bluuebunny/crossref_metadata_2025 huggingface dataset:
The Relationship Between Type and Position of Fungal Infection with Age and Gender
Authors: Fanosh Mohammed Hessiun , Eljamay Salwa Muftah , Elzer Ashraf Saad , Alkirbal Hamdi Abdulbasit
Published: March 2024

Dermatophytosis is a superficial fungal infection caused by filamentous fungi that attack the keratinized tissue. Aimed to: the find out relationship between type and position of fungal infection with age and gender. Material and Methods: This cross-sectional survey study was carried out at the dermatology department, from August 2021 to July 2023. Results: The ages most affected by fungi were between 17 and 32 years old at 60%, followed by the oldest age over 35 years old. The females were the most infected with fungi, 93 out of 155. As for the type of infection, yeast was the highest, especially in 60 women. hyphae 28 and spores 8 where males were less infectious, the relationship between gender and fungal position, because p-value < 0.05, As for the type of fungus and its existence, it has nothing to do with gender because p-value > 0.05, it has nothing to do with gender because p-value > 0.05, and the relationship between age and presence of fungal infection, because p-value < 0.05,  the type of fungus and position of fungal infection, it has nothing to do with age because p-value > 0.05. Conclusion: females are more likely to be infected with fungi, whether they are by infection type or location, and the most infected ages are between 17 and 32 years old. The study also showed that the place of infection in nails was found in males and there was no infection in females.
Effectiveness of Mediation and Arbitration as Alternative Dispute Resolution Methods in Mexico
Authors: Pablo Juan
Published: March 2024

Purpose: To aim of the study was to analyze effectiveness of mediation and arbitration as alternative dispute resolution methods

Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries.

Findings: Mediation and arbitration offer efficient, cost-effective alternatives to litigation. Mediation involves facilitated negotiation sessions with a neutral mediator, fostering open communication and tailored solutions. Arbitration entails submitting disputes to a neutral arbitrator for a binding decision. Both methods ensure confidentiality, expertise, and enforceability, making them highly effective in resolving disputes outside of court.

Unique Contribution to Theory, Practice and Policy: Theory of social exchange, justice theory & game theory may be used to anchor future studies on effectiveness of mediation and arbitration as alternative dispute resolution methods. Practitioners in the field of alternative dispute resolution should prioritize enhancing their skills and competencies to effectively facilitate mediation and arbitration processes. Policymakers should prioritize the promotion of mediation and arbitration as viable alternatives to traditional litigation within legal frameworks and regulatory environments.
Evaluating the Physiochemical and Nutritional Attributes of Dates (Phoenix Dactylifera) Based Cupcakes
Authors: Hassan Ahmed , Ashfaq Javeria , Mudassar Muhammad , Sadiq Dr yasir , Naz Tabana , Saeed Sumaira , Raza Muhammad Qasim
Published: March 2024

Purpose: The proximate analysis aimed to determine nutritional profile of the cupcakes including moisture, crude fat, crude fiber, crude protein, ash, pH and acidity values, while the physicochemical analysis was performed to study total phenolic and total flavonoids contents. The organoleptic attributes if date cupcakes were studied by using nine points hedonic scale for texture, color, volume, flavor, aroma and hardness.

Materials and Methods: Exploratory research design was opted for qualitative and quantitative study of five treatments of date cupcakes aimed to address their dietary significance with respect to shelf life status, nutritional content as well as phytochemical and physicochemical analysis. Dates were purchased from intensive farmers from Multan division, Dera Ismail khan and from local markets. The dates were sorted, graded and washed with chlorinated water to remove field waste. The substitute fruit sample was conveyed to Food Science & Technology lab of Minhaj University Lahore under controlled conditions for further studies. The dates enriched cupcakes with different percentages of date pulp (5%, 10%, 15%, 20%, and 25%) along with control (without date pulp) were subjected for proximate, phytochemical and physicochemical analysis.

Findings: The calculated resulted were compared with control and it was concluded that the overall acceptability and stability of cupcakes with 20% date pulp was greater than other percentages.

Implications to Theory, Practice and Policy: Phoenix dactylifera is among the oldest plants cultivated by men. The nutritional, industrial, medical and environmental importance of this plant is globally acknowledged. Current studies focus on nutritional significance of Phoenix dactylifera when used as a natural additive in cupcakes.
AGILA (Araling Panlipunan Game-based Interactive Learning Activity): Boosting the Learning Attitudes of the Students
Authors: Buenaflor Arwin
Published: March 2024

