bluuebunny/crossref_metadata_2025 huggingface dataset:
PVC Mesh as Adaptable Recycled Textile Waste towards Innovative Tropical Building Façade
Authors: Ali Ariff Azlan Ariff , Mazdi Muhammad Zharfan , Ilagan Ana Paula Delos Santos , Shafie Nur Zawani
Published: December 2023

Textile fibres are commodity materials that society will continue to use in large quantities for various applications yet also generate massive waste. Through coating application, upcycled textile waste has significant potential in building construction. The purpose of this study is to demonstrate the usage of PVC mesh textile waste as a novel textile facade for Malaysian structures. Content analysis is used to analyse various textile façade constructions that perform architectural tasks. The overall conclusion found that PVC mesh covers all features in balance as a creative building façade that responds to the needs of the Malaysian tropical climate.
Conjunctions of Correlation in the National Print Media
Authors: Noviatri Noviatri , Reniwati Reniwati
Published: December 2023

This study aims to describe form and meaning through correlative conjunctions in the national print media. The data are collected by the method of observation. Next, the data are analyzed by using the distribution method and the observation method. Indeed, the study indicated 7 forms of correlative conjunctions, namely correlative conjunctions  tidak hanya-tetapi juga ‘not only-but also’, tidak hanya-namun,  tidak hanya-melainkan, bukan hanya-melainkan, bukan hanya-tetapi ‘not only-but’, baik-maupun ‘neither-nor’, baik-ataupun ‘either-or’. Some of them are not following with the standard form of conjunctions. Regarding affinity, there are are four  affinities for correlative conjunctions, namely 'affirmation', 'more', 'emphasis, ‘comparison', and 'place'.
Function of Self-mention Markers in an Accountancy Conference
Authors: Fauzanna Wulan , T’Chiang Chow Ung , Hashim Azirah
Published: December 2023

This study analyzed presentations made by professionals as part of the development programs to enhance the skills and competencies of Accountants. The presentations at the ASEAN Federation of Accountants (AFA) conference were selected and audio-recorded. The data were then transcribed and documented in a 29 800-word file. Wordsmith tools (Scott, 2020) were used to analyze data. This study focused on using interpersonal metadiscourse markers (Hyland, 2005), particularly Self-- mention as a presentation strategy. The findings showed that ‘I’ and ‘we’ were the dominant Self-mentions in the presentations. They are used as referents for inclusivity and to highlight the presenter's perspectives.
Socio-Economic History of the Mentawai Islands in West Sumatra Province
Authors: Bagindo Muhammad Nur , Chaniago Maizufri Ilyas , Herwandi Herwandi , Saga Syafrizal Sirin , Hussin Hanafi
Published: December 2023

This study describes the socio-economic history of the population in the Mentawai Islands Regency, West Sumatra, Indonesia. Residents of the area engage in different socio-economic activities. The purpose of this study is to explain the socio-economic life of the majority in agriculture. The research methods used are historical methods, for example, heuristics, criticism, interpretation, and historiography. Mentawai Island residents have been active in the world of agriculture and plantations since the 16th century. At the time when Dutch traders arrived there, the Mentawai Islands were already in contact with ethnic groups who came from the west coast of Sumatra and the surrounding islands.
Innovation on Cultural and Creative Product–Designing Traditional Chinese Poetry into Product
Authors: Xuemin You , Legino Rafeah , Xiao Pan
Published: December 2023

The cultural and creative (CAC) industries have experienced rapid growth in recent years, and "Culture" plays a critical role in design. Traditional Chinese poetry is an intangible cultural heritage in China's civilisation. Therefore, designing "Traditional Chinese Poetry" into products will be a CAC product design trend. This study investigates how to transform Traditional Chinese Poetry elements into CAC products with an innovative design model. Through the design practice, participants have successfully designed CAC products based on ancient poetry elements. Moreover, there still needs to be more research on the cultural product design of the intangible traditional culture in China.
A Comparison of the Motifs on Kuala Terengganu Block Batik Sarong
Authors: Legino Rafeah , Zuhir Nikfarhana , Samin Mohd Azhar , Suminto Sekartaji
Published: December 2023

This investigation delves into the art of traditional batik sarongs through the batik block method, with a specific focus on Mokhtar and Ibrahim batik from Kuala Terengganu, emphasising the structural elements of ornamental patterns. Concentrating on Kuala Terengganu, a comparative analysis is necessary to determine the similarities and distinctions in thematic content. While commonalities exist, deliberate processing variations augment and diversify existing embellishments, fostering the evolution of this traditional art form. Therefore, this study adds a lot to our understanding of the complex methods and nuanced approaches used to make batik sarongs, showing how this culturally important tradition is always changing.
Visual Communication in Sustainability Action: Public understanding through human behavior and attitude
Authors: Mohd Muslim Tan Ellyana , Michael Valerie Anak , Hassan Muhamad Hafiz , Abu Bakar Muhammad Fauzan
Published: December 2023

