bluuebunny/crossref_metadata_2025 huggingface dataset:
Sensor-based human activity detection using a novel machine learning algorithm in home automation
Authors: Raghavendra R. , Singh Vaishali , Arora Sonia , Gupta Mohan Vishal
Published: August 2024

The identification of anomalous behavior, the administration of home automation, and a broad variety of real-world applications that depend on human activity detection (HAD). HAD systems make use of intelligent human-computer interfaces, a component of proactive and proactive surveillance systems. Accurately detecting HAD from a sequence of still images is a challenging task because of factors like as the distracting background, the many viewpoints, the low resolution, and the partial occlusion.In this study, we propose a Radiant Moth Flame-Optimized Probabilistic Decision Tree Algorithm (RMFO-PDTA) method to detect human activities.Machine learning (ML) algorithms, according to recent research, are better suited to automate the feature extraction procedure from basic sensor information. The goal of this research is to improve home automation systems by adding HAD based on sensors with the help of a cutting-edge ML algorithm.Initially, the research acquired the HAD dataset and a Min-max normalization technique was employed to preprocess the data. The feature extraction method uses a Fast Fourier transform (FFT) technique which tends to extract the data features. To make a precise prediction of the HAD while simultaneously improving the speed of the RMFO-PDTA model's performance. Accuracy (97.3%), recall (97%), f1-score (97.5%), and precision (97.01%) are used to examine the outcomes of the experiment. The result of the research reveals that the suggested RMFO-PDTA technique works better than conventional approaches in terms of detecting the HAD levels efficiently.
Artificial Intelligence-Based effective healthcare prediction system for diabetic patients
Authors: Ramasamy Murugan , Acharjya Kalyan , Singh Yaduvir , Gupta Rupal
Published: August 2024

Diabetes, a chronic disorder characterized by elevated blood sugar levels, requires a high degree of care for diabetic patients. Diabetes treatment requires frequent monitoring, medication management, nutritional control and lifestyle changes to prevent complications. Effective diabetes treatment assists diabetic individual's healthier lives by reducing the risk of heart disease, kidney difficulties and visual problems. Healthcare providers are essential in instructing and helping patients as they struggle to manage this disease and preserve their general health. In this study, we proposed the Tabu Search-optimized Bidirectional Long Short-Term Memory (TS-BiLSTM) model to enhance the predictive accuracy of healthcare systems for diabetic patients. We gathered datasets from the National Institute of Diabetes Diseases from Kaggle open source, which includes glucose, age, BMI, etc. Initially, we applied min-max normalization to preprocess the collected data and utilized Principal Component Analysis (PCA) to extract key features from the preprocessed data. To improve the efficiency of the BiLSTM, we implemented the TS optimization technique. This combination of preprocessing and optimization strategies improves the BiLSTM model's performance and accuracy in evaluating and analyzing data. The result analysis phase is done on various parameters such as accuracy (95.72%), precision (94.5%), recall (89.68%) and F1-score(90.02%). The findings are compared with other existing methods and our suggested TS-BiLSTM approach performed better than different current methodologies.
Deep learning method for measurement-based anomaly recognition in manufacturing control systems
Authors: Meenu Shukla  , Raman Batra  , Rohaila Naaz  , Sanjeev Kumar Mandal
Published: August 2024

As the manufacturing sector continues to grow, it is increasingly important to make sure that complex control systems are operating effectively and dependably. In such structures, identifying anomalies is essential to keep things running smoothly and averting interruptions. This research provides an innovative strategy called intelligent dolphin swarm optimized adaptable gated recurrent network (IDSO-AGRN) for reliable anomaly identification in production control systems based on measurement data. The adaptability of GRN and neural intelligence derived from dolphin swarm actions are combined in the suggested IDSO-AGRN structure. The approach exhibits improved performance in managing the intricate and shifting behaviors that are characteristic of production procedures by utilizing combined intelligence and adaptable learning characteristics. Appropriate long-term reliance analysis and accurate identification of anomalies in historical data are made possible by the use of the gated technique. Several tests using a Python program based on the HIL-based augmented ICS security (HAI) dataset from various manufacturing contexts were carried out to validate the effectiveness of the IDSO-AGRN framework. The effectiveness of the suggested approach is examined using several indicators. An evaluation of the suggested method's superiority over current anomaly detection methods demonstrated its accuracy (91.4%), recall (98.2%), precision (97.8%) and f1-score (90.4%). The model's actual application in industrial settings is further enhanced by its capacity to adjust to changing anomalies and system conditions.
Fine-tuned tuna swarm optimization for enhanced multi-pass turning performance
Authors: Kumar Raj , Chaudhary Pavan , Ul Hassan Inzimam , Jayaraman Gowrishankar
Published: August 2024