The use of game-based learning has emerged as an innovative educational strategy that promotes student motivation, emotional engagement, and enjoyment. gamification in education has been found to be popular and engaging among students. This study assessed the increase in students’ learning attitudes through the implementation and utilization of AGILA (Araling panlipunan Game-based Interactive Learning Activity) at Luis Hervias National High School in Villamonte, Bacolod City, focusing on Grade 10 Junior High School students enrolled for the school year 2022 – 2023. To gauge the participants’ reactions and experiences after engaging in game-based learning, the researchers utilized an adopted and modified survey questionnaire of game-based learning attitudes. The findings suggest that the students’ learning and interests are not enduring and impactful due to the limited range of modalities available for utilization. Most of the measured statements reflect only average results, indicating a lack of high engagement with the modular approach. Moreover, the AGILA brings about significant enhancements in students’ attitudes towards learning Araling Panlipunan. The mean results, which are based on the students’ capabilities and adjustments in game-playing, affirm the positive impact on the students’ learning experiences.
The Effects of the Coronavirus Pandemic on the Indicators of the End Tuberculosis Strategy: A Literature Review
Authors: Matakanye Hulisani
Published: March 2024

Coronavirus disease 2019 (COVID-19) had severely taken a toll on the health system in all nations from the wealthiest to the poorest countries. The disruption to the health system was not only due to the direct effects of the COVID-19 pandemic but also the pressure it caused to stretch the health systems beyond their capability indirectly. The purpose of this review was to explore the effects of the COVID-19 pandemic on the indicators of the end tuberculosis strategy. Methods: Articles were searched from scientific search engines such as CINAHL Plus (EBSCO), PubMed, Google Scholar, Medline, ProQuest, APA Psych, INFO as well as manual searches through Google and Google Scholar search engines. Both quantitative and qualitative studies that showed the impact or effects of the COVID-19 pandemic on TB diagnosis, TB patient management, treatment initiation, treatment adherence, patients’ loss to follow up were included. A total of 375 articles were screened, and 12 full-text articles were ultimately included in the review. Findings: The extracted impact were synthesized thematically into three indicators of the end TB strategy: impact on TB incidence rate; impact on TB deaths; Impact on catastrophic costs due to TB. Conclusion: The COVID-19 pandemic has affected the three indicators of the end TB strategy and has significantly reversed the global TB progress in the fight to end TB epidemic. This has increased the risk of TB incidence, deaths, and the severity of economic impact on TB-affected households. Therefore, there is a need for countries to take step forward and develop intervention strategies that will help them to resolve the damage caused by the pandemic on the achieve the targets to end TB. This study could improve strategies implementation regarding the management of TB disease.
First Occurrence of the nonindigenous Asian foraminifera Ammonia confertitesta in the Northeastern Pacific Ocean: Vancouver Island, British Columbia, Canada
Authors: McGann Mary , Holzmann Maria
Published: March 2024

Observations in 2022 of intertidal and subtidal foraminiferal faunas at four localities along the central-eastern side of Vancouver Island, British Columbia, Canada, and molecular analyses have documented the first occurrence of the nonindigenous Asian species Ammonia confertitesta Zheng in the northwestern Pacific Ocean. The species was present at three of these localities: Davis Lagoon south of Ladysmith (4% in the lagoon and 49% on the beach) and 0.6% in Nanaimo Harbor. The vector of introduction is thought to be the release of ballast water and associated sediment. These releases probably occurred in the Port of Vancouver, which were then transported by means of the cyclonic circulation across the Strait of Georgia, or from local anchorages close to the sampling sites. The timing of the introduction is impossible to determine because no stratigraphic record is presently available. However, foraminiferal studies in the late 1980s near the Port of Vancouver that recovered calcareous taxa did not report the presence of this species, nor was it found at 33 sites sampled from 1997 to 1999 throughout the Strait of Georgia.
Retrospective Case Analysis on the Effectiveness of Boerhavia Diffusa Mother Tincture in the Management of Essential Hypertension
Authors: Sabarirajan S , Aayesha A
Published: March 2024

Background: Hypertension is a prevalent medical  condition with significant health implications.  This retrospective case record analysis aimed to  investigate the efficacy of Boerhaavia diffusa mother  tincture in managing hypertension. The study utilized  data from diverse healthcare settings affiliated with  Sivaraj Homoeopathic Medical College and Research  Institute, Salem. Methods: A total of 30 cases meeting the inclusion  criteria, comprising both sexes aged between 30 to 75  years, diagnosed with hypertension based on clinical  parameters (systolic BP >140 mmHg, diastolic BP  >90 mmHg), and presenting common symptoms,  were included. Exclusion criteria encompassed cases  of secondary hypertension and those with incomplete  follow-ups. The efficacy of Boerhaavia diffusa  mother tincture was assessed by changes in blood  pressure recorded during the treatment period. The  study adhered to ethical guidelines, and all patients  received Boerhaavia diffusa mother tincture as part  of their therapeutic regimen. Results and Discussion: Among the 30 cases  analyzed, 6 patients exhibited marked improvement,  10 demonstrated moderate improvement, and 10  showed mild improvement, while 4 cases showed  no improvement. Notably, the majority of patients  experienced marked symptomatic relief. Despite the  positive trend observed in the outcomes, the study  has limitations, including a small sample size and  the absence of a control group. The lack of detailed information on dosage and treatment duration  further restricts the generalizability of the findings.  The retrospective nature of the analysis introduces  potential biases, and confounding factors such as  lifestyle changes were not systematically addressed. Conclusion: This retrospective case record analysis  suggests a potential beneficial effect of Boerhaavia  diffusa mother tincture in managing hypertension.  The majority of patients experienced symptomatic  relief, although caution is warranted due to study  limitations. Future research, including well-designed  randomized controlled trials with larger sample  sizes, is needed to establish the efficacy and safety  of Boerhaavia diffusa mother tincture in hypertensive  patients.
The Utility of Upcoming Fish Models in Homoeopathy: A Scoping Review
Authors: Khachane Monica Nandkumar , Mukherjee Anupam , Arulmozhi S , Ghate Varsha Umesh
Published: March 2024

