bluuebunny/crossref_metadata_2025 huggingface dataset:
Citizenship and Democracy in the Texas Social Studies Curriculum: A Historical Comparison
Authors: Lambert Jarod M.
Published: May 2024

Using exploratory qualitative document analysis, this article examines the conceptions of citizenship and democracy in Texas's social studies curriculum standards. In a historical comparison of standards from 2011 and 2018, conceptions of citizenship and democracy are compared to definitions developed by international civic education experts. Citizenship and democracy in the Texas curriculum are identified as inconsistent with the definitions of those terms developed by civic education experts. Instead, the terms are seen to be related to Barber’s (1984/2003) thin democracy and procedural conceptualizations of citizenship. Moreover, conceptions of the terms remain the same from 2011 to 2018. Implications for teacher education and public school practice are discussed. Recommendations for future research are presented. Included among recommendations for future research is the analysis of curriculum documents in additional U.S. states and curriculum documents in countries outside the United States.
The Efficacy of e-Guru Application in Boosting Learning Effectiveness: Does It Deliver Results?
Authors: Ilham Muhammad , Rahman Fadhlur , Kholid Mohammad , Sari Dwhy Dinda
Published: May 2024

In light of the unexpected events caused by the pandemic, educators urgently needed inventive educational resources to improve student comprehension. The rapid implementation of adaptable methods for instruction became necessary. E-guru is a user-friendly online platform that shows the potential to encourage student participation. This study conducted at State Vocational High School 1 of Tanah Luas in North Aceh examines the influence of e-guru on learning effectiveness. Using quantitative methods and conducting SPSS analysis, the results indicate no sie-guruchast impact of e-guru on effectiveness (p = 0.846 > 0.05). Based on the comparison between the T count value (0.196) and the T table value (1.685), the study concludes that e-guru does not significantly impact learning outcomes. The result emphasizes the necessity of further studies to enhance e-learning platforms to address evolving teaching and learning demands.
Analisis Determinan yang Mempengaruhi Penyaluran Kredit Pemilikan Rumah Perbankan Indonesia 2015Q1-2023Q2
Authors: Mahardika Dian , Khasanah Uswatun
Published: May 2024

Penelitian ini bertujuan untuk mengetahui pengaruh jangka pendek dan jangka panjang Inflasi, Produk Domestik Bruto, Indeks Harga Properti Residensial, Suku Bunga Dasar Kredit (KPR), dan Kurs Tengah US Dollar terhadap  penyaluran kredit pemilikan rumah (KPR) Indonesia. Alat analisis yang digunakan adalah Eviews 12. Jenis data yang digunakan dalam penelitian ini adalah data time series tahun 2015 kuartal 1 hingga 2023  kuartal 2 di Indonesia. Data bersumber dari website resmi Badan Pusat Statistik Indonesia, website resmi Bank Indonesia dan website resmi Otoritas Jasa Keuangan Indonesia. Hasil penelitian menunjukkan bahwa dalam jangka pendek KPR merespon semua variabel pada periode tahun selanjutnya. Pada jangka panjang semua variabel tidak signifikan.
Memajukan Pendidikan Melalui Program Digitalisasi yang Efektif di Indonesia
Authors: Adila Salsabila , Rodiyah Isnaini
Published: May 2024

Penelitian ini bertujuan untuk mengevaluasi implementasi program digitalisasi akademik di sebuah departemen pendidikan negeri, dengan fokus pada bagaimana program-program tersebut meningkatkan soft skill para pendidik dan mempersiapkan para siswa dengan kompetensi sains dan teknologi. Dengan menggunakan metode deskriptif kualitatif, data dikumpulkan melalui observasi, wawancara, dan dokumentasi, yang melibatkan sumber primer dan sekunder, dengan teknik pengambilan sampel purposif. Hasil penelitian menunjukkan bahwa program-program tersebut berhasil mendukung pengembangan kebutuhan dasar, akses pendidikan, dan manfaat dari ilmu pengetahuan, teknologi, seni, dan budaya, sehingga meningkatkan kualitas hidup dan kesejahteraan manusia. Program-program tersebut selaras dengan peraturan perundang-undangan dan secara efektif menargetkan siswa sebagai calon pembangun bangsa di masa depan.
Data-Driven Transformation of Agri-Supply Chain (Ascs): Comprehensive Review
Authors: Piyush Nimbokar  , Sanika Yawale  , Samiksha Kasulkar  , Shreya Patil  , Seema Wankhade
Published: May 2024

Traditionally, the agricultural supply chains have dealt with a lot of flaws that affect the whole sector. The agricultural industry is undergoing a transformative shift with advanced technologies, particularly Machine Learning. This review depicts the bridging of the gap in the development of agricultural supply chains. ML and AI are found to be powerful tools for making informed decisions regarding challenges like post-harvest losses, price volatility, logistical difficulties, etc. In many review papers, the stated challenges are not addressed completely. The same can be addressed by handling and analyzing the data carefully and properly using ML algorithms to make the system more efficient than the present scenario. We believe these gaps can be bridged with techniques like demand forecasting, optimal resource utilization, supply chain visibility, etc.
Multi-Domain Smart Safety Helmet
Authors: Kavitha S  , Tammineni Loksai  , Vanna Balaji Naidu  , Shiva kumar  , Venkatesha B
Published: May 2024