Even with advances in machining optimization approaches, the complexity of multi-pass turning tasks is too much for current approaches to handling. This is because current techniques are not able to fine-tune or change dynamically to achieve the best possible results. A novel Fine-Tuned Tuna Swarm Optimisation (FTSO) is presented in this study for a specialized optimization method. FTSO actively modifies its parameters to optimize toolpath preparation, tool decision-making and cutting specifications in an effort to enhance turning performance generally. It is motivated by the group behavior of tuna swarms. To achieve improved multi-pass turning performance, the suggested FTSO technique offers a reliable and effective solution that adjusts to the ever-evolving machining situations. The FTSO method is set into practice and verified using machining trials and Matlab tools. The effectiveness of FTSO in enhancing cutting parameters is demonstrated by the results, which surpass those of conventional optimization techniques and offer significant perspectives for augmenting the productivity and caliber of multi-pass turning operations. In order to achieve improved multi-pass turning efficiency, the suggested FTSO methodology offers a reliable and effective solution that adjusts to the ever-evolving character of machining surroundings.
Boosted chameleon swarm optimization for optimizing air foil bearings with mathematical precision: A tribological perspective
Authors: Thulasiram Ramachandran , Kumar Raj , Singh B. P. , Srivastav Vaibhav
Published: August 2024

Air foil bearings (AFBs) are a vital element of high-speed rotating equipment because they transfer energy efficiently and without causing friction. Because tribological assessment requires accurate mathematics and there are many parameters that interact intricately, optimising AFBs is a difficult task. Current optimisation techniques fail to strike a proper equilibrium between exploration and utilization, particularly when dealing with the complex tribological dynamics found in AFBs. In order to achieve mathematical exactness, this research employs a novel optimisation technique called Boosted Chameleon Swarm Optimisation (BCSO) for the complex domain of the AFBs. The suggested BCSO technique improves the exploration-exploitation equilibrium present in conventional swarm optimisation by incorporating the adaptable and self-organizing properties derived from chameleon behaviour. By means of exacting mathematical simulations and finely tuned tribological examination, this research endeavours to maximise AFB effectiveness throughout a range of operational scenarios. Specifically designed to tackle the complex tribological problems that arise in AFBs, the BCSO technique seeks to maximise load-carrying ability, minimise friction and improve entire performance.
Enhancing lubrication performance with novel artificial intelligence-driven film thickness forecasting
Authors: Upadhyay Satish , Nagappan Beemkumar , Mishra Awakash , Srivastav Vaibhav
Published: August 2024

Elastohydrodynamic lubrication (EHL) is crucial for the longevity and performance of machine parts subjected to high loads and speeds. Analyzing EHL thickness settings with accuracy is crucial for improving construction and mitigating premature wear. Current approaches for forecasting such variables might be limited in their precision due to computation difficulties. This study presents a novel remora-optimized Gaussian process regression (RO-GPR) approach in calculating the factors related to EHL film dimension, addressing the requirement for a more effective and precise predictive model. The suggested RO-GPR approach is trained and verified by utilizing a dataset that was acquired through methods that are either simulation-based or practical. To show how well the suggested RO-GPR strategy handles the complex structure of EHL mechanisms, its efficacy is compared with that of other approaches. The study's findings reveal that the suggested RO-GPR model can predict EHL film thickness properties with an excellent level of accuracy, indicating its potential as a useful tool for tribological research. By providing insights that can improve the efficiency and construction of machine parts exposed to EHL circumstances, this research advances predictive modeling methodologies for lubrication mechanisms.
Boundary stress distribution and elastic viscous of emerging pavement predicted using an innovative hybrid machine learning technique
Authors: Alam Intekab , Sinha Sanjay Kumar , Desai Karishma , Manjunath Honganur Raju
Published: August 2024

Concrete's pumpability is significantly affected by the plastic viscosity of the mix and its surface yield stress. The long-term performance and durability of road infrastructure depend heavily on the capacity to predict the boundary stress distribution and elastic-viscous behavior of developing pavements. This study is concerned with predicting the elastic and viscous behavior of changing pavements using sophisticated predictive modeling approaches. Several techniques frequently need to capture the intricate interdependencies that are a feature of pavement behavior. To overcome this issue, we proposed the hybridization method of dynamic random forest combined with bilateral long short-term memory (DRF-BiLSTM). The purpose of DRF-BiLSTM is to predict the boundary stress distribution and elastic viscous of emerging pavement. Initially, asphalt binder (AB) datasets were collected. The collected dataset is preprocessed using the z-score normalization technique to reduce the effects of size discrepancies by standardizing the data. After preprocessing the data, the short-time fourier transform (STFT) method is used for feature extraction. Predictive results that are superior to those of benchmark models should obtained using experimental data supporting a hybridization of DRF-BLSTM in terms of.
Exploring load models to enable the supply of electricity in AC-Grid operation
Authors: Gill Amandeep , Ganesan Ezhilarasan , Malviya Ashwini , Singh Shweta
Published: August 2024