The study aims to explore the essential elements of an idea in designing visual marketing, advertising, or design developments to impose sustainable efforts. The final data is distributed into four categories: Behavior and Attitude in Visual Development, Mechanism in Public Information, Process of Public Understanding, and Public Understanding in Visual Sustainability. The research suggests creators of visual communications consider how their work shapes attitudes and behaviours about sustainability. With awareness around information, public understanding, and connections between visual media and sustainability, designers can promote responsible, eco-conscious messages. This framework proposes the development process should cultivate mindfulness about communicating sustainability effectively.
Styling Concept In Fashion Photography Process
Authors: Md Khaled Afendi Md Shas , Mohd Sharif Nadzri , Jifei Cheng
Published: December 2023

This study aims to investigate and analyse the production process of fashion photography. Fashion photography is a subset of commercial photography that conveys a product's identity and seeks to attract consumers for marketing and public information purposes. Photography techniques and graphic approaches corresponding to the session's theme and concept can significantly influence and captivate the audience. This study's findings will provide new insights and creative ideas for module development in fashion photography. Conclusion: The findings of this study have the potential to impact the direction of high-quality style and fashion photography, as well as the method by which photography professionals can improve their skills and work efficiency.
Attitudinal Stance towards COVID-19 Pandemic: An appraisal analysis of the Jakarta Post editorials
Authors: Suraiya Lucy , Mohd Nor Nor Fariza , Shaari Azianura Hani
Published: December 2023

This study examines the attitudinal stance of The Jakarta Post editorials about COVID-19 by applying Martin and White's appraisal system. The analysis of fifty editorial texts indicated that 70 % of negative assessments towards the government exceeded the positive ones. The illustrative judgment realisations for negative assessments are depicted by condemning government behaviour due to the government's failure in public communication, inconsistency in social distancing regulation, prioritisation of the economy over health, and mismanagement of social aid. The study suggests that the Indonesian government may learn from the negative judgments and cope with the uncertainties for projecting future COVID-19 risks.
Variations of Food in Traditional Muslim Ceremonies in Minangkabau Isolect, Indonesia
Authors: Nadra Nadra
Published: December 2023

This study describes the variations of food in Minangkabau’s isolect that are commonly used in traditional Muslim ceremonies. Informal discussion and observation were conducted using various techniques on selected ceremonies. Five distinct traditional Muslim ceremonies are found in this study. Furthermore, the result discovered that there are nine foods for dishes and vegetables, eleven items for snacks, three items for drinks and one item for fruit. This included the foods that were classified into one, two, and three lexicons. Overall, it may be concluded that food variations always occur in every traditional Muslim ceremony.
Digital Touchpoints and their Influence on Customer Preference for the B2B Market
Authors: Haron Hazliza , Abd Rahman Azalia , Hajemi Afiza , Hasnan Nor Syafiqah , Fatima Johra Kayeser
Published: December 2023

Many B2B companies have invested in transformation technology, enhancing their digital marketing strategies. This study investigates digital marketing website touchpoints and explores their influence on customer preference in online transactions. The investigation proceeded with convenience sampling, and 311 electronic manufacturers participated in this online survey. Six variables were tested and analyzed using SPSS regression analysis. Three significant variables are visual appearance, ease of use, and order fulfillment. This study contributes to both theoretical and practical implications of digital marketing practice by B2Bs, especially decisions on the features to be implemented on their current website to enhance their marketing practices further.
Low-Cost Webcam Camera and GNSS Integration for Updating Home Data using AI Principles
Authors: Handayani Hepi Hapsari , Cahyadi Mokhamad Nur , Raharjo Agus Budi , Haq Failaqul
Published: December 2023

PDAM Surya Sembada Surabaya City responds to Surabaya's water service demand by pioneering a cost-effective mobile mapping tech. This innovation integrates 3 MP webcams, GNSS, and IMU sensors to update customer building data efficiently. Precise photo data with location and movement info within 1-meter proximity captures accurate building coordinates. Applying georeferencing and Cosine Similarity reduces redundant data by 50%. GNSS, IMU sensors, and VGG-16 model aid data collection and analysis. This comprehensive approach optimizes PDAM Surabaya's operations, ensuring timely and accurate customer updates amid Surabaya's population growth, promising enhanced service delivery while managing costs.
Impact of using Modern Technology in Preserving Traditional Stories
Authors: Gayatri Satya , Pratiwi Dyani Prades , Legino Rafeah , Yuhandri Yuhandri , Rahayu Rita
Published: December 2023

Many traditional Minangkabau stories are lost from the community (Minangkabau people). Creativity is required to make this cultural asset survive. One of the methods is using technology as a tool to preserve the stories. Traditional stories survive and are still enjoyed today because they have been transformed into various forms and taken advantage of by technological advances. However, some positive and negative impacts affect the existence and development of the story. This article will describe the positive and negative effects of using technology on traditional stories and their society. The data were obtained from literary studies and field studies.
Low-Cost LiDAR-GNSS-UAV Technology Development for PT Garam’s Three-Dimensional Stockpile Modelling Needs
Authors: Imani Daud , Cahyadi Mokhamad Nur , Farid Imam Wahyu , Mardianto Ronny
Published: December 2023

