bluuebunny/crossref_metadata_2025 huggingface dataset:
Renewable Energy in Southeast Asia
Authors: Woo Jeongho
Published: August 2024

Abstract: 
 
Renewable energy sources, such as solar, wind, and hydropower, offer great promise in the fight against climate change. The use of these clean energy sources can significantly reduce greenhouse gas emissions and help mitigate the impacts of global warming. One of the biggest advantages of renewable energy is that it is sustainable and does not deplete natural resources. Unlike fossil fuels, which are finite and create harmful emissions when burned, renewable energy sources can be replenished naturally and emit little to no greenhouse gasses. This makes them a crucial component in the transition to a low-carbon economy and a sustainable future.
Solar energy has great potential in Southeast Asia due to the region's high levels of solar irradiation. Several countries in the region, including Thailand, Malaysia, Vietnam, and the Philippines, have implemented policies and incentives to encourage the deployment of solar energy systems.
Hydropower is another significant source of renewable energy in Southeast Asia, particularly in countries with large rivers and mountainous regions such as Laos, Cambodia, and Myanmar. However, the development of large hydropower projects has faced criticism due to their potential environmental and social impacts.
Wind energy is less prevalent in Southeast Asia, but there are increasing efforts to develop wind power in some countries, such as Vietnam and the Philippines. However, the region's low wind speeds and limited land availability for wind turbines have limited the potential for large-scale deployment.
But what is the status of the uptake of solar, wind, and hydropower energies? This paper focuses on South East Asia and the uptake of renewable energies in the past two decades. We focus on the different laws and policies in place in multiple countries and how those laws have been implemented in the countries, and what remains to be done.
LLMs and Spatial Reasoning: Assessing Roadblocks and Providing Pathways to Improvement
Authors: Peng William , Powers Sam
Published: August 2024

In this paper, we show how relative location prompting can improve how Large Language Models (LLMs) such as ChatGPT interact with Spatial Reasoning (SR) tasks. LLMs likely have difficulty with SR tasks due to being designed for language based tasks, whilst SR tasks are more visual (Lee, 2023). By reading papers on Self-Ask (Press et al., 2023) and Chain-of-thought (Jason Zhanshun Wei et al., 2022) and recognizing their success, we hypothesized that prompting techniques similar to the ones mentioned would be effective in increasing the success-rate of the LLM agent in our Spatial Reasoning task. Taking these two factors into account, the solution we came up with was to turn the multi-step interaction-based SR tasks into more simple tasks by prompting the AI agent with its relative location to the target location after each step taken. We set up a 2D 5x5 grid world environment to test the LLM agent against, and by setting up a separate environment which includes relative location prompting, as well as a random environment, we saw the difference between the three success-rates. We collected and analysed data of 300 trials total (100 trials on each of the 3 environments) to conclude that relative location prompting does improve the success rate of LLMs when tackling SR tasks. This showed that by converting SR tasks into text, and by breaking down large tasks into smaller tasks, AI can solve SR problems better. Future studies should investigate other types of SR tasks, such as folding scenarios, and test out different prompting methods to determine the best one.
Musical Instrument Identification Using Machine Learning
Authors: Ding Evelyn , Sharma Emily
Published: August 2024

Music is a beautiful form of expression that is universally understood. In fact, people across all cultural backgrounds, even those without extensive exposure to musical education, can easily recognize the unique sounds of different instruments. This paper explores the use of machine learning to identify various instruments. The scope of this project focuses on audio recordings with one instrument playing one pitch, and the specific instruments in this study were viola, piano, and ukulele. This paper analyzes ways to quantify the differences in sounds of instruments using the harmonic frequency content apparent in spectrograms. It proposes the use of a simple but efficient K-Nearest-Neighbors machine learning algorithm. The results achieved 80% accuracy; using a larger dataset and using convolutional neural networks could improve accuracy of classification. The machine learning algorithm can be applied to the broader world of sound classification, and it can eventually surpass a human’s ability at identifying sounds (e.g. telling apart viola from violin, which the average human cannot do). There are numerous real-world applications for musical instrument recognition. It can enable automatic sorting and searching of massive musical collections with ease, which could be useful to streaming platforms that provide personalized recommendations to their users.
A Comprehensive Analysis of the Habitability of TRAPPIST-1 Exoplanets
Authors: Thejaswi Vyshakh
Published: August 2024

TRAPPIST-1 is the most studied star system other than our Solar System. The announcement of the discovery of the system fostered international attention for its potential to harbor extraterrestrial life, and maybe one day even human life. This paper aims to evaluate the validity of this excitement by interpreting and compiling all available information regarding factors that could potentially affect habitability. To do this, we look at all data regarding the Habitable Zone and Water Presence, Tidal Forces, and Atmospheric Composition resulting in Extreme UV (EUV) Flux. Specifically, we compare Transmission spectra of the four planets in the habitable zone with synthetic, potentially habitable atmospheres, we compare composition and density of the planets with Earth and other density models to determine water composition, and we consider both high and low stellar activity to determine EUV flux in an anoxic, Earth-like and very thin atmosphere. This paper shows that on net, due to the lack of a thick atmosphere, various issues arise that lead to the conclusion that the planetary system is uninhabitable for even the most resistant terrestrial organisms. This set of considerations could be used in studying other planetary systems and evaluating their habitability as well.
The Polarization of Tumor-Associated Macrophages as an Effective Therapeutic Strategy: A Comprehensive Analysis
Authors: Kadali Aryan , Parajuli Dr. Prahlad , Kethar Jothsna , Torremocha Virgel
Published: August 2024

