information System Success Model developed by DeLone and McLean. A quantitative approach was employed using survey data from 206 employees, with 67 valid responses (response rate 32.5%). Structural Equation Modelling-Partial Least Squares (SEM-PLS) was used in this study to examine nine hypothesized relationships among system quality, information quality, service quality, use, user satisfaction, and net benefits. The analysis revealed that five hypotheses were supported: (1) information quality significantly influences user satisfaction (β=0.335, p<0.005), (2) service quality positively affects user satisfaction (β=0.540, p<0.001), (3) use significantly impacts net benefits (β=0.326, p<0.005), (4) use positively influences user satisfaction (β=0.762, p<0.001), and (5) user satisfaction significantly affects net benefits (β=0.538, p<0.001). Four hypotheses were rejected, indicating non-significant relationships between information quality-use, service quality-use, system quality-use, and system quality-user satisfaction. The findings suggest that the Intranet’s success is primarily driven by user satisfaction and system usage rather than technical aspects. Management should improve user experience and promote system utilization to enhance organizational benefits.
Medical Data Security using Deep Learning based Key Generation, Quantum Key Exchange and Modified AES
Authors: Konka Kishan  
Published: February 2025

Medical data security refers to the protection and safeguarding of sensitive patient data in the healthcare domain. It encompasses various measures and protocols designed to ensure the confidentiality, integrity, and availability of medical information. This includes not only medical imaging data but also electronic health records (EHRs), medical test results, patient demographics, and other personally identifiable information (PII). Medical data security is of utmost importance due to several reasons like patient privacy, preventing unauthorized access or disclosure of personal health information, risk of data breaches and identity theft. This paper presents a medical data security framework using deep learning based key generation, quantum key exchange and modified Advanced Encryption Standard (AES). Deep learning-based random number generation for encryption key is an approach that utilizes deep learning models to generate secure and unpredictable sequences of numbers that can be used as encryption keys. Traditional random number generators rely on algorithms or physical processes to generate randomness. Deep learning, on the other hand, offers an alternative approach by leveraging the power of neural networks to learn patterns and generate seemingly random sequences. This generated random number is used as key for quantum key exchange. The proposed framework uses BB84 protocol the utilizes principles of quantum mechanics to achieve secure key exchange. This ensures the confidentiality and integrity of the transmitted data. The AES algorithm is a widely used symmetric encryption algorithm that is known for its high level of security and efficiency. The conventional mix column operation is replaced with low complex algorithm for better performance.
Enhancing Meteorological Pattern Recognition Utilizing U-Net and Bidirectional LSTM Networks
Authors: Z. S. Khaleel  
Published: February 2025

Classification of weather images is very significant in climate monitoring, disaster management, and weather forecasting. This work is an innovation on the architecture that combines U-Net with a BiLSTM network for classification accuracy improvement. U-Net is one of the most advanced convolutional neural networks, and it is characterized by fine-grained feature extraction and spatial information preservation in images. The model combines it with BiLSTM, which focuses on detecting temporal and contextual patterns, thereby enabling a combined understanding of the spatial and temporal dimensions of weather phenomena.
It strengthens all aspects: in addition to how the spatial U-Net's capabilities build strong arguments and why the recognition of correlations with a model such as BiLSTM significantly improves this method against more common, traditionally used, models of the convolutional neural networks family. Tests, also carried out, showed excellent and improved parameters during evaluation like precision, recall, and balance measures, when evaluating results of similar common datasets commonly used within weather forecast systems analysis.
It provides a strong structure for enhancing the classification of weather images and supporting the study of meteorology by bringing in the strengths of convolutional networks and recurrent networks.
Social Marketing Mix : A Framework for Promoting Mental Health Services
Authors: Mahesh Luthia  
Published: February 2025