Motorcycle accidents and head injuries are critical concerns globally, especially where helmet non-compliance is prevalent. To address this, a multi-domain smart safety helmet is proposed for rider safety and accident prevention through advanced sensor technology. This smart helmet integrates sensors like an MQ-3 alcohol sensor and helmet detection sensors to ensure safety conditions before the motorcycle engine starts. If alcohol levels exceed a threshold, the ignition system disables, preventing intoxicated riding. Helmet detection promotes helmet use, reducing head injury risk. The scalable sensor infrastructure enables multi-domain applications beyond motorcycles. This helmet can integrate into industries like coal mining and firefighting. In coal mining, it monitors environmental conditions and worker vital signs. In firefighting, it detects hazardous gases and monitors firefighter status. During motorcycle operation, the helmet continuously monitors critical parameters—speed, tilt, and environment—providing immediate feedback on unsafe behaviours. In accidents, the helmet's accelerometer detects impacts, activating GPS to pinpoint the location and GSM to alert emergency contacts. This smart helmet aims to enhance motorcycle safety, prevent accidents, and expedite emergency responses. It represents progress towards reducing motorcycle-related injuries and fatalities, with adaptable features for broader safety applications across industries and domains.
Power Augmentation of Gas Turbine Using Exhaust Flue Gas Operated Vapor Absorption Machine
Authors: Hemex Premjiyani  , Arunesh Dwivedi  , Hiren Rana
Published: May 2024

Industrial gas turbines (GT) that operate at constant speed are constant-volume-flow combustion machines. As the specific volume of air is directly proportional to the temperature, an increase in air density results in a higher air mass flow rate at low air ambient temperatures. This results more mass of air is now passes through same volume gas turbine space. Consequently, the gas turbine power output increases proportionally with the increase in air mass flow rate. For geographic regions where warm and humid months are predominant throughout the year, significant power loss occurs during these months, and a higher rate of expensive fuel is fired at reduced power output. A gas turbine inlet air cooling technique is a useful option to enhance GT output. One of the innovative options for power augmentation of gas turbine is inlet air conditioning using a vapor absorption machine (VAM). Using VAM for GT intake air conditioning has the advantage over other systems in that it can be operated from waste heat. Many gas turbine machines, particularly natural gas pumping stations, are operated without heat recovery steam generator (HRSG) or heat recovery option. Valuable heat energy is escaped with exhaust flue gas in these systems. This paper demonstrates how GT exhaust waste heat can be utilized for its own power generation enhancement. In this study, a flue gas-based vapor absorption machine is selected for cooling the inlet air of a 26 MW gas turbine, which is used to drive the booster compressor of a natural gas pumping station. The capacity of the VAM for the required cooling effect has been calculated. The expected GT power enhancement from intake air gas conditioning has also been estimated in this paper.
Post Fire Assessment of RCC Buildings Through Rapid Visual Screening
Authors: Mahendra Kumar  , Archana Bohra Gupta
Published: May 2024

The effectiveness of rapid visual screening (RVS) in determining the fire risk of reinforced concrete (RCC) buildings is examined in this review. RVS provides a quick and practical approach to evaluate fire risks, addressing the shortcomings of traditional methods. Through a comprehensive examination of methodology, advantages, limitations, and future directions, this study aims to enhance understanding and application of RVS in fire assessment. The study employs a systematic approach to evaluate the effectiveness of RVS, analyzing its application in assessing fire vulnerability in RCC structures. Key aspects of RVS methodology, including visual inspection, identification of structural vulnerabilities, and categorization of damage, scrutinized. A case study of the Chopasani Housing Boards building in Jodhpur provides empirical evidence of RVS's utility in identifying fire-related structural vulnerabilities. The concluded, the analysis reveals that RVS effectively categorizes fire-induced damage in RCC buildings, facilitating prioritization of mitigation efforts. Damage classifications, ranging from mild to extreme, are discerned through RVS, underscoring its ability to swiftly assess structural vulnerabilities. Additionally, RVS analysis elucidates the residual strength of RCC components post-incident, providing valuable insights for retrofitting and maintenance efforts. Overall, this study highlights the pivotal role of RVS in bolstering structural fire safety measures, emphasizing its practicality, cost-effectiveness, and accessibility. However, limitations such as subjectivity and inadequate assessment of complex structures necessitate ongoing refinement and integration with advanced technologies. The findings underscore the importance of RVS in enhancing fire safety assessment practices and mitigating fire risks in urban buildings, particularly in the context of reinforced concrete structures.
Understanding the Emotional Detachment of Adolescents from Their Parents: A Qualitative Study
Authors: Martin Abigail T. , S. Ordonez Christian Joseph , C. Mendoza Gerard Adrian , De Jesus Sophia Isabelle T. , De Luna Marienell Faith O.
Published: May 2024