Modern life is impossible without electricity, which is essential for running our homes, workplaces, and other facilities. It can be challenging to meet the demand for energy in isolated villages and unconnected areas of the under developed globe. Compared to the demand for energy, power production is insufficient. Electric utilities would either impose zonal load reduction on the grid or choose not to electrify districts. Controlling power demand might be crucial in facilitating access to electricity; yet, meteorological ambiguity causes fluctuation in electricity consumption. This article suggests modifying appliance models to meet their functionality in situations where a lack of electricity is a problem. The suggested approach takes into account the impact of the weather being probabilistic and operating AC grid codes.
Monitoring stress levels and associated clinical health risks utilizing IoT and AI technologies to promote mental health awareness in educational institutions
Authors: Nagayo Analene Montesines , Al Ajmi Mahmood Zayid , Guduri Naga Rama Krishna , Al Buradai Fatma
Published: August 2024

This paper presents the development and implementation of a stress monitoring system and its associated health risks using IoT, GSM, and AI technologies. The designed system was implemented with IoT-enabled Particle Photon microcontrollers that read and processed data from biosensors and input switches to evaluate physiological factors including body thermal heat rate, systemic arterial pressure, heartbeat rate, electrical skin resistance, oxygen saturation level, pain or aches and breathing rate, as well as emotional and behavioral stress symptoms such as restlessness, being irritable or over-reactive, being upset or agitated, nervousness, and impatience. Real-time and distant access to the measured parameters were made feasible through IoT cloud platforms and customized smartphone apps. The system displayed the user's stress score and level (normal, mild, moderate, severe, and extremely severe), health risk level (zero, low, medium, or high), and stress and health management recommendations. When the resulting stress level was extremely high, the system generated a referral message and sent it by SMS to the guidance counselor for necessary mental health care support. As per the research findings, the IoT-based stress level detection prototype achieved an accuracy of 87.5% when compared to the data collected from the AI interactive stress evaluation mobile phone application. The developed application was based on the DASS-21 test and was administered to participants who volunteered from an institution in Oman. Furthermore, when compared to the NEWS2 early warning score system, the system's health risk level results had an accuracy of 93.75%.  With the help of this research project, guidance counselors, psychologists, and medical professionals will be able to assess and address some of the mental and physical health concerns that university students and faculty members have, as well as raise mental health awareness among individuals.
Assessing the potential of a deep learning algorithm for reducing supply chain risk management
Authors: Pandey Mukul , Ulle Ravishankar S. , Gupta Sheryl , Rastogi Mohit
Published: August 2024

The term Supply Chain Risk Management (SCRM) refers to a set of practices aimed at preventing, detecting and responding to unanticipated problems that arise at any point in the supply chain (SC). Many SCRM approaches rely on quick and flexible decision making based on relatively massive, multidimensional datasets. Disruptions, higher costs, reputational harm and a drop in competitiveness are possible results of poorly managed risks in the SC. To overcome these issues, we suggest a Modified Honey bees mating optimized boosting Restricted Boltzmann machines (MHBMO-BRBM) technique for reducing SCRM. Initially, Research gather the SC dataset and use a Z-Score normalization approach for data preprocessing. The principal component analysis (PCA) method is used to extract features from the SC dataset. To predict the SCRM and accelerate the performance of the prediction using MHBMO-BRBM. Accuracy (94%), recall (94%), F1-score (94%) and precision (94%) metrics are used to examine the experimental findings. Results from experiments show that the proposed MHBMO-BRBM method performs superiorly in reducing SCRM than conventional approaches.
Racial gaps in respiratory effects: The influence of personal and community determinants
Authors: Gambhir Vinima , Bhat Vinayak Anil , Abrol Monika , Nirala Pradeep
Published: August 2024

In several conditions, such as chronic obstructive pulmonary disease (COPD), the health results for black individuals are poorer than white adults. To assess the potential contribution of socioeconomic status (SES) disadvantage on an individual and community level to racial differences in COPD outcomes. We assessed respiratory outcomes by race using regression with a generalized linear mixed model, controlling the variables and SES traits at the individual, neighborhood and sequential levels. After removing the risk factors for COPD, wider airways were much more common in black subjects, with severe exacerbations and emphysema prevalence than white participants. Once individual-level SES has been taken into consideration, which can account for up to 12 to 35% of racial variations, respiratory outcomes and the black race had a weaker link but they link with statistical significance. Additional adjustments revealed that the SES at the neighborhood level was between 26 and 54 percent, which was to blame for the differences in respiratory outcomes between races. Black people remained to have a higher incidence of severe exacerbation and worse CT results even after adjusting for both individual and community SES variables.
Improving fake news detection on social networks through a novel machine learning approach
Authors: Jain Anurag , Kumar Arvind , Joshi Manish , Disawala Hansika
Published: August 2024