Aim/Purpose: The study aims to apply the social marketing concepts and framework and develop a marketing mix for reducing social stigma associated with help-seeking behaviour among individuals dealing with mental illness. The study examines perception of practitioners involved in mental well-being services on factors that influence selection of mental health services. This paper highlights the role of social marketing in promoting behavioural change and improving help-seeking behaviour to address mental illness.
Background: The discipline of social marketing can become an important driver for change in terms of brining behavioural change. Social marketing involves adapting commercial marketing theories and practices for supporting campaigns for social change. There is a need to examine how contemporary marketing practices can help to promote mental health service.
Methodology: The study involved review of existing literature on social marketing and its role in social change. A cross-sectional study was conducted among psychologist, social workers, mental health counsellors and HR professionals using online questionnaire based on stratified sampling. The findings of the survey were integrated with the literature using to adopt a mixed method research and propose a framework for social marketing. Descriptive analysis was carried out based on the data collected.
Contribution: The study adds to the body of knowledge of social marketing by of proposing a social marketing framework that can enable service providers to create awareness and reduce the stigma associated with seeking help for mental illness. The study could help community-based services in mental to Promote help-seeking behaviour.
Findings: The findings indicate that adapting the marketing mix for social marketing can creative positive attitude towards mental health and its services. Emotional or interpersonal problems carries social stigma and Confidentiality and safe space for counselling can create a conducive environment for help-seeking. Social media and influencers can contribute to create awareness on the benefits of mental well-being will bring in a social change to accept counselling services.
Marketing Research of the Territory's Image: on the Example of the ISSYK-KUL Region of Kyrgyzstan
Authors: Nukeeva Medina Anarbekovna  
Published: February 2025

This article discusses the process of determining a favorable image and development of a territory (region), as well as its practical development and further functioning. The image of a region is a spontaneously formed and/or artificially created image of a region that is steadily entrenched in the mass consciousness, under the influence of a set of emotional, rational characteristics, beliefs and feelings of people who arise about the characteristics of a given territory. Image is one of the determining factors of the perception of the territory. The image of the territory allows local authorities effectively to interact with various target groups: the population, tourists, investors, etc.
A positive image of the territory is an important element of ensuring socio-economic stability. This article is devoted to the study of the image of the Issyk-Kul region of Kyrgyzstan. Issyk-Kul region is a region located in the central part of Kyrgyzstan. It got its name from Lake Issyk-Kul, which is one of the largest mountain lakes in the world. The region is known for its unique nature, picturesque mountain landscapes, clean air and diverse types of vegetation.
Spontaneous Micro-facial Expression Detection using Attention-based Convolutional Gated Recurrent Neural Networks with RMSProp Optimization
Authors: Ramakrishna Gandi  
Published: February 2025

Introduction: Facial micro expressions have a significant role in communicating hidden emotions, offering profound implications in multiple areas such as psychology, cybersecurity, and the study of human-computer interaction. However, recognizing micro-expressions is tough because of their transient nature. Furthermore,Micro expressions are significantly shaped by the visual characteristics of the face and the interactions among its various sub-regions. Recent advances in computer vision have improved self-supervised learning.
Traditional CNNs for vision disorders learn only from whole photos or videos and cannot consistently distinguish facial micro expressions. Some existing CNN models might lack advanced attention mechanisms to effectively prioritize subtle micro-expression features within the complex facial data. They may leading to potential misinterpretation of expressions.
Objectives: This research offers the Attention Convolutional Gated Recurrent Neural Network with RMSProp (ACGRNN- RMSProp) classifier aims to achieve high accuracy and robustness in micro facial expression recognition. The attention mechanism sharpens the model's emphasis on important facial regions, while convolutional layers gather spatial features, and GRUs effectively capture temporal dynamics. The RMSProp optimizer ensures efficient and stable training, making this approach well-suited for the complex task of recognizing subtle and fleeting micro expressions.. This suggested approach is applied to the FER2013 dataset and compared to conventional micro expression recognition baseline methods.
Methods: The FER2013 dataset is initially loaded and processed. Facial landmarks in this dataset are detected using a Multi-Task Cascaded Convolutional Neural Network, after which features are extracted from the processed data using EfficientNetB3 and InceptionResNetV2. The features obtained from extraction are then fused and subsequently classified using an Attention Convolutional Gated Recurrent Neural Network with RMSProp optimization.
Results:This hybrid model demonstrates exceptional classification performance, achieving precision, recall, and F1-score of 94.5% each, along with an accuracy of 96.43%. Furthermore, it includes additional metrics such as the Matthews Correlation Coefficient (MCC), Receiver Operating Characteristic(ROC) Curve in this field.
Conclusions:This study showcases enhanced recognition accuracy when compared to a range of leading models in the field,eliminated the requirement for system preprocessing procedures such as contrast enhancement, gradient operators, or dimensionality reduction for accurate results.Leverage the inherent relationships between face identification and other face analysis tasks to enhance future performance.
Kadar Trigliserida dan Asam Urat pada Peminum Alkohol (Etanol)
Authors: Lestari Fitriana Yeni , Mu’awanah Isnin Aulia Ulfah , Ariyani Titin 
Published: February 2025