An individual’s attachment is the foundation for their socioemotional development and their capability to establish and maintain meaningful relationships. In contrast, emotional detachment is a phenomenon that occurs when individuals find themselves lacking emotional attachment or connection towards other people. The present study aimed to understand adolescents’ emotional detachment from their parents and what it entails to be emotionally detached. Previous studies have shown that the issue of children being emotionally detached to their parents persists to this day, and that it is a pressing matter that the child can be burdened with until adulthood. However, only a few have touched on the emotional detachment of adolescents, despite adolescence being a crucial period in an individual’s life that comes with heightened sensitivity and vulnerability. Thus, the present study was conducted in search of answers to this question by interviewing emotionally detached adolescents and coding techniques to utilize thematic analysis in the analysis of their answers. The findings show that the emotional detachment of adolescents from their families stems from various factors within their family dynamics. This affects not only the individual’s emotions within themselves but also towards other people. It gives the implication that families, especially parents, must be mindful of their children as they depend on them not just financially, but emotionally. If they don’t, the child could grow up carrying the burden of being emotionally detached which they could potentially pass on to their future offspring as well.
Financial Literacy and Self-Control as the Predicting Variables to the Financial Behavior of Senior High School Students
Authors: Maulias Jerol A. , Abrencia Kyla M , Amar Charmell Nicole M , Baldesco Jenebeth B. , Fuentes Kisha Lee L. , Guevarra Reyna Jean R , Jancinal Hans Ezekiel R , Luzon Donna Jen , Malubay James Anthony C , Porras Kriszel A , Valiente Justine P , Clamares Krystal Joy M. , Pelandas Anna Marie O.
Published: May 2024

This study dealt with the financial literacy and self-control, as predictors to financial behavior among Senior High School students. The primary goal of the study was to determine the level of financial literacy, self-control, and financial behavior in terms of their respective indicators, what domains of financial literacy and self-control substantially influence financial behavior. Also, this study utilized a quantitative-correlational design with 221 respondents among Senior High School students. The average weighted mean, Pearson R, and multiple regression analysis were the statistical tools used in this study. Along with this, results showed a high level of financial literacy among Senior High School students in terms of saving, budgeting, and investing. On the other hand, the results also showed a high level of self-control among Senior High School students in terms of inhibition, initiation, and continuation. Likewise, results showed a high level of financial behavior among Senior High School students regarding saving behavior, spending habits, and financial goal setting. In addition, there is a low correlation, and a significant relationship between financial literacy and financial behavior. Furthermore, there is a high correlation, and a significant relationship between self-control and financial behavior. Hence, this leads to the rejection of the null hypothesis. Saving, budgeting, and investing as domains of financial literacy have a significant influence to financial behavior. Additional, inhibition, initiation, and continuation as domains of self-control have a significant influence to financial behavior. These results helps the student know that their financial behavior or anything financial-related could be incorporated in their academic and non-academic journey.
The Influence of Parental Involvement and Socioeconomic Status on Academic Achievement among Special Science Class Students
Authors: Francisco Decereh R , Allorda Althea I , Cruda Chris Laurence M , Cruda Zarena Nikka F , Dejado Shainne Evanrose F , Dela Cruz Cherry Mae S , Opisan Anesa C , Pateǹo Gian Vincent G. , Quirino Ashley O , Ragadi Mary Dune Jullian P , Yuson Jemimah B , Clamares Krystal Joy M. , Pelandas Anna Marie O.
Published: May 2024

This research aimed to investigate the impact of parental involvement and socioeconomic status on the academic achievement of Special Science Class students at Lorenzo S. Sarmiento Sr. National High School. Employing a quantitative approach with 167 respondents, mean scores, Pearson’s r, and regression analysis were utilized for data analysis. Along with this, the findings revealed a very high level of responsibilities and attendance, and a high degree of parental involvement, particularly in volunteer and mentoring activities, and communication and support. However, literacy and tutorial assistance, along with leadership and partnership, demonstrated moderate levels. Furthermore, socioeconomic status exhibited high levels, with family background, peer influence, interest, and health serving as significant indicators. The results also showed a very high level of student-related factors influencing academic achievement, followed by a high level of degree predominantly influenced by teacher-related factors, home-related factors, and school-related factors. The study established a significant positive correlation between parental involvement and academic achievement (Pearson’s r = 0.565, p<0.001), as well as between socioeconomic status and academic achievement (Pearson’s r = 0.750, p<0.001). This led to the rejection of the null hypothesis, signifying a substantial relationship between parental involvement, socioeconomic status, and academic achievement among Special Science Class students. Regression analysis identified responsibilities and attendance, literacy and tutorial assistance, and volunteer and mentoring activities as influential domains of parental involvement on academic achievement. Moreover, interest and peer influence emerged as significant predictors of academic achievement within the socioeconomic status domains. These findings underscore the critical roles of parental involvement and socioeconomic factors in shaping academic success among Special Science Class students, offering valuable insights for educators and stakeholders.
Peran Motivasi dan Penilaian SOTH terhadap Kinerja BKB Kartini di Kelurahan Bandungrejosari, Sukun Kota Malang
Authors: Made Iska Aprilita Wardani  , Pudji Lestari  , Dewi Retnowati  , Kristin Juwita
Published: May 2024