The complex interplay between tumors and their microenvironment presents challenges in cancer therapy, sparking interest in novel immunotherapeutic strategies. Current therapeutic approaches lack consistency and pose significant risks to patients. Tumor-associated macrophages (TAMs) play a pivotal role in tumor progression or inhibition, depending on their polarization state. This comprehensive analysis explores the potential of selectively repolarizing TAMs towards an anti-tumor phenotype as an effective therapeutic strategy. Nanoparticle-based delivery systems, such as polymeric, lipid-based, and inorganic nanoparticles, offer promising TAM targeting and repolarization avenues. These strategies demonstrate the ability to shift TAMs from a pro-tumoral M2 phenotype to an anti-tumoral M1 phenotype, resulting in significant anti-tumor effects. These processes have been both in vivo and in vitro, depending on the progress of the process. Nanoparticles, for example, have primarily been in vitro, but some have reached the in vivo stage. Despite the complexity of tumor immunology, the repolarization of TAMs emerges as a promising and versatile immunotherapeutic approach with reduced adverse effects compared to traditional treatments. This study underscores the importance of continued research and development in TAM repolarization, paving the way for future advancements and improved cancer therapies.
Napoleon’s Discordant Historical Legacy: Republican Hero or Opportunistic Tyrant?
Authors: Han Luke
Published: August 2024

Heroic republican crusader to some, brutal despot to some, there is perhaps no more divisive European figure of the 19th century as the French general Napoleon Bonaparte. Napoleon is often characterized as one of two extremes, hero or tyrant, and this paper seeks to seek out a more nuanced historical image. This paper explores the major sociopolitical and military events that occurred around the newly founded Republic of France as she entered the 19th century which allowed for Napoleon to rise to power, and seeks to shed light on both Napoleon himself as an individual, as well as the impacts of his conquests and political decisions.
Twitter Sentiment Analysis Using Machine Learning
Authors: Gupta Srimayi , Jawahar Padmavathy
Published: August 2024

In an age of social media, online forums, and chats, cyberbullying is a prevalent issue. On Twitter (now X), approximately 500 million tweets are shared per day (Antonakaki et.al., 2021). It is the job of the moderators to ensure these tweets follow standard community guidelines. However, the sheer number of tweets makes it difficult to sort manually and ensure they are following protocol. Sentiment analysis and machine learning algorithms can be used to classify these texts automatically as positive or negative. Normally, these machine learning models are much more efficient and may provide higher accuracy rates in identifying hate speech in Twitter. In this paper, we are exploring the use of five classical machine learning algorithms to classify Twitter hate speech as neutral, racist, or sexist. Model performance was compared after using raw tweet data versus pre-processed tweets through data cleanup. Furthermore, we highlight two methods to deal with imbalanced datasets to improve the prediction rates. Overall, we were able to achieve a 96% accuracy in correctly classifying tweets into the different labels.
Heroin Chic Resurgence: The Unintentional Romanticization of Female Mental Illness as Depicted in Girl, Interrupted, Prozac Nation and An Unquiet Mind
Authors: Yao Sophia
Published: August 2024

A research article involving the literary analysis of novels Girl, Interrupted, Prozac Nation and An Unquiet Mind to better understand the unintentional romanticization of female mental illness within the text. Using this information, I connect the three novels to the resurgence in the romanticization of mental illness within current trends and social media.
How different parameters affect fast charging of LiFePO4 batteries in electrical vehicles
Authors: Ahn Rachel , Claydon Rory
Published: August 2024

This review paper provides a comprehensive analysis of electric vehicles (EVs) and the various factors influencing fast charging technology. The surge in EV adoption has necessitated advancements in charging infrastructure, particularly in fast charging solutions. We delve into the technical aspects of fast charging, including its impact on battery life, charging station architecture, power grid integration, and charging protocols. Moreover, we discuss the influence of battery chemistry, temperature management, and charging infrastructure on the efficacy of fast charging. By synthesizing current research findings and industry trends, this paper offers insights into the challenges and opportunities for enhancing fast charging efficiency and accessibility, thereby accelerating the widespread adoption of electric vehicles.
Manual Lymphatic Drainage vs. Photobiomodulation Therapy for Breast Cancer-Related Lymphedema
Authors: Vidavalapati Vaishvik
Published: August 2024

In this literature review, I compared the effects of manual lymphatic drainage (MLD) and photobiomodulation therapy (PBMT) in treating breast cancer-related lymphedema (BCRL). I focused on determining which treatment of the two optimized BCRL limb swelling reduction, symptom management, and QOL of patients the most, as well as comparing their minor side effects and potential major risks. There is limited information on the effects of the two treatments on BCRL, but from the information and studies I analyzed, I found that PBMT seems to be a slightly more effective treatment than MLD in the determiners I researched. However, more in-depth research in the future would certainly allow for a more accurate and significant comparison between the two treatments’ efficacy in treating BCRL.
Real-Time Black Ice Detection in Drone View Using YOLOX
Authors: OH JINHOO , Moon Justin , HAN SEOKHEE , SHIN DONGHWAN
Published: August 2024