Recent years have seen an increase in societal information, such as commercial advertisements, celebrity information, political news, etc., due to the growth of online social networks.  Some social media sites including Facebook, Instagram, and Twitter, were impacted by Fake News (FN) spread by their users.  Nevertheless, some individuals propagate false information using words, images, and videos to increase their connections and reputation.  The most current information is unreliable and misleads other members on an online social network.  Because FN is circulated to encourage users to trust disinformation, it’s hard for detection algorithms to recognize false information according to uploaded material.  In this research, we will provide an autonomous false news detection strategy called Grey Wolf optimized Adaptive Bidirectional Gated Recurrent Unit (GWO+ABi-GRU) that can identify FN on Twitter.  The TF-IDF method translates textual material into a mathematical representation that accurately captures the value of terms and their context in the dataset.  We improve the overall efficiency of the BiGRU by applying this GWO, which leads to increased accuracy when spotting false news.  The experimental examination of real-world data shows that the proposed FN detection strategy GWO+ABi-GRU outperforms traditional approaches regarding recall, accuracy, F1 score, and precision.  This enhanced performance proves essential in preventing the circulation of false news on social media, protecting the integrity of information sources, and mitigating the potential damage caused by false information.
Exploring the interplay between adult sustainability attitudes, psychological wellness, affinity for nature, and interest in scientific topics
Authors: Chawala Jasbeen , Homavazir Zuleika , Dani Tarannum Sarwar , Kumari Nishant
Published: August 2024

In recent years, there has been increasing interest in the psychological concept of nature attachment and its relationship with pro-environmental views and psychological wellbeing. Understanding the general public's involvement in scientific matters is also crucial for comprehending scientific research. The researchers set out to chart the connections between adults' affinity to environment, their interest in science, their views on sustainability, and their mental health. In particular, the research set out to investigate the interplay between these factors by testing theory-based hypotheses using structural equation modelling (SEM). A stratified population was created using the probability corresponding to size sampling technique. The population was divided into strata based on relevant characteristics, and systematic sampling was employed within each stratum, taking into account its size relative to the overall population. The study included 436 participants, ranging in age from 19 to 75, who were citizens. The findings of the study revealed a direct relationship between adult nature attachment and adult scientific curiosity. Furthermore, adult scientific curiosity was found to have a direct relationship with sustainability attitudes and psychological wellbeing. Additionally, the analysis indicated that participant attitudes towards sustainability were somewhat and indirectly mediated by adult interest in scientific subjects. The study provided valuable insights into the connections between adults' interest in scientific concerns, connection to nature, sustainability attitudes, and psychological wellbeing. The results demonstrated that individuals who exhibited higher levels of nature attachment and scientific curiosity were more likely to hold favourable sustainable perspectives and report better mental health. The present research contributes to the corpus of expertise by outlining a paradigm that emphasises how scientific involvement affects the views of individuals and welfare.
Investigation on the effect of social problem-solving instruction on nursing students' thinking and decision-making capacity
Authors: Randhawa Sukhman Kaur , Sharma Nidhi , Gambhir Vinima , Suyog G.
Published: August 2024

Registered nurses require individuals with outstanding mental skills like problem-solving, decision-making, and analytical abilities due to the complicated healthcare system and demanding patient care setting. Examining the impacts of a societal troubleshooting course on a group of college registered nurses was the goal of this quasialmost scientific inquiry. Prior to and following the treatment, the study attempted to compare changes in numerical poll results, corporate interviews, updates to the Social Handling Issues Stock, scores on the Critical Analysis Test, and answers to private questionnaires. 50 college registered nurses were randomly selected and assigned to two groups: the experimental group (n = 25) and the uncontrolled group (n = 25). The data obtained from the study were analyzed using the SPSS (Statistical Package for the Social Sciences) program. Resolving societal issues sure has a beneficial impact on pupils. Ability to solve societal challenges, make decisions, and suspect critically after the training session in the experimental group (P =0.05), but in the custody group (P >0.05), that result was not seen. The findings indicated that formal societal instruction could enhance intellectual critical thinking, problem solving, and decision-making abilities. In light of this finding, nursing education should be delivered in novel, inventive, and unconventional ways compared to conventional teaching techniques. Instruction in mental abilities has to be included in the nursing curriculum. Therefore, it is advised that nursing pupils receive mental formation, including problem-solving.
Analysing the effectiveness of policies and programs for sustainable development in the Philippines
Authors: Asiri Masnona S.
Published: August 2024

In the modern era it has been found that the Philippines has been facing many environmental issues and as a result introducing effective policies for sustainable development has become a necessity. The present research has observed some of the problems that the country has been facing before discussing the potential that sustainable strategies possess for the country as they can help in building vital ecosystems and respect the overall environmental quality of the country. The research has discussed past policies of the Philippines and the new Philippine Development Plan (PDP) and AmBisyon 2040, both of which aims at implementing political leadership into their programs and projects for promoting sustainability, the policies will also be helping with ensuring inclusive and equitable education while creating opportunities for the people to improve their economic conditions.
Prediction of heart disease using a novel slap swarm optimized multi-objective random forest
Authors: Ganapathy Kavina , Kapoor Ekta , Patel Devanshu J. , Singh V. K.
Published: August 2024