Unmanned Aerial Vehicles (UAV), Global Navigation Satellite Systems (GNSS), and LiDAR will be combined into one of the newest technologies to cover each other's deficiencies. Surveyors can use UAV, GNSS, and LiDAR multi-sensors to map the stockpile of salt PT Garam, whereas the previous process used manual calculations. LiDAR is a survey tool with a low price, around 999 USD. To minimise operational costs, surveyors can use Low-Cost LiDAR, GNSS, and UAV at around 638 USD. The results of the data obtained are calibrated with pitch, roll, and yaw to get the vertical height of the existing contours.
Post-pandemic Behavioral Trends of School Dropouts
Authors: Mohammad Faisal Nurfarah Najwa , Megat Abdul Rahim Puteri Rohani , Mohd Thuraiya , Kaeni Nor Faizah
Published: December 2023

The widespread of Covid-19 had caused a massive disruption towards education sector. The instant transition and challenges faced by students during the pandemic led to changes in their behaviour and an increment in drop out. This study aims to identify post-pandemic behavioural trends among secondary school students. A qualitative case study utilising interview involving counsellors, at-risk students from 5 schools and documents on dropout-related obtained from systematic literature review were employed.  This study will assist school and educators in determining the crucial elements contributing to student dropout so that they can better serve at-risk students by recognising the behavioural trends.
Retirement Planning among Female Workforce in Malaysia and China
Authors: Yuan Jing , Chong Kim Mee , Hii Ivy Siaw Hung , Li Hao Lun
Published: December 2023

A phenomenon has emerged whereby the life expectancy of women is 74.2 years, and men's is 69.8 years. Hence, it is crucial to encourage early retirement planning among women.  This study aims to explore the factors that influence retirement planning awareness and readiness among women in Malaysia and China. A self-administered online questionnaire was completed by 100 Malaysians and 200 Chinese. Using IBM SPSS and SmartPLS, the determinants examined the moderating effect of self-efficacy towards retirement readiness. This study will provide valuable insights for policymakers to adopt better strategies to address women's issues and improve their quality of life.
Redefining Virtual Assistants in Health Care: The Future With Large Language Models (Preprint)
Authors: Sezgin Emre
Published: December 2023

UNSTRUCTURED

This editorial explores the evolving and transformative role of large language models (LLMs) in enhancing the capabilities of virtual assistants (VAs) in the health care domain, highlighting recent research on the performance of VAs and LLMs in health care information sharing. Focusing on recent research, this editorial unveils the marked improvement in the accuracy and clinical relevance of responses from LLMs, such as GPT-4, compared to current VAs, especially in addressing complex health care inquiries, like those related to postpartum depression. The improved accuracy and clinical relevance with LLMs mark a paradigm shift in digital health tools and VAs. Furthermore, such LLM applications have the potential to dynamically adapt and be integrated into existing VA platforms, offering cost-effective, scalable, and inclusive solutions. These suggest a significant increase in the applicable range of VA applications, as well as the increased value, risk, and impact in health care, moving toward more personalized digital health ecosystems. However, alongside these advancements, it is necessary to develop and adhere to ethical guidelines, regulatory frameworks, governance principles, and privacy and safety measures. We need a robust interdisciplinary collaboration to navigate the complexities of safely and effectively integrating LLMs into health care applications, ensuring that these emerging technologies align with the diverse needs and ethical considerations of the health care domain.
Fostering positive public sentiments during pandemic outbreaks: Evidence from Weibo posts in China (Preprint)
Authors: Wang Tianyu , Yue Wenze , Zhang Xiaoling , Zhuo Hejia , Fan Peilei , Wei Jingxian
Published: December 2023

BACKGROUND

Since the 20th century, the world has witnessed increasingly frequent pandemics, with new viruses outpacing human knowledge. Beyond the lethality of the virus itself, there is growing consensus that its associated psychological distress can be deadlier for most of the public.

OBJECTIVE

This study aimed to elucidate the affective trajectories observed among the populace in China and ascertain the degree to which governmental policy frameworks influence public mental health during an outbreak.

METHODS

To achieve this, an analysis encompassing 182,335 Weibo posts related to COVID-19, comprising original compositions and shared blogs, disseminated between January 1 and May 31, 2020, across 13 Chinese cities, was conducted. The bidirectional long short-term memory (Bi-LSTM) deep learning semantic model was deployed to discern the prevailing emotional tendencies manifest in these Weibo posts.

RESULTS

One significant observation is the notable upswing in positive public sentiment observed during the acute crisis phase, aligning with the extensive implementation of strict community quarantines across diverse regions in China. In light of these remarkable findings, our analysis discloses that individuals’ fears regarding the virus and the detrimental consequences of quarantine measures experienced a considerable alleviation due to the rapid and well-coordinated COVID-19 response regime.