Background: Fish is the earliest, most prolific, and  most diversified class of vertebrates with around  34,000 species. Various species of fish have been used  as research models all around the world to provide  insights into intricate human genetics, anatomical  and physiological systems, and the pathophysiology  of human illnesses.  Aim: This study aimed to highlight experimental  studies of fish models in Homoeopathy using a variety  of evaluation parameters along with validated  analytical tools for traceable evidence.  Methods: The information was gathered for  preclinical research studying the impact of  Homoeopathic formulations on disorders in a variety  of fish, from a number of databases such as Scopus,  Science Direct, Web of Science, PubMed, Research  Gate, and Google Scholar.  Result: There were 30 publications in all that were  evaluated, and of them, 25 met the inclusion criteria  and were included in the scoping review. Conclusion:  The use of fish models in Homoeopathic research can  be considered to be valuable as it gives a versatile  approach that can significantly contribute to our  understanding of biology, disease, and environmental  science. Subsequently, the fish models enhance the  ability of researchers to make advanced discoveries  in various fields of study.
Homoeopathy in Covid 19 Sequelae: A Case of Telogen Effluvium
Authors: Singh Shweta
Published: March 2024

Hair loss is one of the most prevalent complaints in  patients shortly after being infected with Covid-19,  reported more commonly in women. The most  likely cause could be either the pathogenetic aspects  or psychiatric complications of Covid-19, which  can lead to the appearance or aggravation of hair  loss. Homoeopathy has a vital role to play in such  areas; where no specific therapeutic intervention is  available in modern medicine especially when the  disease is stress induced. Since Homoeopathy is the  only healing science that takes care of the patient  as a whole; the root cause, the physical and mental  state of the patient along with the disease symptoms  which individualizes the patient from one another  are the basis of accurate and effective homoeopathic  prescription. Following the cardinal principles,  significant improvement and recovery was seen in  such cases with homoeopathic remedies.
Role of Drug Remedies in Attention Deficit Hyperactivity Disorder (ADHD): A Case Series
Authors: Goyal Aditi , Singh Muktinder
Published: March 2024

Introduction: ADHD is the most common neurobe havioral disorder in children which comprises of 3  types: inattentive/hyperactive-impulsive/combined  type. There are varied drugs in homoeopathy belong ing to narcotic groups which seems to be effective in  these type of cases. These groups have various alka loids whose main sphere of action is on CNS or PNS  as stimulant, depressor or hypnotic.  Case summary: Here, 3 cases are presented with  different types of ADHD as diagnosed by Vanderbilt  Diagnostic Scale. In all these cases homoeopathic  drug remedies were prescribed on the basis of  totality of symptoms. Marked improvement in all the  cases substantiate the effectiveness of homoeopathy  especially drug remedies in these type of behavioural  problems when given constitutionally.
A High-Efficiency Satellite Image Classification Method for Real-Time Application Using Augmented Incremental Transfer Learning
Authors: Dr. Akshay Dhande
Published: March 2024

Researchers have put forth a range of models for processing satellite images, each with distinct data formats and processing requirements. One limitation arises from variations in the forms of modules, such as the image capturing and feature extraction modules, impacting accuracy and scalability in real-time scenarios. This passage introduces and explores a pioneering very competent temporal engine crafted specifically for classification of real-time satellite images. The proposed approach utilizes augmented incremental transfer learning, aiming to mitigate the limitations associated with diverse processing requirements. This approach involves capturing real-time satellite data through Google’s Earth Engine and subsequently processing it using a Convolutional Neural Network (CNN) based on transfer learning. The CNN employs backscatter coefficient analysis, utilizing coefficients derived from Precision Image's average intensity value across a distributed target. By integrating incremental learning and CNN for classification, the model achieves an impressive average accuracy of 98.06% in detecting crop type and severity of damage. Comparative analysis with state-of-the-art approaches reveals the superiority of the proposed model. It outperforms existing models by 5% in accuracy, showcasing its efficacy in satellite image processing and classification.
Ensemble Learning Model for Damage Detection Using Deep Convolutional Networks
Authors: Dr. Akshay Dhande
Published: March 2024