Heart disease is a leading cause of death worldwide, becoming a major health concern for many people. Among the most important tasks and regular diagnostic research entails the identified cardiac issues, like heart diseases, valve conditions, etc. Early detection of heart disease may save many lives. The application of machine learning techniques in the medical sector has advanced significantly. A novel Slap Swarm Optimized Multi-Objective Random Forest (SSO-MORF) approach was presented in the proposed work for predicting cardiac disease. For this suggested investigation, heart disease information using individual customer identification at the University of California Irvine (UCI) was utilized, and data mining methods like categorization were applied. Min–max normalization and principal component analysis (PCA) were used for data preparation and feature extraction. As a result, a rather basic supervised machine learning technique may be used to predict heart disease quite accurately and with excellent potential value. According to this study, a classification based on the RF technique produced results with 99.45% accuracy, 98.3% recall, 98.6% precision, and a 98.9% f1 score. This finding demonstrates that our system is more efficient at predicting cardiac disease than other cutting-edge techniques.
Things to consider affecting secure, avoidant-fearful, and preoccupied attachment among mental health clients
Authors: Parmar Pankaj , Homavazir Malcolm , Shalini Dixit  , Pandey Noopur , Pooja Varma
Published: August 2024

Working alliance (WA) has been demonstrated to be a critical factor affecting treatment effectiveness. The relationship between patients' fundamental perceptions of attachment of WA and the efficacy of treatment as a result is becoming more widely acknowledged. To discover and examine the variables that affects the growth of solid attachment, avoidant-fearful attachment, and preoccupied attachment in psychologically ill patients. The research particularly seeks to investigate the many variables that influence these diverse kinds of attachments in people needing psychological treatment. The main healthcare psychologists enrolled 303 individuals who were scheduled for counseling. Self-report surveys on mental disorders, WA, and attachments were filled out by respondents. Participants who felt safer in their relationship with the psychotherapist displayed considerably higher WA. Increase in result was also connected with initial attachments to the psychotherapist in a subset of patients who finished treatment. According to the research, therapeutic connection is a significant WA prediction. According to the findings, connection to a psychotherapist might be more significant in regards to WA that previous attachments patterns.
Empowering aged persons care services: Leveraging data-driven BiLSTM-GRU integration with wearable devices
Authors: Patel Devanshu J , Khajuria Piyush , Rengarajan A. , Surabhi E. R.
Published: August 2024

Wearable medical devices (WMDs) have emerged as a promising medical technology to enhance patient care from a variety of medical angles. However, due to inaccurate signal measurement in sensors, the conventional model-driven framework has problems with its limited reconstruction ratio and compression ratio. A growing need for effective and individualized aged care services is created by the world's population's increasing aging. To increase the system quality and overall performance, the collected data is preprocessed to normalized data by using Z score Normalization. This study proposes a novel approach that integrates wearable device data with Elderly people's health and wellbeing may be predicted and monitored using Gated Recurrent Unit (GRU) and Bidirectional Long Short-Term Memory (BiLSTM) models. This data-driven strategy enables caregivers to deliver tailored care plans, timely treatments and early identification of potential health problems, which improve the aged population's overall quality of life. The BiLSTM-GRU evaluates the effectiveness and efficiency of an approach by analyzing the performance of Accuracy (96%), Precision (93%), F1-score (95%), Sensitivity (94%), Specificity (90%) and MSE. By advancing data-driven techniques in aged care services, this research intends to pave the way for a more effective and long-lasting healthcare system that is designed to meet the needs of the senior population.
Regional Integration and Food Security in West Africa: Challenges, Opportunities and Sustainable Solutions
Authors: Muhammad Abdulrasheed , Babatunde Ahmed Yusuf
Published: August 2024

Regional integration and food security are pivotal aspects of sustainable development, especially in the context of West Africa. The Economic Community of West African States (ECOWAS) represents one of the regional arrangements on political cooperation and economic integration in Africa. While regional integration holds the promise of bolstering food security through collective efforts, its success in fostering food security has encountered a myriad of challenges in West Africa. This study analyzed the problems and potential opportunities of regional integration in West Africa. From the analysis, it became evident that the ECOWAS faces unique challenges and opportunities as it strives to achieve a balance between economic collaboration and ensuring an adequate stable food supply for its growing population. Some of the problems of regional integration in West Africa include trade barriers, lack of unified agricultural policy, border issues and environmental problems. Notwithstanding these problems, collaboration within the ECOWAS framework presents avenues for member countries to unlock economic potential, foster stability, and collectively address food security challenges. It is therefore recommended that the ECOWAS needs to adopt a common agricultural policy, implement water management strategies, develop various market information systems and embark on different capacity building programmes in order to ensure food security among ECOWAS countries.
The Concept of International Security
Authors: Adhikari Abhaya Shekhar
Published: August 2024

To grasp the idea of international security, it is crucial to clarify the broader notion of security. A full understanding of international security can only be attained once the concept of security is comprehended. The shift in the understanding of security from the traditional approach to a more expansive one has created challenges in defining what security truly entails, resulting in it being considered as an essentially contested concept. Nevertheless, it is important not to use this disagreement as an excuse to avoid providing one's own definition. It is imperative to establish one's own conceptualization of security before delving into any work on security. This study formulates a comprehensive conceptualization of security reinstating the special role of state in security affairs that has been shadowed by the expansionist concept. The paper then applies the framework to conceptualize international security taking into consideration the unique complexities associated with the global context.
Analisis Diskursus Indonesia dalam Forum The Archipelagic Island and State (AIS) 2023
Authors: Ridani Syahri
Published: August 2024