CONCLUSIONS

The policy framework characterized by shared objectives, robust institutional cohesion, and widespread social mobilization notably influenced and molded positive public attitudes toward the COVID-19 pandemic.
E-Learning Platforms: A Bibliometric Review of Current Status and Future Developments
Authors: Singh Sourav , Yadav Indresh , Bhalaria Mohit , Monika
Published: December 2023

Abstract: Online education is vital, offering flexibility for learners. However, ensuring active participation and positive outcomes in online learning is complex. This review paper assesses strategies to enhance online education. We explore innovative instructional designs, interactive technologies, and adaptive pedagogical approaches. Building a sense of community through collaboration and effective communication is emphasized. We investigate the impact of learner support systems, such as tutoring, timely feedback, and personalized learning paths. Data analytics and learning management systems are discussed for their role in customized learning. Challenges, including the digital divide and privacy issues, are addressed. The review also considers integrating emerging technologies. This analysis provides educators and policymakers with insights to create a more effective online education landscape.
Coronary Artery Disease Prediction: A Systematic Review
Authors: Patil Vipul , Jagtap Mayur , Bhoje Nikhil , Sangve Dr. Sunil
Published: December 2023

Abstract: Coronary artery disease (CAD) continues to be the primary cause of mortality and chronic impairment in cardiovascular illnesses around the globe, hence coronary artery disease prediction is becoming more important in today's society. As we know, more individuals died as a result of late detection of cardiac disease, thus anticipating it in the early stages is critical. As there are more techniques to predict heart disease but, they are either time consuming or more expensive. So, our goal is to create a system that can predict the outcome fast, cheaply, and more precisely from our house, from our smart phone camera. We know that facial recognition plays a significant part in human-computer interaction, thus we want to integrate this approach with the medical profession in order to anticipate a condition that contributes significantly to the world population's mortality rate. The goal of this review paper is to compare these approaches to the current state-of-the-art and to discuss the challenges that must be addressed. It also includes recommendations for further study.
Credit Score Prediction
Authors: Balaji Krishna , Gupta Aashima , Goswami Shristy
Published: December 2023

Abstract: A credit score is the numerical representation of a person’s credit worthiness, which is the likelihood that they will replay the borrowed money. Credit scores are used by lenders, such as banks and credit companies, to evaluate the risk of lending money or extending credit to an individual. Machine learning (ML) is the scientific study of algorithms and statistical models that computer systems use to perform a specific task without being explicitly programmed. Learning algorithms in many applications that we make use of daily. These algorithms are used for various purposes like data mining, image processing, predictive analytics, etc. to name a few. The main advantage of using machine learning is that, once an algorithm learns what to do with data, it can do its work automatically. Various algorithms used in machine learning, along with their drawbacks and usages, have been discussed briefly. A model is also made using one of these algorithms which provide minimum error of provide correct predictions based on the previous data available. The model is made using random forest classifier algorithm which gave the highest accuracy ,out of all the machine learning algorithm, up to 79.97%. The result was printed at last containing the predictions made on the test data , id and customer id.
Alpha Logarithm Transformed Half Logistic Distribution: Properties and Applications
Authors: Rao I. Narasimha , Lakshmi M. Vijaya , Anjaneyulu G. V. S. R
Published: December 2023

Abstract: In this paper, we introduce a new two parameter Alpha Logarithm Transformed Half Logistic (ALTHL) distribution. A new method has been proposed to introduce an extra parameter to a family of distributions for more flexibility .The proposed family may be named as Alpha Logarithm Transformed Half Logistic. This can be obtained via reparameterizing the exponentiated Kumaraswamy G-logarithmic family and the alpha logarithmic family of distributions. The recommended distribution reveals increasing, decreasing and bath-shaped probability Density, Distribution and Hazard rate function and Survival function. Some distributional properties of new model are investigated which include the Density Function, Distribution Function (DF), Quantile Function(QF), Moments, Moment Generating Function (MGF), Cumulative Generating Function (CGF).
Challenges and Solutions in Integrating AI with Legacy Inventory Systems
Authors: Singh Navdeep , Adhikari Daisy
Published: December 2023

Abstract: This paper delves into the intricate process of integrating Artificial Intelligence (AI) into legacy inventory systems, a critical challenge in the realm of modern inventory management. It presents a comprehensive analysis, exploring the multifaceted barriers encountered in this integration, particularly in traditional industries. The study identifies and examines key technical, organizational, and financial challenges, offering a nuanced understanding of the complexities involved. Innovative solutions and strategies are proposed to address these challenges, drawing on a rich array of existing literature and real-world case studies. The paper highlights successful integrations of AI in various sectors, extracting valuable lessons and best practices. It contributes significantly to the existing body of knowledge by bridging theoretical research with practical applications, providing insights that are both profound and actionable. This research not only illuminates the path forward for traditional industries seeking to embrace AI in inventory management but also serves as a valuable resource for practitioners and researchers in the field. The findings and strategies outlined in this study offer a roadmap for successful AI integration, marking a pivotal step in the evolution of inventory management practices.
Shope House
Authors: Khan Mohd Amaan , Khan Sahil , Mohammad Faiz
Published: December 2023