Alkohol (etanol) merupakan minuman yang mengandung zat adiktif yang dapat menimbulkan ketagihan dan ketergantungan. Asupan alkohol mengganggu metabolisme lemak dengan meningkatkan lipolisis pada jaringan adipose serta menyebabkan penumpukan lemak ektopik di hati dapat menyebabkan penyakit hati berlemak dan menigkatkan kadar trigliserida Konsumsi alkohol dikaitkan dengan peningkatan kadar asam urat karena etanol dan purin dalam alkohol merangsang produksi asam urat dalam darah. Penelitian ini bertujuan untuk mengetahui hubungan konsumsi alkohol terhadap kadar trigliserida dan asam urat pada peminum alkohol di Kalurahan Tirtorahayu Kabupaten Kulon Progo. Desain penelitian menggunakan eksperimental serta dengan pendekatan deskriptif observasional kuantitatif analitik. Sampel yang diperoleh sebanyak 17 orang yang berusia 20 – 60 tahun, jenis kelamin laki-laki. Uji statistik yang dilakukan yaitu uji Shapiro Wilk untuk mengetahui normalitas distribusi sampel, uji korelasi Spearman’s rho untuk melihat hubungan konsumsi alkohol terhadap kadar trigliserida dan kadar asam urat. Hasil uji menunjukkan tidak terdapat hubungan frekuensi konsumsi terhadap kadar trigliserida (p=0,836 atau p> 0,05) dan kadar asam urat (p=0,889 atau p> 0,05), serta tidak terdapat hubungan durasi konsumsi terhadap kadar trigliserida (p=0,146 atau p> 0,05) dan kadar asam urat (p=0,374 atau p>0,05) sedangkan volume konsumsi alkohol terhadap trigliserida terdapat hubungan (p=0,035 atau p< 0,05) dan kadar asam urat (p=0,038 atau p< 0,05). Dapat disimpulkan bahwa tidak ada hubungan antara frekuensi dan durasi konsumsi alkohol terhadap kadar Trigliserida dan asam urat. Sedangakan terdapat hubungan volume konsumsi alkohol terhadap kadar Trigliserida dan kadar asam urat.
Impactos climáticos e superexploração dos recursos da biodiversidade no Marajó
Authors: Oliveira Patricia Chaves de , Fenzl Norbert , Lopes Luís Otávio do Canto , Gomes Kassiana Renê , Santos Marcia Cristina , García Waldilene do Carmo , Peixoto Herbert Júnior Campos , Souza Evelyn Rafaelle de Oliveira 
Published: February 2025