Damages to crops happen due to natural calamities, irregular fertilization, improper treatment, etc. To perform this estimation of this damage with high accuracy, both satellite & near-field images are needed. Satellite images assists in evaluation of damages due to natural calamities, while near-field images assist in evaluation of damage due to plant diseases. Separate models are designed for processing these images, which limits their correlative analysis; and thereby reduces overall accuracy of damage detection. To remove this drawback, this text proposes a deep convolutional network (DCN) design that integrates both near-field and far-field images in order to perform effective correlation. The model is trained for detection of areas which are infected by natural calamities, thereby assisting farm experts to undertake corrective measures based on specific area. Results of proposed model are compared with some of the recently developed state-of-the-art methods, and it is observed that the former model achieves 10% better accuracy, performance.
Ticketing at Ease
Authors: Prof. S. A. Gulhane  , Mohammad Uzef Javed Patel  , Shravani Subhash Kawale  , Mohammad Adnan Mohammad Ayaz  , Manjiri Subhash Dange
Published: March 2024

Transport Pass the Executives Framework the web application will deal with every one of the records of pass which is issue by transport authoritative. Transport Pass the Board Framework which is a programmed framework which conveying information handling in an exceptionally rapid in the precise way. This framework helps transport authoritative to track transport passes. Before this application the manual cycle used to do the course of the responsible the transport pass framework to the Explorer. Subsequently, The Old Framework Consume Such a lot of Time. This manual interaction requires labor supply and additional tedious to keep away from this trouble we carry out Transport Pass The board Framework. Transport pass the board framework is for understudies to help go through online Yet Not Restricted to Just understudies They Can Work for Any Age Gathering Individuals. Before this application execution the manual methodology is utilized to do the System of issue the transport pass to the understudies. To stay away from such challenges Very much Like It Require Parcel of Time and Endeavors So We Are Made a Framework That Take out Such a great deal Intricacies and Endeavors
Entendendo a desinformação: algumas determinações e uma proposta de conceituação
Authors: Santos Wérleson Alexandre de Lima , Pajeú Hélio Márcio
Published: March 2024

Objetivo: Realizar aproximações teóricas a respeito da desinformação tendo em vista suas relações com o capitalismo.
Metodologia: Pesquisa exploratória tendo como instrumento principal a pesquisa bibliográfica, e como norte epistemológico o materialismo dialético. Realiza uma investigação teórica que visa contribuir para um entendimento geral sobre desinformação, aplicando uma visão materialista que tem base em teorias marxistas e bakhtinianas, além das contribuições dos estudos de autores da Ciência da Informação como Capurro, Buckland e Dantas. Trata de questões envolvendo as estratégias de dominação burguesa, em especial de forma discursiva por meio da formação de consenso através da perpetuação de ideologias materializadas em gêneros discursivos.
Resultados: Traz determinações basilares para a compreensão da desinformação envolvendo seu teor e sua forma de atuação; aponta três níveis de circulação nas dimensões da infraestrutura e da superestrutura, além de elencar tipologias e dimensões de manifestação, propondo sua conceituação enquanto um fenômeno material.
Conclusões: O combate à desinformação vai muito além de combater informações falsas e isso demanda articulações teóricas e práticas mais complexas que envolvem o funcionamento da sociedade como um todo
Análise dos planos de gestão de universidades Brasileiras e Portuguesas: uma investigação das políticas de acessibilidade e inclusão para as bibliotecas universitárias
Authors: Lima dos Santos Ana Paula
Published: March 2024

Objetivo: A alta incidência de pessoas com deficiência é uma questão global que preocupa a criação de políticas. O artigo tem como objetivo analisar os planos de desenvolvimento institucional de universidades no Brasil, a Universidade Federal Fluminense (UFF) e a Universidade Federal do Rio de janeiro (UFRJ) e em Portugal, a Universidade do Porto e a Universidade de Lisboa para verificar se há políticas direcionadas à inclusão social de pessoas com deficiência, bem como se há menção da biblioteca universitária nesses planos.
Método: A metodologia utilizada é a revisão de literatura seguida de análise de conteúdo de Bardin (2009).
Resultado: Discute a preocupação com a inclusão e permanência dessas pessoas no ensino superior tanto no Brasil quanto em Portugal. Estudos sobre Regime de Informação na Ciência da Informação enfatizam a inclusão de grupos socialmente excluídos.
Conclusões: Conclui que os planos de desenvolvimento institucional incorporaram ações voltadas à acessibilidade e inclusão, incluindo orientações para que as bibliotecas sejam inclusivas em todas as esferas de acessibilidade. Nota-se que as políticas institucionais são a melhor forma de incluir pessoas em situações de vulnerabilidade social.
Método para avaliação direta da indexação automática via julgamento por indexadores
Authors: Correa Renato Fernandes , Fujita Mariângela Spotti Lopes
Published: March 2024