Abstract: A Shop House System for Web Applications in the Automotive Industry: Enabling Seamless Collaboration between Buyers and Automotive Companies In the rapidly evolving landscape of the Automotive industry, the integration of web applications has become instrumental in facilitating efficient communication and transactions between buyers and Automotive companies. This research paper explores the design, development, and implementation of a robust Shop House system tailored for a web application in the Automotive sector. The proposed Automotive system serves as a pivotal tool for both buyers and Automotive entities, fostering seamless interactions, streamlined processes, and an enhanced user experience
Cyber Security Challanges for Online Trading
Authors: Tiwari Himanshu , Kumar Alok
Published: December 2023

bstract: Today Security is a fundamental component in the computing and networking technology. The first and foremost thing of every network designing, planning, building, and operating a network is the importance of a strong security policy. Network security has become more important to personal computer users, organizations, and the military. With the advent of the internet, security became a major concern. The internet structure itself allowed for many security threats to occur. Online trading facilitates as a financial platform form for buying and selling shares, bidding, product sale or purchase using computers. The vital online trading between B2B, B2C and C2C transaction data may be under siege due to spywares, malwares, Hijackers and intruders. Often trading secrets and portfolios are in risk with network attackers who tracks unauthorizedly the personalized data of business clients. Cyber security is the practice of defending computers, servers, mobile devices, electronic systems, networks, and data from malicious attacks. It's also known as information technology security or electronic information security. The term applies in a variety of contexts, from business to mobile computing, and can be divided into a few common categories.
IOT based Soldier Health Monitoring and Position Tracking System
Authors: Gaikwad Prof. Jitendra , Tele Rushikesh , Sawant Sanket , Nichit Pratik , Sambare Ajinkya , Rathod Gurupreetsingh
Published: December 2023

Abstract: An Internet of Things-based system for tracking a soldier's position and health during combat operations is one technological advancement that makes it possible to monitor a soldier's whereabouts and health in real time. The system goals are to protect soldiers and improve their effectiveness in combat. The system utilizes various sensors and devices such as heart rate monitors, temperature sensors, GPS, and accelerometers to gather data on the soldier’s vital signs and movements. This data is then transmitted wirelessly to a central monitoring system, which analyzes it and provides real-time feedback to the commanding officers. By monitoring soldier’s vital signs, the system can quickly identify any health issues that may arise, such as fatigue or dehydration, and alert the appropriate medical personnel. The system also tracks soldier’s positions and movements, allowing commanders to make informed decisions about deployment and resource allocation. All things considered, a position tracking and health monitoring system for soldiers based on the Internet of Things is a useful instrument for ensuring their safety and wellbeing in combat
Análisis químico y biológico de biosólidos sometidos a sistema de lombricultura como potencial abono orgánico
Authors: Chávez Porras PhD Álvaro , Rodríguez González Alejandra
Published: December 2023

Uno de los principales problemas en las plantas de tratamiento de aguas residuales –PTAR- es la cantidad de residuos que generan, estos conocidos como biosólidos tienen potencial como materias primas en industrias de producción de abonos orgánicos siempre y cuando se establezca su composición química y biológica, permitiendo su uso. Este proyecto realizó un análisis del biosólido de la PTAR Salitre de Bogotá D.C., el cual se clasifico cómo tipo B, según las referencias bibliográfica, ya que el país no ha definido una legislación del tema. El proceso de lombricultura se realizó con la especie Eiseniafoétida. Las pruebas químicas relevantes fueron: cantidad de N - P – K; elementos menores (Mn, Fe, Zn y Cu); materia orgánica (% C) y otros elementos (Cr, Cd y Pb). A nivel bilógico se efectuó el análisis de germinación y la cuantificación de hongos, bacterias, fijadores de nitrógeno y coliformes. Como conclusión se establece que el proceso de lombricultura podría ser una iniciativa ecológica para el manejo de biosólidos de las PTAR, ya que estos presentaran características de abonos orgánicos, los cuales pueden ser usados para cultivos no agrícolas de tipo ornamental y recuperación forestal.
Análisis correlacional del perfil de dominancia cerebral de estudiantes de ciencias de la salud y estudiantes de ciencias sociales de la Universidad Colegio Mayor de Cundinamarca
Authors: Velásquez Burgos Bertha Marlene , Remolina de Cleves Nahyr , Calle Márquez María Graciela
Published: December 2023

El presente artículo explicita los resultados correspondientes al análisis correlacional de los perfiles de dominancia cerebral o estilos de pensamiento de los estudiantes de Ciencias de la Salud y Ciencias Sociales de la UCMC, los cuales forman parte del proyecto conjunto Representaciones, organización conceptual y estilos de pensamiento, en el marco del Convenio de Cooperación Académica IISUE-UNAM (México) y La UCMC, Bogotá-Colombia, liderado por el Dr. Miguel Ángel Campos Hernández. Lo anterior tomando como base el modelo de Cerebro Total de Herrmann y los estudios recientes de Omar Gardié.Los estudiantes de Ciencias de la Salud presentan mayor preferencia de los cuadrantes cortical izquierdo y límbico izquierdo A-B; es decir, tienen predilección por el hemisferio izquierdo. Los estudiantes de Ciencias Sociales presentan mayor predisposición en los cuadrantes límbico izquierdoy límbico derecho B-C; es decir, tienen mayor tendencia por el sistema límbico. Con los resultados de esta investigación se verificó la hipótesis en torno de la escasa utilización de las posibilidades creativas y del desarrollo del cerebro total de los grupos sometidos a estudio. De igual modo, se identificó la manera como los perfiles de dominancia de los estudiantes se relacionan con las disciplinas que han seleccionado en su formación.
Chapter 1 INTRODUCTION
Authors: Acharya Kamal
Published: December 2023