Motivation and assessment are ways to determine the results of program work both individually and in general for the organization as a whole. The research method is Paired Sample Test, namely comparing the roles before and after the roles of Motivation and SOTH Assessment. Meanwhile, qualitatively, skills are assessed, namely consisting of coordination and teamwork abilities; discipline and solutions to problems. Assessment data from January to March 2024. The time limit was chosen due to ongoing program adjustments. The research results show that SOTH motivation and assessment have an average impact of 26% and make motivation and assessment more attention to all members of the organization. Based on the Paired Sample Test, it can be concluded that from the Paired Sample Test calculations it is proven that there is a significant difference in the average role of Motivation and Assessment before and after the delivery of the material begins (Pre Test) for the participants (students) at a confidence level of 95%. And proves that motivation and assessment are useful for program efficiency and effectiveness, controlling and monitoring performance, and are able to encourage participants (students), managers and presenters to contribute to even better performance.
Image Classification Model
Authors: Sachin Dhawas  , Hitakshini Thombare  , Harsh Humne  , Divyanshu Awari
Published: May 2024

Image Classification nowadays is used to narrow the gap between the computer vision and human vision so that the images can be recognized by machines in the same way as we humans do. It deals with assigning the appropriate class for the given image. We therefore propose a system named Image Classification using Deep Learning that classifies the given images using Classifiers like Neural Network. This system will be developed to measure the accuracy of classifying images on GPU (NVIDIA) and CPU. The system will be designed using Python as a Programming Language and Tensorflow for creating neural networks.
Different Method of Plastic Waste Management in the Light of Ecosystem Balance: A Review
Authors: Dhiraj Kumar  , Dr. Prince Bansal
Published: May 2024

The present paper is review paper based on the different method of plastic waste management in the light of ecosystem balance. Plastic waste has become a major environmental concern, causing pollution in both land and marine ecosystems. As a result, plastic debris is accumulating in landfills and natural environments instead of decomposing. This accumulation is causing various environmental hazards and negatively impacting habitats and species distribution. To address this issue, researchers have been focusing on finding effective methods of plastic waste management that promote ecosystem balance. Understanding ecosystem balance is crucial in the study of different methods of plastic waste management. It involves recognizing the intricate relationships between organisms, their habitats, and the natural processes that maintain environmental stability. This understanding is important when considering the impact of plastic waste on ecosystems and the need for effective waste management strategies. It also plays a crucial role in identifying the most suitable methods for plastic waste management that minimize negative impacts on the environment and promote ecological balance
AI Image Generator
Authors: Dr. Manisha Pise  , Naveen Yadgiri  , Preksha Gaikwad  , Yashika Dusawar  , Prathamesh Nandanwar
Published: May 2024

In recent years, the field of artificial intelligence has witnessed remarkable advancements in image generation, with Open AI at the forefront of this innovative wave. This abstract explores the development and implications of an Image Generator using Open AI technologies, emphasizing its potential to facilitate creative expression through AI-generated art. The foundation of this Image Generator is rooted in Open AI's GPT-3, a state-of-the-art deep learning model that has demonstrated remarkable capabilities in natural language understanding and generation. Leveraging GPT-3's prowess, the Image Generator harnesses the power of generative adversarial networks (GANs) to produce visually stunning images. This amalgamation of technologies allows artists and creators to transcend traditional creative boundaries by generating art that is both novel and visually captivating.
One of the key features of this Image Generator is its ability to generate art based on textual prompts. Users can provide descriptive or conceptual inputs, and the AI model interprets these prompts to create images that align with the given descriptions. This process not only sparks creativity but also offers a unique medium for artists to convey abstract ideas and emotions visually. Moreover, the Image Generator incorporates neural style transfer, enabling users to merge artistic styles and concepts seamlessly. The implications of such a tool are profound. Beyond serving as a source of inspiration for artists, it democratizes the creative process, making it accessible to individuals with varying levels of artistic expertise. Additionally, it has potential applications in fields such as advertising, graphic design, and entertainment, where generating captivating visuals is paramount. Nevertheless, ethical considerations and challenges, such as issues of copyright, authenticity, and the potential for misuse, should be addressed as the technology evolves. Open AI's commitment to responsible AI development is crucial in navigating these complexities. In conclusion, the Image Generator using Open AI is a testament to the transformative power of AI in the realm of creative expression. It empowers artists and creators to explore new dimensions of artistry while presenting opportunities and challenges that require careful consideration. As this technology continues to evolve, its impact on the art world and beyond is likely to be profound, opening up new horizons for human creativity and innovation.
Dubify: Multilingual Video Translation Platform
Authors: Dr. Shabina Modi  , Mr. Aniket Kamble  , Mr. Pratik Gawande  , Ms. Pritee Ithape
Published: May 2024