Objetivo: Com a finalidade de avaliar um sistema de indexação automática aplicado a e-books, este trabalho propõe e aplica um método para avaliação direta da indexação automática via julgamento por indexadores, quanto à qualidade dos termos de indexação atribuídos automaticamente aos documentos.
Método: Realizou-se uma pesquisa metodológica de natureza descritiva e aplicada, utilizando-se procedimentos técnicos da pesquisa bibliográfica e pesquisa empírica. Inicialmente, por meio de revisão de literatura, delimitaram-se as etapas do método proposto de avaliação direta da indexação automática via julgamento por indexadores, para depois proceder à construção de instrumento para coleta de dados e aplicação do método proposto na avaliação da indexação automática do sistema SISTRA, na indexação de e-books técnicos-científicos.
Resultado: O método proposto de avaliação é apresentado através de diagrama e descrição de etapas. O método consiste, primeiramente, no julgamento por indexadores da qualidade dos termos atribuídos pelo sistema de indexação automática a uma amostra de documentos digitais e, posteriormente, na análise de valores calculados para métricas de qualidade da indexação automática. A aplicação do método proposto se mostrou útil numa primeira avaliação de um sistema de indexação automática.
Conclusões: Conclui-se que o método proposto de avaliação direta da indexação automática via julgamento por indexadores propicia a padronização da avaliação e sua prática por profissionais da informação, e que a avaliação direta é uma atividade necessária para a aplicação e a adoção da indexação automática na indexação por assunto de documentos digitais, no âmbito das unidades de informação.
Comparative Analysis of Sentiment in Original and Summarized Tweets: Leveraging Transformer Models for Enhanced NLP Insights
Authors: Bu Kun , Ramachandran Kandethody
Published: March 2024

This paper investigates the sentiments of Twitter users towards the emergent topic of ChatGPT, leveraging advanced techniques in natural language processing (NLP) and sentiment analysis (SA). Our approach uniquely incorporates a dual setting for sentiment analysis: one analyzes the sentiments of original, full-length tweets, while the other first condenses these tweets into succinct summaries before performing sentiment analysis. By employing this dual approach, we are able to offer a comparative analysis of sentiment assessment pre- and post-text summarization, exploring the accuracy and reliability of the summarized sentiments. Central to our methodology is the application of Transformer models, specifically ProphetNet, which facilitates a deeper and more nuanced understanding of the original text. Unlike traditional methods that rely on keyword extraction and aggregation, our approach generates coherent and contextually rich summaries, providing a novel lens for sentiment analysis. This research contributes to the field by presenting a comprehensive study comparing sentiment analysis outcomes between original texts and their summarized counterparts, and examining the effectiveness of different NLP techniques, namely NLTK and the Transformer-based ProphetNet model. The findings offer valuable insights into the dynamics of sentiment analysis in the context of social media and the efficacy of state-of-the-art NLP technologies in processing complex, real-world data.
Originlens: A Real-Time AI-Generated Text and Plagiarism Detection using Deep Learning and Augmented Reality
Authors: Liu Henry Muyang , Do Jenny
Published: March 2024

ChatGPT has integrated itself into the academic space in an unprecedented timeframe, as the promise of hours of work done in seconds can outweigh the sense of honor and logic. This project determines whether a student is cheating or not by reducing the presence of human decision-making while simultaneously acting as a deterrent for future usage of AI technology. Utilizing databases such as Kaggle, we can procure several samples of human writingin conjunction with ChatGPT's API to generate artificial intelligence instances, which are then stored for usage in machine learning algorithms. Employing powerful Python libraries such as Sklearn and NLTK, we can utilize natural learning processing, the ability for computers to understand human writing, to yield an algorithm that can predict with approximately 96% certainty. The result is a probability ratio, with one side displaying the percentage chance of the sample being human-written, whereas the other displays the likelihood of AI-generated instances. Furthermore, innovation lies in integrating this algorithm with wearable augmented reality technology, allowing usersto efficiently scan and assess text elements. This approach amalgamates and helps reduce the delay between text input and response, empowering users to contribute to the decision-making process in identifying academic dishonesty without any loss in efficiency. The result that is shown displays pieces of information to the user that can all play a large role when determining the possibility of cheating, granting the user a role in making the decision along with simple scanning of each text element.
Value of Purchase Prediction using Machine Learning Algorithms
Authors: Egbuna Fidelis , Omerenna Chukwuemeka
Published: March 2024

The aim is to analyze the sales of a supermarket as well as predict the impact of future sales on profit increase andcustomers satisfaction in the organization. The technique used for value of purchase is Linear Regression Algorithm,a widely acclaimed Algorithm in the field of Machine Learning. Linear Regression was compared with K- Nearest Neighbors Algorithm as well as with Gradient Descent and Random Forest. The actual data of the year, 2019, was compared to the predicted value and the accuracy of prediction calculated. The results testify to the trustworthiness and accuracy of the different prediction algorithms used. The study showed Random Forest as the best model with the prediction's highest accuracy. Random forests accuracy rate based on multiple decision trees and prediction taken from average output from various trees; generalized well and achieved a higher accuracy of 94% than other models.
An Intelligent DDoS Detection System to recognize and Prevent DDoS Attacks using Artificial Intelligence and Machine Learning
Authors: Li Xiangfeiyang , Thamrun Jonathan
Published: March 2024