The ”Student Information Management System” is prepared or operates to maintain the records of student in school as well as in college. Student Information Management System deals with the all the activities done by computers such as registration admission process online , and staff and class management etc all these process are handled by the computer management system. The student record can be maintained online for the distance accessible to the entire student and their parents. Without the student management system managing and maintaining the details student is tedious job for any organization. Student information system will store all the detailed of the students including their background information, educational qualifications, Personal details and all the information related to their resume. Suppose we have 1000 of student from this we have to search a particular student we know the name of the student. In a manual system it is a tedious task through we know the name of student but using the module we can easily search the student by specifying the name of student in the search criteria. Thus module will help the administrator in searching the student with the various criteria. This student management system also contained the registration module and account management. This module will help the student get registered from anywhere if the internet is present. This module really simplifies the works on paper registration. Also after successful registration the user can update information and changed their password as when required This student management system also contained the user module. This module will help administrator enabling and disable a user account and change their password when they required.
Sensitive response of atmospheric oxidative capacity to the uncertainty in the emissions of nitric oxide (NO) from soils in Amazonia
Authors: Lee Ben H. , Munger J. William , Wofsy Steven C. C. , Rizzo Luciana V , Yoon James Y. S. , Turner Alex , Thornton Joel A , Swann Abigail L.S.
Published: December 2023

Soils are a major source of nitrogen oxides, which in the atmosphere
help govern its oxidative capacity. Thus the response of soil nitric
oxide (NO) emissions to forcings such as warming or forest loss has a
meaningful impact on global atmospheric chemistry. We find that the soil
emission rate of NO in Amazonia from a common inventory is biased low by
at least an order of magnitude in comparison to tower-based
observations. Accounting for this regional bias decreases the modeled
global methane lifetime by 1.4% to 2.6%. In comparison, a fully
deforested Amazonia, representing a 37% decrease in global emissions of
isoprene, decreases methane lifetime by at most 4.6%, highlighting the
sensitive response of oxidation rates to changes in emissions of NO
compared to those of terpenes. Our results demonstrate that improving
our understanding of soil NO emissions will yield a more accurate
representation of atmospheric oxidative capacity.
Adjoint inversion of near-field pressure gauge recordings for rapid and accurate tsunami source characterization
Authors: Xie Yuqing , Mohanna Saeed , Meng Lingsen , Zhou Tong , Ho Tung-Cheng
Published: December 2023

We explore the potential of the adjoint-state tsunami inversion method
for rapid and accurate near-field tsunami source characterization using
S-net, an array of ocean bottom pressure gauges. Compared to
earthquake-based methods, this method can obtain more accurate
predictions for the initial water elevation of the tsunami source,
including potential secondary sources, leading to accurate water height
and wave run-up predictions. Unlike finite-fault tsunami source
inversions, the adjoint method achieves high-resolution results without
requiring densely gridded Green’s functions, reducing computation time.
However, optimal results require a dense instrument network with
sufficient azimuthal coverage. S-net meets these requirements and
reduces data collection time, facilitating the inversion and timely
issuance of tsunami warnings. Since the method has not yet been applied
to dense, near-field data, we test it on synthetic waveforms of the 2011
Mw 9.0 Tohoku earthquake and tsunami, including triggered secondary
sources. The results indicate that with a static source model without
noise, using the first 5 minutes of the waveforms yields a favorable
performance with an average accuracy score of 93%, and the largest
error of predicted wave amplitudes ranges between -5.6 to 1.9 meters.
Using the first 20 mins, secondary sources were clearly resolved. We
also demonstrate the method’s applicability using S-net recordings of
the 2016 Mw 6.9 Fukushima earthquake. The findings suggest that
lower-magnitude events require a longer waveform duration for accurate
adjoint inversion. Moreover, the estimated stress drop obtained from
inverting our obtained tsunami source, assuming uniform slip, aligns
with estimations from recent studies.
The Role of Entertainment in Changing Social Climate Norms
Authors: Coren Emily , Tiwathia Anirudh
Published: December 2023

Storytelling is a powerful tool for supporting climate literacy. Media can reflect the changes that communities are already making and connect viewers to resources for participating in climate action. This summary provides a touch point for what is currently ongoing in Hollywood as a growing community of practice to include climate mitigation and adaptation information within scripted mainstream media, provide an overview of current challenges, and present suggestions for future work to integrate commercial media into the ecosystem of informal climate education. The new Climate Literacy Guide developed by the U.S. Global Change Research Program can help shape the next decade of storytelling as we build capacity for climate change communication.
Urbanisme tactique : de l'action temporaire à la régénération urbaine durable
Authors: kilani Bochra hadj
Published: December 2023