In an increasingly globalized society, effective cross-linguistic communication is essential. This brief presents a new approach. Dubify is a feature-rich application created to facilitate smooth translation of video information between languages. Dubify uses advanced machine learning algorithms to provide real-time translation services, ensuring that video content is understandable and accessible to viewers around the world. Strong speech recognition, accurate translation, and natural language generation are some of Dubify's main strengths. Thanks to the platform's extensive language support, users can easily translate video content into multiple languages. In addition, Dubify offers customization tools that allow users to adjust translations to suit their particular taste and dialect. Dubify's easy-to-use interface and advanced translation skills make it a flexible choice for individuals, businesses, and organizations looking to translate
Survey on Blind Assist System using ML and Image Processing
Authors: Prof. Deepu G  , Adarsh N M  , Bhuvan R  , Darshan A  , Darshan R
Published: May 2024

This paper presents a Blind Assist System (BAS) leveraging Machine Learning (ML) and Image Processing (IP) techniques to enhance the autonomy and safety of visually impaired individuals. The system utilizes a convolutional neural network (CNN) to process real-time image inputs from a wearable camera device. Through ML classification, it identifies objects, obstacles, and environmental cues. The IP module further refines data, providing depth perception and spatial awareness. Leveraging ML's adaptability, the system continuously learns and improves its recognition accuracy. Integration with auditory feedback facilitates intuitive interaction, conveying vital information to users. In evaluations, the BAS demonstrates promising results in aiding navigation and increasing users' independence. The fusion of ML and IP offers a robust solution for empowering the visually impaired in navigating complex environments
PARÁSITOS INTESTINALES EN MONOS AULLADORES (Alouatta coibensis trabeata) DE LA RESERVA FORESTAL EL MONTUOSO, LAS MINAS, PROVINCIA DE HERRERA
Authors: Frías Castillo Edy Alberto , Montañez Grael Dalila Del Carmen , De la Cruz Lombardo Alexis , Goti Italo
Published: May 2024

Nuestro objetivo fue determinar la ocurrencia de parásitos intestinales en monos aulladores de Azuero (Alouatta coibensis trabeata) en la zona alta de la Provincia de Herrera. Los monos aulladores presentan una alta cantidad y diversidad de parásitos, sin embargo, la información sobre la parasitosis no se ha caracterizado. Se colectaron 43 muestras de materia fecal, las cuales fueron preservadas en formol al 10%, y posteriormente analizadas por métodos coprológicos de observación directa y las técnicas de Ritchie y Willis-Molloy, para determinar la presencia de parásitos intestinales de los monos del área de estudio, durante los meses de octubre 2019 a enero 2020. Los parásitos intestinales encontrados fueron Strongyloides sp. (34%), Entamoeba sp. (22%), Ascaris sp. (18%), Tripanoxyuris sp. (16%) y Controrchis sp. (11%). No se observó diferencias significativas en cuanto a la prevalencia parasitaria durante los meses de monitoreo. Los resultados sugieren que las cargas parasitarias están determinadas por condiciones particulares del hábitat, alimentación y comportamiento de los monos dentro de la reserva.
MODELO DE EVALUACIÓN DE LOS APRENDIZAJES BASADO EN EVIDENCIAS CONTEXTUALIZADO AL NIVEL SUPERIOR PÚBLICO PANAMEÑO
Authors: Tejedor De León Damaris Varsovia , Tejedor De León Elzebir Gisela
Published: May 2024

Estudios a nivel internacional han demostrado que en las instituciones educativas prima un modelo de evaluación de los aprendizajes tradicional-cognoscitivista (Huerta, 2018; Ramis et al., 2019), por lo que es necesario proponer nuevos modelos evaluativos. El objetivo principal de esta investigación es el diseño un modelo de evaluación de los aprendizajes basado en evidencias, buscando articular la planificación, la ejecución y la evaluación, a fin de lograr la coherencia entre lo planificado, lo evaluado y lo aprendido (Huerta, 2018). El estudio se dividió en dos fases: una de diseño y la otra de validación del modelo, el cual contempla 4 competencias, 3 dimensiones y 10 indicadores, sustentados teóricamente desde una revisión bibliográfica y por un cuestionario aplicado a especialistas.  El modelo de evaluación de los aprendizajes basado en evidencias llamado MEABE, está dirigido a la educación universitaria, sin embargo, puede ser aplicado en otros escenarios educativos.
Sustainability in Inclusive Innovation: District-Community Solutions, Mindsets, and Practices
Authors: Young, Ph.D. Viki M. , Merritt Johnson, Ph.D Alexandra
Published: May 2024