In response to the increasing threat of DDoS (Distributed Denial of Service) attacks, this project investigates fortifying defenses against such malicious invasions. The project incorporates a user-friendly UI featuring two buttons: one for uploading captured traffic files and another for analysis to classify whether it’s a DDoS attack. The background of the problem aspires to a robust and adaptive DDoS detection system to ensure the continuity of online services [14]. To resolve this, the project proposes an automated DDoS attack detection mechanism powered by Machine Learning and Artificial Intelligence. The application involves two pivotal experiments: the first assesses model accuracy, highlighting the Decision Tree as the most promising, while the second focuses on preventing overfitting during training, and the Random Forest Classifier stands out to this one [15]. The challenges encountered were mitigated through techniques like early stopping and regularization. The model’s application across various scenarios showcased its potential for effective real-time DDoS detection.
An Optimized Writing Efficiency Tool with Integrated Gamification and Work Interval Timer for Enhanced Essay Productivity and AI Advice
Authors: Shen Summer , Andaya Moddwyn
Published: March 2024

both productivity and writing quality. Students often struggle with overwhelming tasks, slow progress, and lack of motivation during the writing process. Our proposal combines the Pomodoro Technique, gamification, and an AI-powered writing quality checker to offer a holistic solution [8]. The Pomodoro Technique breaks down tasks, while gamification elements, including a playful chicken character, make writing enjoyable. An AI-based writing quality checker provides real-time feedback on grammar, sentence structure, and clarity [9]. Challenges, such as balancing interactivity and efficiency, were addressed through thoughtful design decisions. Experimentation involved applying the application to various writing scenarios, showcasing its adaptability. Results demonstrated enhanced productivity, improved writing quality, and increased user satisfaction. This comprehensive approach addresses the shortcomings of existing methodologies and provides users with a valuable tool to navigate the challenges of essay writing efficiently and effectively.
SAMURAI：A Transformation System for Animation Characters based on GLCIC to Alleviate the Workload of Animation Directors
Authors: Tsukiyama Takuto , Ooi Sho , Sano Mutsuo
Published: March 2024

People from various professions are involved in the production of anime, including directors, animation directors, character designers, and voice actors/actresses. Specifically, the role of an animation director is of importance in the realm of animation. The animation director serves as the unifying force in shaping the animation's style by meticulously reviewing and redrawing the key animations provided by the key animators. The aim of this study is to develop a redrawing system using GLCIC to reduce the workload on animation directors when redrawing original key animation. Specifically, this study devised a system that employs GLCIC to analyze and learn the distinctive drawing styles of individual animation directors from images of their work and subsequently apply those styles to the conversion process. In the experiment, we asked people whose hobby is drawing to experience the developed system, and conducted a qualitative evaluation using a questionnaire and a quantitative evaluation using KLM analysis. As a result, we found that there were issues with ease of modification and UI. Additionally, the KLM analysis revealed that improving the system could reduce work time by a quarter. In the future, we think to improve the system with the aim of increasing work efficiency.
Parafusion: A Large-Scale LLM-Driven English Paraphrase Dataset Infused with High-Quality Lexical and Syntactic Diversity
Authors: Jayawardena Lasal , Yapa Prasan
Published: March 2024

Paraphrase generation is a pivotal task in natural language processing (NLP). Existing datasets in the domain lack syntactic and lexical diversity, resulting in paraphrases that closely resemble the source sentences. Moreover, these datasets often contain hate speech and noise, and may unintentionally include non-English language sentences. This research introduces ParaFusion, a large-scale, high-quality English paraphrase dataset developed using Large Language Models (LLM) to address these challenges. ParaFusion augments existing datasets with high-quality data, significantly enhancing both lexical and syntactic diversity while maintaining close semantic similarity. It also mitigates the presence of hate speech and reduces noise, ensuring a cleaner and more focused English dataset. Results show that ParaFusion offers at least a 25% improvement in both syntactic and lexical diversity, measured across several metrics for each data source. The paper also aims to set a gold standard for paraphrase evaluation as it contains one of the most comprehensive evaluation strategies to date. The results underscore the potential of ParaFusion as a valuable resource for improving NLP applications.
Domain Adaptation Regularized LayoutLM with Automatic Domain Discovery from Topic Modelling
Authors: Lin Chen , Singh Piush Kumar , Xu Yourong , Lees Eitan , Saxena Rachna , Donaparthi Sasidhar , Su Hui
Published: March 2024

In this paper, we propose using domain adaptation to improve the generalizability and performance of LayoutLM, a pre-trained language model that incorporates layout information of a document image. Our approach uses topic modelling to automatically discover the underlying domains in a document image dataset where domain information is unknown. We evaluate our approach on the challenging RVL-CDIP dataset and demonstrate that it significantly improves the performance of LayoutLM on this dataset. Our approach can be applied to other NLP models to improve their generalization capabilities, making them more applicable in real-world scenarios, where data is often collected from a variety of domains.
An Internet-of-Things (IoT) Sustainable Water Filtering and Monitoring System using Big Data Analysis and Clean Energy
Authors: Yuan Kaining , Sahagun Jonathan
Published: March 2024