Black ice is a perilous phenomenon resulting from frozen precipitation on road surfaces. It stands as one of the most prominent contributors to winter traffic accidents since it is nearly invisible. Given these characteristics, there is a pressing need to develop automotive systems capable of detecting black ice to improve driving safety and conditions. This study proposes the deployment of two YOLOX-based models to implement real-time black ice detection from drone-view images. The proposed approach leverages YOLOX-Tiny, known for its proficiency in real-time object detection, in conjunction with YOLOX-B which is a refined version designed specifically for detecting black ice on roadways. For training and evaluating the proposed system, we collected a dataset of black ice consisting of 2,851 sample images sized at 416x416 pixels. Significantly, YOLOX-Tiny achieved an AP@[0.5:0.95] of 0.4923, whereas YOLOX-B achieved 0.4779. Additionally, we demonstrate a practical implementation of the proposed method by deploying the system on the Nvidia Jetson Orin Nano device for real-time inference. The black ice dataset we compiled is publicly available on GitHub. We expect that the proposed black ice detection system will contribute to effectively maintaining safer driving conditions.
Understanding drivers of wildfires in California
Authors: Randhawa Jaden , Farquhar Samantha
Published: August 2024

This research study investigates the intricate relationship between El Niño events, precipitation patterns, and wildfires in California over the past two decades. California, known for its susceptibility to wildfires, has experienced significant variations in precipitation influenced by the El Niño-Southern Oscillation (ENSO) phenomenon. The objective of this research is to examine the impact of El Niño events on California's precipitation patterns and subsequently assess their association with wildfire occurrences. Predicting wildfire and precipitation wildfires are important to California’s significant agriculture production and better preparing for possible droughts or wildfires. To achieve this objective, a comprehensive analysis of climate data spanning the last 20 years was conducted. Historical records of El Niño episodes, obtained from reputable sources, were measured by correlation with precipitation data acquired from meteorological databases. Additionally, wildfire occurrence and severity data were collected from relevant agencies and organizations to be measured for correlation. As it turns out, while there was some positive correlation with El Nino and precipitation, there was little direct correlation between El Nino and wildfires. This means that there are many more complex factors to be assessed when figuring out causes of wildfires in addition to El Nino. The findings of this research will contribute to a better understanding of the main causes of wildfires in California.  The results can inform policymakers, land managers, and disaster response agencies in developing more effective strategies to mitigate the risks associated with wildfires. Additionally, the study will provide valuable insights into the influence of climate variability on fire-prone ecosystems, aiding in the prediction and management of future wildfire events.
The Air Quality Smart Monitoring and Management System
Authors: Saravanan Ashwath , Stuart Megan , Rios Richard
Published: August 2024

In this project, the problem that I attempt to solve is the lack of knowledge and action surrounding poor air quality. Inspired by a trip to India, I took action and built a prototype device that gave auditory and visual indications of the air quality and turned an air ionizer as necessary. During project development, I interfaced a microcontroller with multiple peripheral devices, and I studied associated documentation as necessary. Using this knowledge, I wired each component to a digital or analog pin, and a ground power connection. Some components also required a 5 voltage connection. I then programmed my microcontroller to read the temperature, humidity, and pollutant ppm values from the associated sensors. During project development, I tested my device in five environments: my room, my backyard, an open garage with a car running, the air after a car runs, and a car running in a closed garage. I used this data to determine what pollutant ppm values constitute good, poor, and bad air quality. Using this information, I programmed the microcontroller to use LEDs and a buzzer to notify users of the current air quality conditions. Finally, I later incorporated an ionizer into the project, and programmed the system to switch it on when the air quality is bad. Through further testing, I determined that each component did its job, allowing me to validate. Thus, this device could make a difference for people in industrial countries facing respiratory diseases and can be applied to various fields of science.
The Efficacy of Employing Music-based Interventions to Manage Neurodegenerative Diseases: A Systematic Review of Music Therapy as a Nonpharmacological Method
Authors: Patel Diya , Varkey Jobin , Kethar Jothsna , Torremocha Virgel
Published: August 2024

Among the diseases with no cure lies neurodegenerative diseases, a group of disorders that result from progressive damage to cells and nervous system structures and connections that are essential for mobility, coordination, sensation, cognition, and strength. Research on ways to manage Neurodegenerative Diseases (NDDs) is increasing in its pivotal nature in the modern realm of medicine, because to this date there is no widespread cure for them. This paper assesses the efficacy of using music-based interventions (MBIs) to manage these NDDs. In addition, after reviewing multiple articles, this research paper highlights a systematic review of music therapy (MT) when employed as a nonpharmacological method. These articles are based on relevant topics, which are included as a review of related literature. To make the data visually easier to read, a table was constructed, and visual information, including images, was incorporated. The primary method for going about this research problem was interviewing a music therapist. The interview provided extremely valuable insight from an expert who frequently witnesses the implementation of MBIs to better the quality of life for dementia patients. This includes using music therapy to manage their NDDs. From the primary themes analyzed from the music therapist's responses, the researcher concludes that music therapy is extremely efficient in managing dementia and other such NDDs, as well as, its increasing popularity, relevance, and practicality. However, additional research needs to be conducted on this subject. Additional studies and tests of other nonpharmacological methods and other specific types of music-based interventions are recommended in order to explore this topic further.
Machine Learning-based Biomarker Identification for Cardiovascular Disease Prediction: Combining X-ray with Electrocardiogram Analysis
Authors: Choi Heeyoon , Rose Gregory
Published: August 2024