This paper examines the factors that supported sustainability under Inclusive Innovation, an R&D model where students, families, communities, and teachers engage with school and district leaders, researchers, and solution providers to co-research an educational challenge in context and to co-develop solutions to the challenge, with intentional goals to benefit students from historically and systematically excluded communities. Key sustainability factors include garnering buy-in at all levels of the system, iterating to improve implementation, embedding changes in existing structures, and concretely demonstrating the benefits of the solution. In addition, the paper describes the mindsets participants developed and incorporated into their practices as a result of engaging in Inclusive Innovation. These mindsets reflect the Inclusive Innovation Core Tenets of valuing student voice and leadership, context expertise, and pursuing continuity of equity.
Estrategias de comercialización de la miel de abeja melipona y sus derivados en el Estado de Yucatán
Authors: Magaña Magaña Miguel Ángel , Ek Ek José Francisco , Leyva Morales Carlos Enrique
Published: May 2024

Estrategias de comercialización de la miel de abeja melipona y sus derivados en el Estado de Yucatán Resumen La meliponicultura es una actividad de importancia y se práctica desde tiempos prehispánicos, actualmente ésta genera ingresos a las familias rurales a través de la comercialización de la miel y otros productos elaborados. El objetivo de la investigación es identificar y analizar la innovación en los procesos de mercadeo de la miel obtenida en los meliponarios de la región noroeste y poniente de Yucatán, así como caracterizar las estrategias de integración de los productores a los canales de comercialización actuales. La información se obtuvo por medio de una cédula de entrevista semiestructurada, la técnica de muestreo fue la de referidos y el análisis de la información se realizó con base en la estadística descriptiva y correlacional. Se encontró que el principal destino de venta de la miel y sus derivados es la Ciudad de Mérida; la miel se distribuye generalmente en envases de medio litro, carentes de imagen comercial y su precio es muy superior al convencional. La innovación en los procesos de comercialización es la mejor estrategia para el meliponicultor, ya que el posicionamiento de sus productos en los mercados depende del uso de medios digitales y nuevas plataformas de comunicación, indispensables para la creación de redes de distribución.
Maternal Health Risk Prediction Using Machine Learning Methods
Authors: Ibewesi MaryJane Chinyere , Alice Uzuke Chinwendu
Published: May 2024

This work employed machine learning methods – decision tree algorithm, support vector machine (SVM) and logistic regression to predict health risk outcome of pregnant women based on their vital signs. The aim was to determine which of the model most suitable for the prediction of health risk for any pregnant woman. Evaluation of the methods were done using Accuracy, Precision, F1-Score and recall. The results revealed that the Decision tree model achieved the highest accuracy of 0.8669 (86.99%), that indicates correct prediction in 86.99% of the cases. Also, it achieved the highest precision for all the risk categories (high_risk, low_risk and mid_risk) with values (87%, 86% and 75% respectively) implying lower likelihood of false positive predictions for all risk categories. The Decision Tree model appears to be a promising approach for predicting the impact of vital signs on health risk of pregnant mothers. It exhibited high precision, high recall (sensitivity) and a balanced F1-score, suggesting accurate predictions with very low rate of false positives.
Navigating legal pathways: Optimizing energy sustainability through compliance, renewable integration, and maritime efficiency
Authors: Portia Oduro  , Ngozi Samuel Uzougbo  , Munachi Chikodili Ugwu
Published: May 2024

This concept paper explores the intricate interplay between legal frameworks and energy sustainability, focusing on compliance, renewable energy integration, and maritime efficiency. The maritime industry, a significant contributor to global emissions, faces unique challenges and opportunities in transitioning towards sustainability. By examining current legal pathways and best practices, this paper aims to provide insights and recommendations for optimizing energy sustainability in the maritime sector. The concept paper begins by outlining the current regulatory landscape, highlighting key international conventions, regional regulations, and emerging trends shaping the maritime industry's sustainability agenda. It then delves into compliance challenges faced by maritime stakeholders, including regulatory complexities, enforcement issues, and the need for harmonization. The paper also explores the role of renewable energy in maritime sustainability, analyzing successful integration strategies, such as hybrid propulsion systems, wind-assisted propulsion, and shore power solutions. It highlights legal frameworks supporting renewable energy adoption and identifies opportunities for further innovation. Furthermore, the concept paper examines maritime efficiency through legal lenses, discussing measures to improve operational efficiency, reduce emissions, and enhance overall sustainability. It considers the impact of digitalization, automation, and data-driven technologies on maritime operations, emphasizing the need for legal frameworks to adapt to these technological advancements. Based on these analyses, the concept paper proposes recommendations for policymakers, industry stakeholders, and legal practitioners to enhance energy sustainability in the maritime sector. These recommendations include fostering international cooperation, promoting renewable energy investment, and enhancing regulatory clarity and enforcement mechanisms. In conclusion, this concept paper underscores the importance of legal pathways in optimizing energy sustainability in the maritime sector. By embracing compliance, integrating renewable energy, and enhancing efficiency, the maritime industry can transition towards a more sustainable future while navigating the complex legal landscape effectively.
Keywords: Energy, Sustainabiltiy, compliance, Policy, Renewable.
AI-enhanced healthcare management during natural disasters: conceptual insights
Authors: Samira Abdul  , Ehizogie Paul Adeghe  , Bisola Oluwafadekemi Adegoke  , Adebukola Adejumoke Adegoke  , Emem Henry Udedeh
Published: May 2024