L’urbanisme tactique propose des approches de planification alternatives
aux méthodes traditionnelles de conception urbaine. Axés sur la
satisfaction des besoins des utilisateurs et la résolution des problèmes
socio-urbains, ces projets utilisent des méthodes inclusives,
intuitives, collaboratives, expérimentales et sensibles pour aborder la
ville. Essentiellement, ces projets “ascendants” inspirent une
nouvelle façon de penser la ville en construisant de nouvelles valeurs
urbaines collectives. Cette analyse documentaire synthétise diverses
perspectives sur l’urbanisme tactique, en explorant sa nature
adaptative, son rôle de catalyseur économique, sa dimension
d’autonomisation sociale, l’influence narrative des médias et son
applicabilité à l’échelle mondiale. Collectivement, ces dimensions
décrivent l’urbanisme tactique comme une force à multiples facettes qui
façonne les aspects économiques, sociaux et culturels du développement
urbain.
GC21M-1096: Is Parameter Inference a Disappearing Practice? Comparing Photosynthesis Simulations Using Perturbed Parameter Ensembles and Machine Learning
Authors: Massoud Elias , Hoffman Forrest M , Collier Nathan , Walker Anthony , Sharma Bharat
Published: December 2023

The increase in computational power and richness of Earth system data
has allowed new methods for simulating natural processes with higher
precision and accuracy than previously imagined. Older methods to
increase skill of computer model simulations include parameter
inference, where the parameters of a forward simulation model are
optimized to better represent reality and allow the model to capture
dynamics seen in the observed data. However, these methods are limited
by our physical understanding of the underlying system, making it
impossible to capture certain dynamics when the model is
under-represented. Machine learning methods have emerged as a potential
tool to bypass the limitations of our physical understanding, and they
can create simulations with much higher skill than previous methods.
This work investigates and compares the skill of photosynthesis
simulations from various model formulations including those with
optimized parameters and those from machine learning.
Several mechanisms drive the heterogeneity in browning across a boreal stream network
Authors: Zhu Xudan , Berninger Frank , Chen Liang , Larson Johannes , Sponseller Ryan , Laudon Hjalmar
Published: December 2023

Increases in dissolved organic carbon (DOC) have occurred in many
freshwaters across Europe and North America over the last decades.
Several mechanisms have been proposed to explain these trends, but
consensus regarding the relative importance of recovery from acid
deposition, climate change, and land management remains elusive. To
advance our understanding of browning mechanisms, we explored DOC trends
across 13 nested boreal catchments, leveraging concurrent hydrological,
chemical, and terrestrial ecosystem data to quantify the contributions
of different drivers on observed trends. We first identified the
environmental factors related to DOC concentrations, then attributed the
individual trends of DOC to potential drivers across space and time. The
results showed that all catchments exhibited increased DOC trends from
2003 to 2021, but the DOC response rates differed five-fold. No single
mechanism can fully explain the ongoing browning, instead the
interaction of sulfate deposition, climate-related factors and site
properties jointly controlled the variation in DOC trends. Specifically,
the long-term increases in DOC were primarily driven by recovery from
sulfate deposition, followed by terrestrial productivity, temperature,
and discharge. However, catchment size and landcover type regulated the
response rate of DOC trends to these drivers, creating the spatial
heterogeneity in browning among the sub-catchments under similar
deposition and climate forcing. Interestingly, browning has weakened in
the last decade as sulfate deposition has fully recovered and other
current drivers are insufficient to sustain the long-term trends. Our
results highlight that multifaceted, spatially structured, and
nonstationary drivers must be accounted for to predict future browning.
Deforestation-Driven Increases in Shallow Clouds are Greatest in Drier, Low-Aerosol Regions of Southeast Asia
Authors: Leung Gabrielle R , Grant Leah D. , Heever Susan C van den
Published: December 2023

Anthropogenic activity drives extensive tropical deforestation,
particularly in Southeast Asia where 16% of total forest cover was lost
between 2000 and 2020. While land surface changes significantly affect
the atmosphere, their net impact on convective clouds is not
well-constrained. Here, we use satellite data to provide the first
observational evidence that long-term deforestation in Southeast Asia
robustly alters cloud properties, and that the magnitude of this
response depends on the atmospheric environment. Deforestation drives a
shift towards more widespread, shallower clouds during the daytime, with
amplified effects in dry inland areas compared with moist coastal
regions. Aerosols only weakly modulate the cloud fraction response, but
offset the cloud top height response to deforestation, suggesting the
influence of aerosol indirect effects. We conclude that the local
signature of forest loss is not uniform, and regional differences in
climatology must be considered when assessing deforestation impacts on
clouds and the climate system.
Ice Modeling Indicates Formation Mechanisms of Large-scale Folding in Greenland's Ice Sheet
Authors: Zhang Yu , Sachau Till , Franke Steven , Yang Haibin , Li Dian , Weikusat Ilka , Bons Paul D
Published: December 2023