Cardiovascular disease (CVD) is a major health problem worldwide. As there currently is no cure for cardiovascular disease, early diagnosis is imperative in maintaining a high quality of life for patients. Traditional method of diagnosis for cardiovascular disease involves assessing a coronary artery calcium score (CACS) through computerized tomography (CT). However, this method cannot achieve early diagnosis of cardiovascular disease. This study aims to find a novel biomarker for cardiovascular disease using X-rays and electrocardiograms (ECG). A machine learning-based approach will be used to create a multimodal algorithm that can diagnose the severity of CVD through using CACS benchmarks. Numerous experimental results indicate that the proposed multimodal approach enhances the accuracy of diagnosing the severity of CVD. The proposed multimodal approach was evaluated with several state-of-the-art convolutional neural network architectures, resulting in an impressive accuracy rate of 93.8% on a large-scale CVD dataset comprised of 21,625 patient samples. These findings demonstrate the feasibility of utilizing biomarkers such as ECG and X-ray for diagnosing CVD.
Understanding and Testing Iceberg Algorithmic Trading Strategy
Authors: Sahni Bhupinder Paul Singh
Published: August 2024

As Technology has advanced in recent times, it also has impacted the Trading requirements that modern day traders have. Trading now is not a simple Buy and Sell of a Security, but it is way complex involving complex mathematical algorithms programmed to execute Trades at much faster rates and using different trading strategies, also called Algorithmic Trading strategies. Traders’ selection of algorithmic strategy/ order types is a critical decision that significantly influences the execution quality and outcome of trades. In this Paper, we will specifically study one of the commonly used Algorithmic strategy/ order type called Iceberg Order. We will try to understand why Iceberg Orders are required, how they are executed with the help of different examples and what Testing should be done to ensure we deploy a Defect free Iceberg Order Strategy to production. A small issue in execution of trading strategy can result in big losses to the company, regulatory fines and reputational loss. So, Test Scenarios to be considered and testing requirements for Iceberg Orders should consider different scenarios which will be discussed in detail in this paper.
Enhancing Physics Education in Ugandan Teacher Training Institutions: Technology Integration and Gender-Inclusive Teaching Strategies
Authors: Waninga Willy , Olinga John Paul , Ajuko Anna Grace , Opusi Michael
Published: August 2024

Purpose: This article investigates strategies to enhance physics education in Ugandan Teacher Training Institutes (TTIs) by utilizing the TPACK framework. It focuses on technology integration, professional development for educators, and innovative teaching approaches to improve the quality of physics education.
Methodology: Employing a mixed-method design, this study examined ICT and gender integration in physics teaching across three Teacher Training Institutions in Eastern Uganda. The research utilized case study and survey designs, gathering data from 14 Physics Lecturers and 14 TTI administrators through surveys, interviews, observations, and document analysis. Purposive sampling was used to select participants with relevant expertise. Data were analyzed using content analysis and quantitative methods in Excel, adhering to ethical protocols that included obtaining permissions and ensuring confidentiality.
Findings: The study highlights that while physics lecturers possess strong subject matter and pedagogical knowledge, there is a notable deficiency in updated ICT skills and gender-inclusive practices. Key strategies for enhancing ICT competencies include implementing professional development programs, adopting blended learning models, and conducting ICT integration workshops. The research identifies that demographic factors and digital literacy significantly influence ICT integration, emphasizing the need for targeted training and resource allocation to create inclusive, technology-enhanced educational environments aligned with TPACK, DOI, and sociocultural theories.
Unique Contribution to Theory, Practice, and Policy: This study underscores the critical need for comprehensive training in ICT and gender inclusivity within TTIs. It emphasizes the importance of institutional support and policy development to modernize physics education, enhance pedagogical practices, and promote gender equity.
The Effects of Sheng’ Vocabulary Usage in the Learning of Kiswahili Grammar in Public Secondary Schools in Kenya
Authors: Mugun Dorcas , Simiyu John , Koros Rachel
Published: August 2024