Microplastic contamination in freshwater ecosystems is a growing environmental concern. This paper introduces MyRiiver, a solar-powered microplastic filtration system, designed to overcome limitations in current methods. The background underscores the urgency of addressing microplastic pollution, emphasizing the need for an efficient, adaptable, and economical solution. MyRiiver employs a sophisticated multi-layered filtration system without requiring pre-treatment, offering advantages over existing methodologies. Challenges identified in previous approaches, such as electrode wear and biofilter maintenance, are addressed through the simplicity of MyRiiver's design. Experimental trials showcase its adaptability and superior efficiency in filtering microplastics as small as 1 µm. Results demonstrate a significant removal rate, positioning MyRiiver as a practical, scalable, and eco-friendly solution. The study concludes by asserting MyRiiver's potential as a transformative tool for combating the escalating global issue of microplastic contamination in freshwater environments.
An Educational Platform to Enhance Financial Literacy using Multiplayer Interaction and Innovative Game Mechanics
Authors: Xu Zinuo , Mirzaee Soroush
Published: March 2024

This paper addresses the gap in financial literacy education for teenagers by introducing Landlord Legends, an innovative multiplayer video game designed to impart essential skills in property and money management [1][2]. Grounded in the recognition of underutilized potential in video games for education, the project draws inspiration from the diverse methodologies discussed in "Video Games in Education,""Using a Financial Education Curriculum for Teens," and "How Multiplayer Games Increase Social Closeness." [3] Landlord Legends provides an engaging platform for teenagers to learn and apply financial concepts while fostering social interaction. The challenges in dice interpretation and multiplayer system selection were overcome through meticulous design and research [4]. Experimental results showcased the game's effectiveness, yielding increased financial literacy scores and positive participant feedback. Landlord Legends demonstrates the fusion of educational content and gaming, offering a dynamic and enjoyable approach to financial education that addresses challenges faced by teenagers, making it a valuable tool for enhancing financial literacy [5].
An Intelligent Plant and Animal Identification Mobile Application for Increased Biodiversity Awareness and Safety using Machine Learning
Authors: Xiao Austin , Li Ang , Bodle Wyatt
Published: March 2024

Dangerous animal encounters have steadily increased over time and consumption of deadly plants is an important issue [12]. Our paper introduces a new mobile application that addresses the critical need for accurate animal and plant identification and classification to help mitigate safety risks for humans.With up to five million animal attacks reported every year in the United States alone, and over 100,000 cases of toxic plant exposure there is a need and a responsibility to increase awareness of the risks associated with animal and plant ignorance.Our proposed app utilizes innovative classification technologies, offering our users a swift and simple identification of both select plant and animal species.The app will relay information about the potential dangers and general facts about the classified animal [14].This will help our users to understand the environment they live in and to best prepare themselves against it.Some challenges with this proposal are curating a broad and efficient dataset, there are estimated to be eight million eukaryotic species which is unattainable for one dataset.We then had to decide which valuable information would be best to present without providing unwanted distractions in our user interface.We utilized Google Firebase to ensure secure authentication and data storage while using TensorFlow Lite to power the image classification.We then integrated all of this into flutter to create a friendly user interface and application that can run on both iOS and Android [15].Once our app was complete, we ran two experiments, one to test the accuracy of our classifications in plants and animals and another to test the effect of lower resolution images on classification accuracy.The experiments shed light on challenges and potential improvements for the application to help improve its efficiency as a tool for users to enhance their awareness, safety and understanding of the environment they live in.
A Comprehensive Review of Interactive System Architecture
Authors: Mohammed Mohammed Swaleh
Published: March 2024

This paper presents a detailed review of interactive software architecture (ISA). ISA has emerged as an important aspect in software engineering offering a framework that prioritizes user interaction, real-time responsiveness and adaptability. The paper explores various aspects crucial for the design, development, and maintenance of robust and scalable software systems. The review encompasses architectural patterns, design principles, scalability, maintainability, security, and emerging trends. The paper also examines the significance of ISA and challenges for the same. Objective: The objective of the paper is to provide a comprehensive understanding of the key considerations in interactive system architecture and how they impact the overall success of a software project. The paper also goes on to discuss the challenges and benefits of implementation of ISA Methodology: the study adopted a desktop approach by reviewing existing literature on the topic at hand so as to provide a simplified understanding of the interactive system architecture. Recommendations: at the end of the paper it provides recommendation on future developments in this field.
Yaşantısal ve Çözüm Odaklı Aile Terapisi Bakış Açısıyla “Bizi Hatırla” Film Analizi
Authors: Taşdelen Karçkay Arzu , Toprak Begüm , Alkan Derya
Published: March 2024