O arquipélago flúvio-marítimo do Marajó na costa do Pará, é um ambiente diverso, tanto do ponto de vista ambiental quanto cultural. Atualmente, essa região já sofre com os impactos das mudanças climáticas, como a erosão costeira e o avanço do mar. Considerando que as principais atividades da Bioeconomia de populações tradicionais no Marajó são o extrativismo vegetal e a pesca historicamente praticada, então quais seriam esses impactos climáticos sob a ótica de quem vive diariamente a floresta, o manguezal e o mar, sendo esta a principal questão científica da pesquisa. A metodologia caracterizou-se pela utilização de questionários semiestruturados e análise das narrativas de agroextrativistas e pescadores a partir de amostragens seguindo o método Snowball sampling. Também foram calculados a Razão de Extrativismo/Agricultura (REA) ou Razão D’Cleyton e a Razão de Vulnerabilidade Extrativista (RVE). Os resultados demonstraram a partir das narrativas que as seguintes espécies já são vulneráveis a partir de dois fatores combinados, superexploração associada às mudanças climáticas, são elas: Cocos nucifera, Mangifera indica, Manilkara achras; Astrocaryum tucuma, Talisia esculenta, Crescentia cujete, Physalis pubescens; Cocos nucifera, Ucides cordatus. Essas espécies são, portanto, indicadores de riscos socioeconômicos e ambientais, que podem ser úteis no desenvolvimento de políticas públicas capazes de mitigar os efeitos das anomalias climáticas locais. Por fim, foi elaborado um Atlas como instrumento de popularização dos resultados científicos encontrados. Este Atlas é uma obra pedagógica que expressa a contribuição para a educação ambiental crítica, local, costeira e amazônica em contextos de mudanças sociais, econômicas e climáticas globais.
Asuhan keperawatan pasien acute respiratory failure et causa ensefalopati uremikum di ICU: Studi kasus
Authors: Monicha Ecy Oktaviana , Jufrizal Jufrizal , Aklima Aklima 
Published: February 2025

Latar belakang: Acute respiratory failure (ARF) merupakan kondisi kritis dimana sistem pernapasan gagal untuk mempertahankan pertukaran gas yang memadai yang ditandai dengan hipoksemia atau hiperkapnia atau keduanya. Salah satu faktor penyebab ARF adalah ensefalopati uremikum. Pasien dengan ensefalopati uremikum akan terjadi penumpukan ureum sehingga pasien mengalami penurunan kesadaran dan bahkan koma, yang dapat mengakibatkan ketidakmampuan untuk mempertahankan ventilasi spontan. Tujuan: Studi kasus ini bertujuan untuk dengan melakukan dan mendeskripsikan asuhan keperawatan pada pasien dengan acute respiratory failure et causa ensefalopati uremikum. Metode:Penelitian ini menggunakan studi kasus dengan pendekatan asuhan keperawatan keluarga yang meliputi pengkajian, penetapan diagnosa, intervensi, implementasi, dan evaluasi. Hasil: Hasil studi kasus menunjukkan bahwa diagnosa yang muncul pada Ny. AR yaitu risiko aspirasi dengan rencana keperawatan pencegahan aspirasi, gangguan pertukaran gas dengan rencana keperawatan manajemen ventilasi mekanik, penurunan kapasitas adaptif intrakranial dengan rencana keperawatan peningkatan tekanana intrakranial dan ketidakstabilan glukosa darah dengan rencana keperawatan manajemen hiperglikemia. Kesimpulan: Terdapat sebagian perbaikan pada kondisi pasien seperti terjadi peningkatan kesadaran, tidak terdapat residu lambung, dan tidak terdengar suara napas tambahan namun harus dilakukan peningkatan intervensi lainnya diakibatkan kondisi pasien yang belum stabil. Rekomendasi: Diharapkan pelaksanaan penanganan pasien dapat dilakukan segera dengan intervensi yang menunjang perbaikan kondisi pasien dan terus meningkatkan asuhan keperawatan pada pasien acute respiratory failure.
Asuhan keperawatan pasien post craniotomy et causa sol intrakranial di intensive care unit: Studi kasus
Authors: Tifany Adinda , Nurhayati Irfanita , Fikriyanti Fikriyanti 
Published: February 2025