Purpose: Sheng’ is a linguistic code based primarily on the Kiswahili structure and grammar with the lexicon drawn from Kiswahili, English and the various ethnic languages of Kenya; that are mostly spoken in towns and other urban areas. The purpose of this paper was to examine the effects of Sheng’ vocabulary on the learning of Kiswahili grammar in public secondary schools in Kenya.
Methodology: Krejcie & Morgan sampling table was used to sample the schools. Stratified random sampling, simple random sampling and purposive strategy were used to sample the public secondary schools to participate. Krejcie and Morgan sampling table was used to sample 55 teachers of Kiswahili and 360 students to take part in the study. Data was collected using observation schedules, focused group discussion guides and a writing task for students. Questionnaires and interview guides were used for teachers of Kiswahili. Qualitative data collected was analyzed thematically to generate information that was summarized in graphics and discussed in narrative form. Quantitative data was analyzed with the help of Statistical package for social Studies.
Findings: The findings of the study further revealed that Sheng’ vocabulary influenced written Kiswahili grammar as learners wrote Sheng’ words whereas they were expected to write standard Kiswahili.  
Unique Contribution to Theory, Policy, and Practice: School administrators should come up with a school-based language policy so as to control learners’ language environment. The ministry of education should encourage the culture of drama, music and debate competition among schools. The Kenya Institute of Curriculum Development should also ensure language use is stipulated in Kiswahili curriculum and Sheng’ be considered as an independent language code in the country.
Analysis of Conflict-Oriented Circumstances in the Social History of the Vedic Period: A Sociological Perspective
Authors: Adhikari Shukra Raj , Adhikari Bhawani Shankar , Acharya Ganga , Mishra A. K.
Published: August 2024

Purpose: The decline of the old and the emergence of the new; life and society involve a continuous series of conflicts within every social structure. Conflict has been a part of human civilization since ancient times, serving as a process for managing resources in socio-cultural structures. This article explores the different forms of conflict in Vedic social history, offering insights into an ancient civilization.
Design/Methodology/Approach: The research is based on a qualitative approach, using primarily secondary data. Information was gathered from Vedic texts, interactions with historians, historical documents of an ancient civilization, and research journal articles using historical content analysis. The content analysis method was used to analyze the collected data.
Findings/Results: The pattern of production was based on animal husbandry and the agricultural system in the Vedic period. Land and livestock were the major resources of the production system. The practices of conflicts were increasing in a way in the process of captured and extension of the land and livestock as the resources of the production system. In these surroundings of socio-economic circumstances, so many forms of conflicts are found in the Vedic period such as the conflict between the Aryans and the Dravidians, the Hind Aryan and the Vedic Aryan, the different Varna’s of Vedic Aryan, between different race and class of Vedic Aryans, the animal owners and the traders/merchants (pani), different states and kings, and in different cultures. Similarly, due to the leadership of holding resources, family, and the Gotra system are found to be debatable and antagonistic in the form of the conflicts.
Originality/Value: It has been found that the conflicts are of various kinds found in the society of the Vedic period. Such conflicts have been found the conflicts between son and father, conflicts between the parents and the children, between Aryans and Dravidians, between Hind Aryan and Vedic Aryan, husband and wife, women and women, Pastoralist and trader, between wives in Polygamous, conflicts in war, cultural conflict and the so on. These different kinds of the conflicts have been found and dealt in the Vedic society. In fact, the conflicts of the society have been found as the central causes of disharmonious, chaos, restlessness, and the trouble and it has been found stressful life in the society of Vedic era and conflicts have been found to be the reasons of the suffering as well as hardship of not only individual life but of the entire social structure even in the Vedic era.
Duygusal Öz Farkındalığın Duyguları Yönetme Becerileri Üzerindeki Etkisinde Duygusal İklimin Aracılık Rolü
Authors: Öztürk Efraim , Nacar Davut , Nanto Zülküf
Published: August 2024

Bu çalışmada, duygusal öz farkındalığın duygu yönetim becerilerine yönelik etkisi incelenmiştir. Ayrıca bu etkide duygusal iklimimin aracılık rolü de ortaya koyulacaktır. Bu amaca yönelik literatürde var olan ölçekler kullanılmıştır. Elazığ il merkezinde bulunan okullarda görev yapan 364 öğretmen çalışmaya katılmıştır. Zamandan ve mekândan tasarruf sağlamak amacı ile Tesadüfü Örnekleme yöntemi kullanılmıştır. Öğretmenlerin duygusal öz farkındalığa yönelik görüşlerini değerlendirmek amacı ile A Duygusal Öz Farkındalık Ölçeği; Öğretmenlerin duygusal iklime yönelik görüşlerini değerlendirmek amacı ile Okulların Duygusal İklim Ölçeği; Öğretmenlerin duygu yönetim becerilerine yönelik görüşlerini değerlendirmek amacı ile de Duygu Yönetim Becerileri Ölçeği kullanılmıştır. Araştırma verilerini analiz ederken demografik değişkenler için t-testi ve varyans analizi kullanılmıştır. Etki ve ilişkiyi belirlemek için korelasyon ve regresyon analizleri ile değerlendirmeler yapılmıştır. Aracılık için ise Process eklentisi kullanılmıştır. Elde edilen sonuçlara göre duygusal öz farkındalık, duyguları yönetme becerileri ve duygusal iklim arasında anlamlı ilişkiler tespit edilmiştir. Duygusal öz farkındalığın duyguları yönetme becerileri üzerinde anlamlı bir etkiye sahip olduğu görülmüştür. Bu etkide duygusal iklimin ise kısmi aracılık etkisi gösterdiği tespit edilmiştir. Okul yöneticilerinin duygusal iklimi düzenleme konusunda istekli olması, öğretmenlerin duygularını yönetme becerilerini olumlu yönde etkileyecek ve eğitime katkı sağlayacaktır.
Comparative Analysis of Profitability between Public and Private Sector Banks in India: A Study of SBI, Syndicate Bank ICICI Bank, and HDFC Bank
Authors: Ms. Amudala Bhumika  , Mr. N. Srikanth Reddy  , Dr. Chokkamreddy Prakash
Published: August 2024