Filmlerin, aile psikolojik danışmanlığı oturumlarında bir araç olarak ve aile danışmanlığı eğitiminde ise bir öğretim materyali olarak kullanıldığı görülmektedir. Dolayısıyla farklı yaklaşımlarla incelenen film analizi çalışmalarının zengin bir kaynak oluşturduğu söylenebilir. Bu makalede yazarlar, 2018 yılında Türkiye’de vizyona giren senaristliğini ve yönetmenliğini Çağan Irmak’ın yaptığı “Bizi Hatırla” filmini yaşantısal aile terapisi ve çözüm odaklı aile terapisi bakış açısıyla incelemişlerdir. Filmin analizi için yazarların her biri tarafından 24 sahne seçilmiş, bu seçim sonucunda ortak kararın alındığı 22 sahne incelenmiştir. Ele alınan kuramlara ait temel kavramlar açıklanıp uygun sahnelerle eşleştirilmiştir ve bu kavramlar somutlaştırılmıştır. Çalışma sonucunda, çözüm odaklı kısa süreli aile terapisi ve yaşantısal aile terapisi kavramları bağlamında değerlendirilen ‘’Bizi Hatırla’’ filminin yaşantısal aile terapisi ve çözüm odaklı aile terapisi bakış açısıyla aile psikolojik danışmanlığına etkili bir öğretim materyali olabileceği düşünülmektedir. Bu bağlamda çalışma, aile psikolojik danışmanlığı, gelişim psikolojisi, kariyer danışmanlığı alanlarında öğretim materyali ve aile psikolojik danışmanlığı oturumlarında bir araç olarak kullanılabilir.
Human Resource Management in Times of Economic Uncertainty: Lessons from Financial Crises.
Authors: Christine Osinde , Atandi Dr Fred Gichana
Published: March 2024

This scholarly paper examines the collection of empirical studies on human resource management during crisis situations. It encompasses research conducted both before the onset of the COVID-19 pandemic and studies published in the aftermath of the pandemic's outbreaks. Thefindings point to the significance of Human Resource Management (HRM) in guiding organizations through times of economic instability. It extracts valuable lessons from previous financial crises to underscore the crucial human resource management significance in sustaining business operations, strengthening resilience, and fostering enduring success. Finally, a conclusion is presented.
Ethical Implications and Governance of Artificial Intelligence in Business Decisions: A Deep Dive into the Ethical Challenges and Governance Issues Surrounding the Use of Artificial Intelligence in Making Critical Business Decisions
Authors: Oladele Ifeoluwa , Orelaja Adeyinka , Akinwande Oladayo Tosin
Published: March 2024

This paper focuses on governance frameworks as a means of addressing the pressing need to identify ethical challenges surrounding the applications of artificial intelligence (AI) in making critical business decisions, to help businesses navigate the ethical issues of AI-driven decision-making. The study employs a qualitative methodology to investigate current literature, assess regulatory frameworks, examine case studies from the real world, and suggest moral guidelines to address ethical dilemmas and governance concerns in AI applications.Results point to a variety of problems, including algorithmic biases, data storage procedures, and AI-powered business decisions. The study places a strong emphasis on moral issues, which is consistent with responsible AI development. Assessing regulatory environments, the research pinpoints opportunities for enhancement and efficiency. The recommendations emphasize the continued significance of ethical issues in AI and promote public awareness, developer accountability, user empowerment, and stringent regulations. The recommendations prioritize societal well-being and individual privacy to encourage the responsible deployment of AI.Therefore, to navigate the complex intersection of AI and privacy, researchers, policymakers, developers, and users can benefit substantially from the insights provided by this research.
Spiritual Retreats: Implications for Practical Christian Living
Authors: Yalley Doris E. , Yalley Ebenezer
Published: March 2024

Spiritual retreats have a long history steeped in religious tradition and generally involve a separation from everyday life and entering into a new temporary experience. Retreats have been a means of help for people in all spheres of life, providing favour able outcomes such as spiritual growth and restoration. This study utilized Attention Restoration Theory and Activity, Setting, Experience and Benefit (ASEB) framework to explore the implication of spiritual retreat activities and experiences on Christian growth indicators, i.e., in the areas of establishing a deeper relationship with God, gaining a fuller understanding of self, applying personal faith in troubling life situations, and finding fulfilment in reaching out to fellowship with others. Data from 115 study participants were analysed using a mixed-method approach and demonstrated evidence of the beneficial effects of spiritual retreats on Christian growth. Spiritual retreats were shown to have a significant and beneficial impact on participants’ Christian growth, particularly in the areas of abiding in Christ, living by the Bible and biblical principles, growing in faith and prayer, fellows hipping with other Christians, and service to God. The practical and theoretical implications of the findings of the study for pastors, church leaders, retreat centre facilitators as well as the general Christian community are also discussed.
Odevixibat (Bylvay)
Authors: CADTH
Published: March 2024

CADTH recommends that Bylvay should be reimbursed by public drug plans for pruritus (itching) in patients aged 6 months or older with progressive familial intrahepatic cholestasis (PFIC) if certain conditions are met.

Bylvay should only be covered to treat patients aged 6 months or older who have been diagnosed with PFIC type 1 (PFIC1) or PFIC type 2 (PFIC2), have severe itching, and have elevated serum bile acids. The first time Bylvay is prescribed, it should be for a trial period of 3 months to ensure that it improves the patient’s itching before it is renewed.

Bylvay should only be reimbursed if it is prescribed by specialists in managing PFIC, if patients experience an improvement in their itching after using Bylvay for 3 months, and if the cost of Bylvay is reduced. Bylvay should be stopped if the patient receives a liver transplant.