The Archipelagic and Island States (AIS) Forum is a platform for island nations, regardless of their region, size, or level of development, aimed at addressing global challenges related to the sustainable use of marine resources, climate change resilience, marine pollution, emergency management, and the promotion of sustainable fisheries. Countries use international forums as the main instruments to tackle common issues in global politics. These forums are crucial for dialogue, where delegates meet and communicate through verbal and non-verbal language to express their concerns, share their views, and work towards reaching agreements. Initiated by Indonesia, the forum fosters new discourse among various international actors. This phenomenon raises the research question: How does Indonesia introduce and shape the discourse on marine development, climate change mitigation, and marine pollution management within the AIS Forum? The paper employs a constructivist paradigm to answer this research question, examining how Indonesia brings these issues into the AIS Forum, thereby creating a social construct within it. The research will utilize a qualitative, interpretative approach, employing data triangulation techniques that include interviews, literature reviews, and necessary documents. Consequently, the data sources will be secondary data.
 
The Archipelagic and Island States (AIS) atau Forum Negara Kepulauan adalah sebuah platform bagi negara-negara kepulauan tanpa memandang wilayah, ukuran dan tingkat pembangunannya yang memiliki inisiasi global untuk mengatasi tantangan penggunanaan sumber daya laut untuk pertumbuhan ekonomi berkelanjutan, ketahanan terhadap perubahan iklim, polusi laut, manajemen darurat dan peningkatan perikanan berkelanjutan. Didalam forum ini terdapat aktor dalam hubungan internasional yang memiliki pengaruh dalam regional maupun internasional di bidang kemaritiman karena terdapat kesepakatan didalam forum tersebut yang di prakarsai oleh Indonesia sehingga memunculkan diskursus baru bagi beberapa aktor dalam hubungan internasional, oleh karena itu dari fenomena ini memunculkan pertanyaan penelitian bahwa bagaimana Indonesia membawa diskursus sektor pembangunan kelautan, mitigasi perubahan iklim dan penanggulangan pencemaran laut di forum AIS.  Untuk menjawab pertanyaan penelitian ini, makalah ini akan menggunakan paradigma kontruktivisme. Teori ini akan melihat bagaimana Indonesia membawa diskursus ini ke dalam forum The Archipelagic and Island States (AIS) sehingga menciptakan kontruksi sosial di dalam forum AIS. Penelitian ini akan menggunakan metode penelitian kualitatif yang bersifat interpretatif dengan teknik pengumpulan data triangulasi dengan mengambil data kolaborasi wawancara, studi Pustaka dan juga dokumen yang diperlukan sehingga sumber data yang akan diperoleh ialah data sekunder.
Ethio-Telecom Reform: An Assessment from the Perspective of Homegrown Economic Reform and the Imperatives of Economic Globalization
Authors: Tulu Diriba Adugna
Published: August 2024

This article explores the Ethio-Telecom reform within the context of the Homegrown Economic Reform (HGER) initiated by the Ethiopian government and the imperatives of economic globalization. Its main objective is to analyze the extent to which the Ethio-Telecom reform within the HGER agenda is genuinely homegrown and new by considering internal dynamics and external influences. In order to achieve the intended aims, the article employed a qualitative approach, which includes the analysis of existing work surveys and document examination. To this end, the work has relied primarily on secondary data sources. The article argues that the Ethiopian HGER, with a specific focus on the Ethio-Telecom sector reform, reflects a mix of endogenous factors and external influences, with ongoing debates regarding its authenticity and alignment with domestic priorities. Moving forward, it should balance external support with local perspectives to avoid being perceived as a replication of external models.
Analisis Semiotika Pesan Moral Dalam Drama Korea Today's Webtoon (Analisis Semiotika Roland Barthes)
Authors: Yudhistira Bellinda Ferra , Prasetyo Yuwono Andri
Published: August 2024

Drama merupakan kisah cerita yang memperlihatkan kehidupan, perilaku, budaya manusia dengan menggunakan peran dan dialog yang akan dipertunjukkan. Drama mempunyai unsur amanat yang terdapat dalam dialog. Amanat merupakan pesan moral yang diberikan oleh penulis untuk para penontonya. Penyampaian amanat dalam drama berisi nilai moral berupa pedoman dan contoh yang baik agar penonton dapat mengambil makna tersebut. Salah satu Drama Korea yang memiliki pesan moral yang mendalam yaitu Today’s Webtoon. Drama Korea Today’s Webtoon menampilkan kisah perjuangan seseorang mantan atlet judo yang berusaha keras dengan rekan kerjanya untuk menjadi editor webtoon yang sejati, serta pesan moral dalam kisah cerita yang memotivasi. Drama Korea ini memiliki bentuk genre drama dan kehidupan untuk menunjukkan kehidupan dalam dunia kerja sehingga dapat menarik perhatian khalayak. Pada umumnya, drama Korea hanya mendeskripsikan tentang kisah cinta, persahabatan atau persaingan saja. Akan tetapi, berbeda dengan drama ini yang lebih menampilkan sisi kehidupan yang sesungguhnya terjadi. Penelitian ini bertujuan untuk menganalisis pesan moral dalam drama korea “ Today’s Webtoon” memakai metode kualitatif dan analisis semiotika Roland Barthes. Hasil dari penelitian ini menjelaskan bahwa Drama Korea Today’s Webtoon memiliki pesan moral pada scene drama yakni tolong menolong antar sahabat, mempunyai rasa tanggung jawab dan berkata baik dan positif.
Kata-kata Kunci: Drama Korea; Pesan Moral; Semiotika Roland Barthes;
Implementasi Kebijakan Dana Desa Terhadap Pemberdayaan Masyarakat Nagari Andaleh Kecamatan Batipuh Kabupaten Tanah Datar
Authors: Yeni Reza Fitri , Fitri Ulya
Published: August 2024