This study provides a comprehensive comparative analysis of profitability between public sector banks and private sector banks in India, focusing on four prominent institutions: State Bank of India (SBI), ICICI Bank, HDFC Bank, and Syndicate Bank. By examining key financial metrics such as Return on Assets (ROA), Return on Equity (ROE), Net Interest Margin (NIM), and Cost-to-Income Ratio, this research aims to elucidate the differences in profitability and operational efficiency between these banks. The analysis draws on secondary data from various financial sources, employing descriptive statistics, graphical representations, and ratio analysis to highlight trends and performance disparities. The study reveals that while public sector banks like SBI and Syndicate Bank exhibit substantial growth in total assets and deposits, private sector banks, particularly ICICI and HDFC, demonstrate superior profitability and cost efficiency. The findings underscore the impact of management practices, technological advancements, and macroeconomic conditions on bank performance. This research provides valuable insights for investors, regulators, and bank management, contributing to a deeper understanding of the factors driving profitability in the Indian banking sector.
Performance Analysis of Selected Mutual Fund Schemes: A Case Study
Authors: Ms. Sathiri Sneha  , Mr. Shravan Boini  , Dr. Chokkamreddy Prakash
Published: August 2024

This study aims to evaluate the performance of selected mutual fund schemes offered by Aditya Birla Sun Life Mutual Fund. By leveraging secondary data from April 2022 to March 2023, this research analyzes the Net Asset Value (NAV) and corresponding returns of five mutual fund schemes. Utilizing statistical tools and the Sharpe Index Model, the study assesses risk-adjusted returns to rank the schemes and provide insights into their relative performance. The findings serve as a valuable resource for individual investors, organizations, and regulators, facilitating informed investment decisions and highlighting market trends. The research underscores the significance of mutual funds as a viable investment vehicle for diverse portfolios and examines the efficacy of specific schemes in achieving their investment objectives.
Performance Evaluation and Risk Analysis of Mutual Funds: Insights from Recent Trends and Technological Advancements
Authors: Mr. Jenegala Venu Prasad  , Mr. Indraganti Kamalaksr Rao  , Dr. Chokkamreddy Prakash
Published: August 2024

Mutual funds, as a popular investment vehicle, pool resources from multiple investors to create diversified portfolios managed by professionals. This study explores the performance of mutual funds by analyzing various types, including equity, bond, and balanced funds, and their associated risks. Utilizing both primary and secondary data, the research evaluates mutual funds based on returns, investment patterns, and risk factors. It also examines the impact of recent technological advancements and regulatory changes on fund performance. The study highlights the benefits of mutual funds, such as diversification and professional management, while addressing potential risks including market, credit, and interest rate risks. By assessing the effectiveness of different mutual funds, the research aims to guide investors and improve capital allocation. The findings provide insights into how mutual funds contribute to individual financial goals and broader economic stability
5G Analysis Using Software Applications
Authors: Mohd Hakimi Zohari  , Mohd Hezri Mokhtar  , Hairulazwan Hashim
Published: August 2024

Recently, 5G connection is widely used for mobile communication. The 5G technology is increasingly implemented in Malaysia country and in the big towns. There are many researches have been done to test and improve the connection. For the research analysis, Net Analyzer, nPerf, Meteor and speedtest applications that can measure parameters related to cellular communication have been used as a measurement tool. As a conclusion, internet and mobile connection shows that the performances are good for the users.
Picture and Picture Learning Model in Improving Mathematics Learning Outcomes for Students at SDN Wonobodro 01 on Flat Shapes Matter
Authors: Purwantyono Bambang , Nadhiyya Asa , Anaguna Nursyam , Manullang Ketrin R , Marshanawiah Andi
Published: August 2024

The problem in this research is that the learning outcomes of class II students at SDN Wonobodro 01 are still low in Mathematics on the topic of flat shapes. This is because the learning system provided by the teacher in class is less interesting, causing students to be less enthusiastic about participating in the learning provided. The aim of this research is to determine the increase in mathematics learning outcomes in flat shapes material using the picture and picture learning model for class II students in the first semester of SDN Wonobodro 01. The research method used is classroom action research (CAR) which is carried out in two cycles and every cycle consists of four stages, namely planning, implementation, observation and reflection. The research results showed that the picture and picture model was successful in improving student learning outcomes. This was shown by the results of the percentage of student completion in the pre-cycle of only 19.2% with an average class score of 53.1. Then, in cycle I it increased to 53.8% with an average class score of 64.8 and increased again in cycle II to 92.3% with an average class score of 90.7. Thus, it can be concluded that the use of the picture and picture model in the material for building mathematical data was successful because student learning outcomes increased each cycle.
The Application of Mind Mapping Method to Improve Subject Writing English Main Topics Analytical Exposition Text for class 11 students North Sumatra Hajj Health Vocational School
Authors: Chairunnissa Chairunnissa
Published: August 2024