Radio-echo sounding (RES) has shown that large-scale folds in the
englacial stratigraphy is ubiquitous in Greenland’s ice sheet. However,
there is no consensus yet on how these folds form. Here, we use the
full-Stokes code Underworld2 to simulate ice movements in
three-dimensional convergent flow, mainly investigating the effect of
ice anisotropy due to a crystallographic preferred orientation, vertical
viscosity and density contrasts in ice layers, and bedrock topography.
Our simulated folds show complex patterns and are classified into three
types: large-scale folds, small-scale folds and basal-shear folds. The
amplitudes of large-scale folds tend to be at their maximum in middle
ice layers and decrease towards the surface, in accordance with
observations in RES data. We conclude that bedrock topography
contributes to perturbations in ice layers, and that ice anisotropy
amplifies these into large-scale folds, while vertical viscosity
contrasts in ice layers are insufficient for large-scale fold
amplification.
Fault initiation, exuhmation, and propagation documented by low-temeprature thermochronology in the Andean Precordillera, San Juan, Argentina
Authors: Abbey Alyssa , Granger Darryl , Suhster David
Published: December 2023

The central Andean Precordillera, between 30-31°S, has experienced
active faulting and deformation from the early Miocene to present driven
by a flat-slab segment of the down-going Pacific Plate. Basic models for
fault propagation, in this region, involve progressive eastward stepping
of deformation; however, out-of-sequence faulting has been postulated.
Furthermore, deformation appears to have started earlier in the northern
part of this region and later in the southern part. We use apatite
(U-Th-Sm)/He (AHe) low-temperature thermochronology to quantify timing
of fault exhumation and fault growth patterns to test hypotheses about
out-of-sequence thrusting and the southward propagation of deformation
in the region. Nine vertical transects were collected in the
eastern-most part of the Precordillera. Preliminary AHe data indicate
complete and partial age resetting in middle to late Miocene sedimentary
units, that were deposited, buried, and subsequently exhumed. AHe ages
range between 30 - 2Ma and trend younger to the south, supporting
previous suggestions of north to south deformation migration.
Additionally, we use cosmogenic radionuclides (CRN) to assess modern
erosion rates across the landscape. Initial erosion rates range from 22
– 1330 m/my, with generally lower rates in the north and higher rates
to the south. Ongoing analysis and modeling of both thermochronologic
and CRN data will help to constrain the recent exhumation and erosion
history in the central Andean Precordillera and determine if combining
these two techniques can be used to identify out-of-sequence faulting
and changes in spatial patterns of tectonically driven deformation.
Delineation and Fine-Scale Structure of Active Fault Zones during the 2014-2023 unrest at the Campi Flegrei Caldera (Southern Italy) from High-Precision Earthquake Locations
Authors: Uccio Francesco Scotto di , Lomax Anthony , Natale Jacopo , Muzellec Titouan , Festa Gaetano , Nazeri Sahar , Convertito Vincenzo , Bobbio Antonella , Strumia Claudio , Zollo Aldo
Published: December 2023

In the past two decades, the central portion of Campi Flegrei caldera
has experienced ground uplift of up to 15 mm/month, and a consequent
increase in the rate, magnitudes and extent of seismicity, especially in
the past two years. We use a new method for multi-scale precise
earthquake location to relocate the 2014-2023 seismicity and map in
detail currently activated fault zones. We relate the geometry, extent,
and depth of these zones with available structural reconstructions of
the caldera. The current seismicity is mainly driven by the
time-varying, ground-uplift induced stress concentration on
pre-existing, weaker fault zones, not only related to the inner caldera,
dome resurgence but also to ancient volcano-tectonic collapses and magma
emplacement processes. The extent of imaged fault segments suggests they
can accommodate ruptures up to magnitude 5.0, significantly increasing
estimates of seismic hazard in the area.
Using System-Inspired Metrics to Improve Water Quality Prediction in Stratified Lakes
Authors: Kurucz Kamilla , Carey Cayelan , Huang Peisheng , Sousa Eduardo R. De , White Jeremy , Hipsey Matthew Richard
Published: December 2023

Despite the growing use of Aquatic Ecosystem Models (AEMs) for lake
modelling, there is currently no widely applicable framework for their
configuration, calibration, and evaluation. To date, calibration is
generally based on direct data comparison of observed vs. modelled state
variables using standard statistical techniques, however, this approach
may not give a complete picture of the model’s ability to capture
system-scale behaviour that is not prevalent in the state observations,
but which may be important for resource management. The aim of this
study is to compare the performance of ‘naïve’ calibration and a
‘system-inspired’ calibration, a new approach that augments the standard
state-based calibration with a range of system-inspired metrics (e.g.
thermocline depth, metalimnetic oxygen minima), in an effort to increase
the coherence between the simulated and natural ecosystems. This was
achieved by applying a coupled physical-biogeochemical model to a focal
site to simulate temperature and dissolved oxygen. The model was
calibrated according to the new system-inspired modelling convention,
using formal calibration techniques. There was a clear improvement in
the simulation using parameters optimised on the additional metrics,
which helped to focus calibration on aspects of the system relevant to
reservoir management, such as the metalimnetic oxygen minima. Extending
the use of system-inspired metrics for the calibration of models of
nutrient cycling, algal blooms, and greenhouse gas emissions has the
potential to greatly improve the prediction of complex ecosystem
dynamics.