Natural disasters often lead to significant disruptions in healthcare delivery, exacerbating the already formidable challenges faced by healthcare systems. Leveraging artificial intelligence (AI) offers a promising approach to mitigate these challenges and enhance healthcare management during and after natural disasters. This conceptual paper aims to propose a framework for the integration of AI into disaster response efforts, with a focus on optimizing resource allocation, improving patient triage, and enhancing overall system resilience.  Through a comprehensive review of existing literature, this paper identifies the gaps in current disaster management practices and explores the potential of AI to address these shortcomings. By analyzing case studies and examples from previous disasters, the paper highlights the transformative impact that AI technologies such as predictive analytics, machine learning, and robotics can have on healthcare delivery in crisis situations. The objectives of this paper are twofold: to define a strategic approach for incorporating AI into disaster response protocols and to outline the expected outcomes of implementing such a framework. Expected benefits include expedited triage processes, more accurate resource allocation, and improved communication systems, ultimately leading to better patient outcomes and enhanced system efficiency. The proposed framework emphasizes the importance of interdisciplinary collaboration between healthcare professionals, technologists, policymakers, and disaster response experts. It also addresses ethical considerations and potential challenges associated with AI implementation in disaster settings. In conclusion, this paper underscores the critical role of AI in bolstering healthcare management capabilities during natural disasters. By leveraging AI technologies, healthcare systems can become more adaptive, responsive, and resilient in the face of unforeseen challenges, ultimately saving lives and minimizing the impact of disasters on communities.
Keywords: AI-Enhanced Healthcare Management, Natural Disasters, Conceptual Insights.
Evaluating the effectiveness of global governance mechanisms in promoting environmental sustainability and international relations
Authors: Uwaga Monica Adanma  , Emmanuel Olurotimi Ogunbiyi
Published: May 2024

This study critically evaluates the effectiveness of global governance mechanisms in promoting environmental sustainability and enhancing international relations. Employing a systematic literature review and content analysis, the research scrutinizes peer-reviewed articles, official reports, and policy documents published between 2010 and 2024. The main objectives were to analyze the role of global governance in environmental sustainability, assess its impact on international relations, and propose strategic recommendations for enhancing governance frameworks. The methodology focused on identifying, selecting, and analyzing relevant literature based on predefined inclusion and exclusion criteria, emphasizing the contributions of multilateral environmental agreements, international organizations, public-private partnerships, and the involvement of civil society and non-governmental organizations. Key findings reveal that while global governance mechanisms have significantly contributed to advancing environmental sustainability goals, challenges related to implementation, compliance, stakeholder engagement, and the integration of technological innovations persist. The study concludes that adaptive governance structures responsive to evolving environmental issues and stakeholder needs are crucial. Strategic recommendations include strengthening legal and institutional frameworks, enhancing stakeholder engagement, promoting public-private partnerships, and leveraging technological advancements. Directions for future research emphasize exploring the impact of emerging global challenges and investigating the role of non-traditional actors in shaping environmental policies.
Keywords:  Global Governance, Environmental Sustainability, International Relations, Systematic Literature Review.
Renewable energy expansion: Legal strategies for overcoming regulatory barriers and promoting innovation
Authors: Portia Oduro  , Ngozi Samuel Uzougbo  , Munachi Chikodili Ugwu
Published: May 2024

The expansion of renewable energy sources is pivotal in mitigating climate change and transitioning towards a sustainable energy future. However, the realization of this transition faces numerous regulatory barriers that impede the deployment and integration of renewable energy technologies. This abstract explores the legal strategies essential for overcoming these barriers and promoting innovation in renewable energy expansion. Regulatory hurdles often stem from outdated policies, complex permitting processes, and conflicting regulations at various governmental levels. Moreover, legal uncertainties surrounding property rights, land use, and interconnection standards pose significant challenges to renewable energy developers and investors. To address these barriers, legal frameworks must evolve to accommodate the unique characteristics and requirements of renewable energy projects. Effective legal strategies encompass a range of interventions, including streamlining permitting procedures, harmonizing regulations across jurisdictions, and providing clarity on legal and contractual frameworks. Furthermore, innovative policy mechanisms such as feed-in tariffs, renewable portfolio standards, and tax incentives can incentivize renewable energy deployment while ensuring regulatory compliance. Promoting innovation in renewable energy expansion requires a proactive approach to legal and regulatory reform. This involves fostering collaboration between policymakers, industry stakeholders, and legal experts to identify regulatory bottlenecks and develop tailored solutions. Additionally, flexible regulatory frameworks that allow for experimentation and adaptation to technological advancements are essential for driving innovation in the renewable energy sector. Case studies from various jurisdictions illustrate successful legal strategies employed to overcome regulatory barriers and promote innovation in renewable energy expansion. These examples highlight the importance of proactive policy interventions, stakeholder engagement, and adaptive governance structures in facilitating the transition to a renewable energy economy. In conclusion, overcoming regulatory barriers and promoting innovation in renewable energy expansion requires a multifaceted approach that combines legal, policy, and technological solutions. By adopting proactive legal strategies, policymakers can create an enabling environment that fosters renewable energy deployment, accelerates innovation, and advances the transition towards a sustainable energy future.
Keywords: Legal Strategies, Promoting Innovation, Regulatory Barriers, Renewable Energy, Overcoming.
Utilizing machine learning to predict employee turnover in high-stress sectors
Authors: Kudirat Bukola Adeusi  , Prisca Amajuoyi  , Lucky Bamidele Benjami
Published: May 2024