This research aims to determine the skills of class This research is classroom action research using two cycles. The research instruments used were observation sheets and written tests. Based on the results obtained, observations showed that the average for the first cycle was 53%, while for the second cycle, it was 83%. This shows increased cooperation, activeness, and changes in student learning outcomes. From the results of the written test on mastery of analytical exposition text writing material, the average score for the first cycle was only 68.39 with students not yet reaching the KKM of 80. Meanwhile, in the second cycle, the average score for the written test reached 82.50, with students achieving the expected KKM. the. It proves that the action hypothesis can be achieved, so applying the Mind Mapping technique can improve the ability to write analytical exposition text of Class XI students at the Hajj Health Vocational School, North Sumatra.
CHARACTERISTICS OF EYE MOVEMENTS WHEN COMPARING IMAGES OF STRONG AND WEAK EMOTIONAL EXPRESSIONS
Authors: ZHEGALLO ALEXANDER , NOSULENKO VALERY , BASUL IVAN
Published: August 2024

In previous studies of facial expression perception, integral measures of eye movements were calculated for selected regions of interest or for regular time intervals. Combining the analysis of free verbalizations and the analysis of eye movements in one study makes it possible to obtain and compare the integral characteristics of eye movements for different types of verbalizations. Participants compared 13 images of strong and weakly expressed emotional expressions from the VEPEL database. Comparisons were made on a scale from 1 to 9 with free descriptions of the differences between the images. At the same time, eye movements were recorded. For time intervals corresponding to the selected verbal units, integral integrated indicators of eye movements were calculated: number of fixations, average duration of fixations (ms), average pupil dilation (mm), total duration of fixations (ms), path length as the sum of distances between the centers of fixations (px), coverage area (Convex Hull) as the area of a polygon covering the viewing area, the vertices of which are the centers of fixations (px2). The study involved 50 Moscow university students: 42 women and 8 men aged 18 to 39 years (m=22.5, sd=4.8). Differences between different types of verbal units are described. When justifying the assessment of similarity between images, subjects first of all resort to the “easiest” descriptions, characterized by a smaller amount of viewing of images. At the same time, the “complexity” of “heavy” descriptions, characterized by a large volume of examination, is compensated by a reduction in the duration of individual visual fixations. When solving a comparison problem, subjects strive to provide an acceptable level of justification for this assessment from their point of view, while avoiding constructs that lead to an increase in the complexity of the problem being solved. If it is necessary to use “complex” constructs, some reduction in cognitive load is achieved by reducing the duration of visual fixations.
THE MEANING OF THE CONCEPT OF «PERSONIFICATION» AS A NECESSARY THEORETICAL TOOL FOR ANALYZING PSYCHOLOGICAL TRAUMA
Authors: KRASILO A.I.
Published: August 2024

The concept of personification is, in our opinion, the key to solving some fundamental problems of age and clinical psychology. Firstly, it is required when analyzing the process of gaining independence in early childhood. Secondly, without it there is no way to analyze the traumatic situation and the phenomenon of «personification introjection». In a chain of dramatic situations, the personalized image of alternating beneficiaries has a single narrative component, which is destructively enriched with each new trauma of the victim. An individual-interpersonal «traumatic funnel» is formed, which does not have its own power of drawing the victim into traumatic memories. Such a force is the flow of the victim’s own consciousness, directed into the past. Being affectively limited and disoriented within the framework of the performing position formed as a result of trauma, the victim, in fact, exposes himself to suffering, This performing position, which is closely related to the group form of fear, is the result of the disintegration of the associated activity into indicative and performing parts and the fixation of polarized positions for the beneficiary and his victim. The panic fear of the victim, destroying the indicative part of the individual’s activity, exists in the individual, but not at all for the individual, but to ensure group functions on the part of the powerful leader. Keywords: personification, personifier, beneficiary, the relationship of power
Mental Wellbeing and Resilience among Occupational and Public Health Nurses in Cebu, Philippines
Authors: Lumayag Lynette C. , Bacarisas Joan, P.
Published: August 2024