Space Occupying Lesion (SOL) is a critical condition that requires intensive care in monitoring hemodynamic stabilization. SOL refers to a mass or lesion that occupies space within the skull. The pressure from this lesion causes neurological disturbances and increased intracranial pressure (ICP). One of the medical management strategies for SOL patients is craniotomy. This case study aims to describe the nursing care for patients with post-operative craniotomy due to intracranial SOL in the Intensive Care Unit. The methodology used is a case study. The results of this case study show that the diagnoses encountered in the patient include decreased intracranial adaptive capacity, gas exchange disturbances, aspiration risk, infection risk, and ventilator weaning disturbances. The interventions used include intracranial pressure management (ICP), mechanical ventilation management to prevent aspiration, infection prevention, and mechanical ventilation weaning. The conclusion of this case study is that there has been some improvement in the diagnoses, such as gas exchange disturbances and successful ventilator weaning. However, other interventions have not been optimal due to the patient's unstable condition. It is hoped that the patient’s management can be carried out promptly with interventions that support the improvement of the patient’s condition.
Space Occupying Lesion (SOL) suatu kondisi kritis yang memerlukan perawatan intensif dalam pemantauan stabilisasi hemodinamik. SOL merupakan massa atau lesi yang mengisi ruang di dalam tengkorak. Pendesakan akibat lesi tersebut mengakibatkan gangguan neurologis dan peningkatan tekanan intrakranial (TIK). Penatalaksanaan medis pasien SOL salah satunya adalah craniotomy. Tujuan dari studi kasus ini adalah untuk mendeskripsikan asuhan keperawatan pada pasien dengan post op craniotomy et causa SOL intrakranial di Intensive Care Unit. Metodologi yang digunakan adalah case study. Hasil studi kasus menunjukkan bahwa diagnosa yang muncul pada pasien yaitu penurunan kapasitas adaptif intrakranial, gangguan pertukaran gas, risiko aspirasi, gangguan penyapihan ventilator, dan risiko infeksi. Intervensi yang digunakan adalah manajemen peningkatan intrakranial (PTIK), manajemen ventilasi mekanik pencegahan aspirasi, penyapihan ventilasi mekanik, dan pencegahan infeksi. Kesimpulan dari studi kasus ini adalah terdapat sebagaian perbaikan pada diagnosa yaitu gangguan pertukaran gas dan keberhasilan penyapihan ventilator, namun intervensi lainnya belum optimal dikarenakan kondisi pasien yang belum stabil. Diharapkan pelaksanaan penanganan pasien dapat dilakukan segera dengan intervensi yang menunjang perbaikan kondisi pasien.
Survey paper on Crop Classification using Convolutional Neural Network
Authors:   Department of Computer Engineering, Adsul’s Technical Campus Chas., Bakshi Krish 
Published: February 2025

Crop Classification using CNN - A Multi-Model Approach for Crop Classification and Health Assessment Using Convolutional Neural Networks and GPT Integration. The integration of deep learning and natural language processing (NLP) in agriculture has gained significant attention for automating crop classification and disease diagnosis. This survey provides an extensive review of various deep learning models applied in crop classification, plant health assessment, and NLP-based report generation. The study explores the effectiveness of object detection models like YOLO, classification networks such as ResNet and EfficientNet, and NLP models like GPT for generating quality assessments. Additionally, this paper discusses the challenges and future research directions in this domain. The survey serves as a precursor to our research implementation, which integrates CNN-based models for crop identification, health assessment, and GPT-based NLP solutions for automated reporting.

Key Words: Deep Learning in Agriculture, Convolutional Neural Networks (CNNs), Plant Disease Detection, Generative AI for Crop Analysis, Precision Agriculture.