This study investigates the application of machine learning techniques to predict employee turnover in high-stress sectors. The primary objective is to enhance retention strategies by accurately identifying potential turnover risks. The research utilizes a comprehensive dataset comprising various factors, including employee demographics, job satisfaction, performance metrics, and stress levels. Multiple machine learning algorithms, such as logistic regression, decision trees, random forests, and neural networks, are employed to build predictive models.
The methodology involves data preprocessing, feature selection, model training, and evaluation. Cross-validation and hyper parameter tuning are performed to ensure the robustness and accuracy of the models. The performance of each algorithm is assessed using metrics such as accuracy, precision, recall, and the area under the receiver operating characteristic curve (AUC-ROC).
Key findings reveal that machine learning models can effectively predict employee turnover, with random forests and neural networks demonstrating superior performance. Significant predictors of turnover include job satisfaction, stress levels, and performance ratings. The study concludes that integrating machine learning models into human resource practices can provide valuable insights for preemptive interventions, ultimately reducing turnover rates in high-stress environments.
Future research should explore the integration of real-time data and the potential of deep learning techniques to further enhance predictive accuracy. Additionally, the ethical implications of using predictive models in HR decisions warrant careful consideration to ensure fairness and transparency.
Keywords:  Machine Learning (ML), Employee Turnover, Predictive Analytics, Human Resources (HR), High-Stress Sectors, Decision Trees, Random Forests, Extreme Gradient Boosting (XGBoost), Personalized Retention Strategies, Business Intelligence (BI) Tools, Data Quality, Ethical Considerations, Data Privacy, Natural Language Processing (NLP), Deep Learning, Real-time Data Analysis, Employee Engagement, Work-Life Balance, Organizational Performance, Data-Driven Insights.
A review of the challenges and opportunities in implementing health informatics in rural healthcare settings
Authors: Samira Abdul  , Ehizogie Paul Adeghe  , Bisola Oluwafadekemi Adegoke  , Adebukola Adejumoke Adegoke  , Emem Henry Udedeh
Published: May 2024

This paper reviews the challenges and opportunities associated with implementing health informatics in rural healthcare settings. It examines the unique barriers rural communities face, such as infrastructure limitations, workforce shortages, and financial constraints, which can impede the adoption and utilization of health informatics solutions. However, it also explores the promising opportunities afforded by health informatics, including telemedicine, electronic health records (EHRs), and mobile health technologies, to overcome these challenges and improve healthcare access, quality, and efficiency in rural areas. By addressing these challenges and leveraging the opportunities presented by health informatics, stakeholders can work towards achieving equitable healthcare outcomes for rural populations. By addressing these challenges and leveraging the opportunities presented by health informatics, stakeholders can work towards achieving equitable healthcare outcomes for rural populations. Health informatics holds immense potential to revolutionize healthcare delivery, particularly in rural settings where access to quality care is often limited Health informatics holds immense potential to revolutionize healthcare delivery, particularly in rural settings where access to quality care is often limited. Health informatics holds immense potential to revolutionize healthcare delivery, particularly in rural settings where access to quality care is often limited. Telemedicine, for instance, enables remote consultations and diagnostic services, breaking down geographic barriers and providing rural patients with access to specialists and healthcare expertise they may not have locally. Electronic Health Records (EHRs) streamline administrative processes, improve care coordination, and enhance patient safety by ensuring that vital health information is readily accessible to healthcare providers regardless of location. Mobile health technologies, including smartp hone apps and wearable devices, empower rural residents to monitor their health, track chronic conditions, and engage in self-management activities from the comfort of their homes.By embracing these innovations and overcoming infrastructure challenges, stakeholders in rural healthcare can significantly improve healthcare access, quality, and efficiency. Additionally, leveraging health informatics can help address workforce shortages by enabling healthcare providers to deliver more effective and integrated care, even in remote areas. Ultimately, by harnessing the opportunities presented by health informatics while addressing the unique challenges of rural healthcare, stakeholders can work towards achieving equitable healthcare outcomes for rural populations.
Keywords:  Health Informatics, Rural Healthcare, Electronic Health Records (EHRS), Mobile Health, Challenges.