Mental well-being suffices to be the most important indicator of mental health, while resilience is the adaptation process to bounce back into a normal life. Following the COVID-19 pandemic, the Philippine government issued an enhancement plan to address the scarcity of workers in hospitals, clinics, and municipalities. This will address the government mandate to assess and provide proper care for nurses in terms of their mental well-being and their resilience efforts following the crisis. The aim of the study is to assess the level of mental well-being and resilience among occupational and public health nurses in Cebu, Philippines. However, there are limited resources to be found at the local level concerning the mental well-being and resilience of nurses in Cebu. The methods used in the study are a descriptive correlational design with 99 randomly selected nurses in city health, clinics, and companies in Cebu. The instruments used were the MHC-SF and Brief Resiliency Scale models, disseminated through face-to-face interviews and Google Forms to gather the data. Data were analyzed using descriptive and inferential statistics, summation, chi square, Cramer’s V, and Pearson r. The results of the study show that out of 99 nurse respondents, they attain the highest level of mental well-being, which is flourishing, with over a quarter of nurses having moderate mental well-being and a few nurses are languishing. For the respective profiles of the respondents, over half of them were aged 18–35, followed by over one-third of them being 36–55, and a few of them being 56 and above. The results for the level of resilience among nurses are within normal, and a few of them were in neutral. In conclusion, the mental well-being and resilience of occupational and public health nurses in Cebu achieved the highest level of well-being and achieved normal resilience following the pandemic. With the help of the governments’ efforts to provide well-being to health workers under R.A. 11036 and R.A. 11058, nurses burden eases their fear, anxiety, and stress. It helps them recover and cope following the pandemic.
Esnek Öğrenme Ortamı İlgi Ölçeğinin Geliştirilmesi
Authors: Fer Seval , Genç Esma , Cırık İlker , Uysal İbrahim , Ertuna Levent , Yıldız Sevilay , Debbağ Murat , Gürer Melih Derya , Pehlivan Hülya , Karadeniz Derya , Kuzgun Yasemin , Karataş Fatih
Published: August 2024

Son yıllarda etkili öğrenme üzerindeki artan vurgu ve bilişim teknolojilerindeki hızlı değişimler, öğretim kurumlarında tüm öğrencilerin ihtiyaçlarını karşılayan esnek bir öğrenme anlayışının öneminin altını çizmektedir. Bu çalışmada, belirtilen önemden yola çıkarak öğretmen adaylarının esnek öğrenme ortamlarına ilgisini belirlemek için bir ölçme aracı geliştirmek amaçlanmaktadır. Çalışmada ilgili alan yazın doğrultusunda 36 adet aday madde oluşturulmuş ve "konu alanı (5), ölçme ve değerlendirme (5) uzmanlarının görüşleri" sonrasında kalan 30 madde ile deneme uygulaması gerçekleştirilmiştir. Beşli Likert tipi ölçeğin geliştirilmesi için iki ayrı örneklem üzerinde çalışılmıştır. Araştırmanın birinci örneklemi üç farklı üniversitede öğrenim görmekte olan 469 öğretmen adayından, ikinci örneklemi ise iki farklı üniversitede öğrenim görmekte olan 329 öğretmen adayından oluşmaktadır. Birinci örneklemden elde edilen veriler ile açımlayıcı faktör analizi kullanılarak ölçeğin mevcut faktör yapısı ortaya konmuş; madde analizleri ve güvenirlik incelemesi gerçekleştirilmiştir. İkinci örneklemden elde edilen veriler ile deneme uygulaması sonucunda elde edilen yapı doğrulayıcı faktör analiziyle incelenmiştir. Ayrıca ikinci örneklem üzerinde tekrar güvenirlik alınmıştır. Açımlayıcı faktör analizi sonucunda açıklanan varyans oranı %44 olan 29 madde ve tek boyuttan oluşan bir yapıya erişilmiştir. Düzeltilmiş madde-toplam korelasyon değerleri, ölçek maddelerinin yeterince ayırt edici olduğunu göstermiştir. Doğrulayıcı faktör analizi sonucunda elde edilen uyum indeksleri ilgili kriterleri karşıladığından model uyumunun sağlandığı belirtilebilir. Çalışmada güvenirliği belirlemek için incelenen Cronbach alfa ve McDonald omega katsayıları, her iki örneklemde de .92 olarak hesaplanmıştır. Elde edilen katsayılar ölçekten elde edilen puanların güvenilir olduğunu göstermektedir.
A filosofia por trás do videogame: metafísica, epistemologia e ética dos jogos eletrônicos
Authors: Souza Euclides
Published: August 2024

More than mere human entertainment, in this paper we will argue that video games have their own ontological status as an institutional event of linguistic and social interaction, excluding the old definitions that placed them as a subordinate to the class of tools and other technological creations of humanity, proving themselves to be an entity independent of our minds, thanks to their various fundamental elements, and also capable of providing conditions for our own understanding of ourselves as rational human beings.
Accelerating Fintech optimization and cybersecurity: The role of segment routing and MPLS in service provider networks
Authors: Olajide Soji Osundare  , Adebimpe Bolatito Ige
Published: August 2024

This review paper explores the profound impact of advanced financial modeling techniques on strategic business planning and performance. The paper begins with an overview of the evolution of financial modeling, highlighting the importance of advanced techniques such as Monte Carlo simulations, real options analysis, and machine learning models. It delves into the role of technology, including artificial intelligence and big data analytics, in enhancing financial modeling capabilities. The discussion then shifts to how these advanced models support strategic business planning by providing deeper insights, improving risk management, and facilitating better decision-making. The paper also examines the challenges of implementing advanced financial modeling, including data quality issues and skill gaps, and offers practical business recommendations. Future trends in financial modeling, such as increased AI integration and the incorporation of ESG factors, are also explored. The review concludes by emphasizing the significant benefits of advanced financial modeling in driving strategic business decisions and improving overall business performance.
Keywords: Advanced Financial Modeling, Strategic Business Planning, Monte Carlo Simulations, Machine Learning Models, Risk Management.