Artikel ini berfokus pada pembahasan tentang Minimnya kesadaran, pengetahuan, pengalaman dan konsep diri masyarakat dalam kegiatan yang berkaitan dengan pemberdayaan. Tujuan Dalam Penulisan ini ialah untuk mengetahui implementasi kebijakan dana desa terhadap pemberdayaan masyarakat nagari Andaleh Kecamatan Batipuh Kabupaten Tanah Datar. Jenis penelitian yang digunakan adalah metode penelitian kualitatif dengan analisis deskriptif . Teknik pengumpulan data dalam penelitian ini adalah menggunakan teknik observasi, wawancara dan dukumentasi. Adapun teori yang dipakai yaitu Konsep Implementasi Kebijakan. Hasil penelitian menunjukan bahwa, Implementasi kebijakan dana desa terhadap pemberdayaan masyarakat di Nagari Andaleh sudah berjalan tetapi penggunaannya belum sesuai dengan ketentuan PermendesPDTT No. 21 tahun 2020 tentang pedoman umum pembangunan desa dan pemberdayaan masyarakat desa. Melalui penyampaian laporan realisasi penggunaan dana desa yang tidak transparansi, agar tidak terjadi kesalahpahaman antara masyarakat dengan pelaksana kebijakan. Implementasi Kebijakan penggunaan Dana Desa mengacu pada Undang-Undang Nomor 6 Tahun 2014 tentang Desa, dimana tujuan dari pelaksanaan kebijakan Dana Desa ini adalah untuk mewujudkan kesejahteraan masyarakat di Desa dengan cara mendistribusikan keuangan negara kepada desa dalam bidang pembangunan dan khususnya untuk kegiatan pemberdayaan masyarakat di desa. Adanya kebijakaan penggunaan Dana Desa ini ditujukan pada kegiatan-kegiatan di desa yang telah ditetapkan prioritasnya sesuai dengan apa yang telah disepakati melalui Musyawarah Perencanaan Pembangunan Nagari (Musrenbang Nagari) tentang Rencana Kerja Pemerintahan Nagari (RKPN) setiap tahunnya. Dikatakan berdaya apabila kegiatan pemberdayaan yang dilakukan oleh Pemerintah Desa mampu menghasilkan proses pemberdayaan yang melahirkan partipasi masyarakat Kebijakan Penggunaan Dana Desa, khususnya dalam membantu terlaksana pemerintahan Desa. Sehingga, dalam hal ini Pemerintah Desa perlu memberikan dukungan dan bimbingan kepada masyarakat agar masyarakat mampu menjalankan peranan serta tugas-tugas dalam kehidupannya. Kegiatan pemberdayaan dimaksudkan untuk menumbuh-kembangkan kreativitas dan kemandirian masyarakat, khususnya masyarakat pedesaan, salah satunya diwujudkan melalui adanya kebijakan dana desa yang merupakan bentuk dukungan pemerintah pusat kepada pemerintah desa dalam rangka mempercepat proses kegiatan pemerintahan di desa.
Aliansi Dalam Balancing: Analisis Normalisasi Hubungan Qatar Dengan Iran Ditengah Munculnya Pergeseran Aliansi Di Timur Tengah
Authors: Putri Rahma Nia , Taufiqulhakim Rajaa Yusuf , Alfiana Rike , Aisyah Siti , Ismail Zaky
Published: August 2024

The need for regional alignments or alliances between large and small states has continued to influence international politics in recent decades. It has also given rise to the Gulf regional crisis which has largely become an increasingly important aspect of contemporary international political relations. The purpose of this article is to interrogate Iran-Qatar relations and the Gulf regional crisis, using the concept of balance of power as an analytical framework, and data from secondary sources. It argues that despite the economic blockade on Qatar, there has been improved relations between Qatar and Iran and more direct communication between officials of the two countries. However, the article concludes that the blockade imposed by the Gulf Cooperation Council (GCC) might further strengthen Iran-Qatar relations in the long run through the foreign policy taken by Qatar to normalise relations with Iran. This paper recommends that Qatar should constantly ensure proper manoeuvring between countries in the Gulf region for Qatar to survive and ensure its national interests are secured
Dilema Umat Islam Dalam Keterkaitan Memilih Pemimpin Di Indonesia Pasca Reformasi “ Tinjauan Dari Surat (An-Nisâ’/4:59)” Dan Hadis Nabi (Shahih Al-Bukhari,: 1765)
Authors: Muda Mahmuda
Published: August 2024

Indonesia is one of the countries in the world that is unique, including being the largest Muslim country in the world, and being a country with a plurality of other religions apart from Islam. Talking about Indonesiacannot be separated from talking about Muslims, an inseparable part before independence until independence from colonial invaders. The influence of Islamic teachings in Indonesia is reflected in the many freedom fighters who fought against colonialism so that they could unite the jihad spirit of the people of the entire archipelago in defending independence.The problem that arises in this reform era is the dilemma of Muslims in determining whose attitude isgood in leading .. This is a big dilemma as Muslims in determining who is a worthy candidate for leadership to be elected. Therefore, the author assumes that this issue is considered very urgent to be discussed, because the issue of leadership is also a very sensitive religious issue if examined closely.
Efficacy of Anogeissus leiocarpus as a Therapeutic Agent for Some Pathogenic Bacteria
Authors: Akharaiyi F.C.
Published: August 2024

BACKGROUND: This study examines the folkloric potential of the leaf extract of _Angogeissus leocarpus_ and it is aimed at the effectiveness for possible treatment of infections caused by some pathogenic bacteria.

METHODOLOGY: Solvent extract of the leaf of _A_. _leocarpus_ was processed for phytochemical and antibacterial effects. Clinical and type bacterial cultures were tested for susceptibility to the quotes.

RESULTS: The phytochemicals screened from the ethanol leaf extract were saponin, flavonoids, steroids, alkaloids, tannins, glycosides and phlobatannins while from the aqueous extract, it was flavonoids, tannins, saponin and steroids. The ethanol leaf extract provided the higher bioactive compounds for inhibition (10-36 mm) of the tested bacteria species. The aqueous leaf extract inhibited the bacteria species with zones that ranged from 10-25 mm. The ethanol leaf extract's minimum inhibitory concentration (MIC) was effective at 12.5 mg/mL and minimum bactericidal concentration (MBC) at 50 mg/mL. The aqueous MIC was effective with the 50 mg/mL concentration and MBC with the 100 mg/mL concentration. Promising values were recorded in the proximate and mineral contents analyzed. The hydroxyl radical scavenging values of the ethanol and aqueous extracts are 0.56±0.60 and 73±0.4, FRAP (1.86±0.11 and 1.24±0.2), DPPH (1.79±1.3 and 1.61±0.1) mg of ascorbic acid/1 g dry leaves sample respectively.

CONCLUSION: _A_. _leiocarpus_ extracts effective in bacteria inhibition and nutrition could be a good source for drug development to treat diseases hence it could have a space of recognition among the few medicinal plants which have been studied for their medical properties with novel therapeutic values.
From Earth to Art: Repurposing Clay Residues into Ephemeral Clay Sculptures of Organic Art and Styles
Authors: Donkor Evans Kwadwo , Boakye-Yiadom Fredrick , Ankrah Owusu-Ansah , Bondzie Micah Victor Kweku
Published: August 2024

The ceramic and sculpture studios generate significant amounts of clay residues, which often end up in landfills, contributing to environmental degradation. This study explores the latent of repurposing these waste materials into ephemeral clay sculptures, addressing both waste management issues and creating opportunities for innovative artistic expression. The research employed a qualitative approach, combining machine milling with artistic experimentation. Clay residues from local ceramic and sculpture art studios were collected, analyzed for composition, and processed to enhance their sculptural properties. A series of workshops with artists explored various techniques for creating ephemeral clay sculptures using these reclaimed materials. The resulting artworks were documented and analyzed for their aesthetic and conceptual advantages; contemporary artistic trends and methodologies; cultural and environmental repercussions. Clay residues, when properly processed, proved suitable for creating flexible yet intentionally temporary sculptures. The unique properties of the reclaimed clay led to distinctive structures and forms; inspiring new artistic styles reminiscent of organic, earth-based art. The ephemeral nature of the sculptures encouraged artists to explore themes of impermanence, environmental cycles, and the relationship between art and nature.
On Ekeland Variational Principle and Its Applications Through Fuzzy Quasi Metric Spaces with Non-Archimedean t-norm
Authors: Dutta Riya , Nayak Prasun Kumar , De Sujit Kumar
Published: August 2024

The aim of this article is to introduce Ekeland variational principle (EVP) and some results in fuzzy quasi metric space (FQMS) under the non-Archimedean \(t\)-norms. In this article the basic topological properties and a partial order relation are defined on FQMS. Utilizing Brézis-Browder principle on a partial order set, we extend the EVP to FQMS also. Moreover, we derive Takahashi’s minimization theorem, which ensures the existence of a solution of an optimal problem without taking the help of compactness and convexity properties on the underlying space. Furthermore, we give an equivalence chain between these two theorems. Finally, two fixed point results namely the Banach fixed point and the Caristi-Kirk fixed point theorems are described extensively.