bluuebunny/crossref_metadata_2025 huggingface dataset:
Perspectives of parents and caregivers about vaccination during COVID-19 pandemic: An online cross-sectional study
Authors: Arunnair Vijayamathy , S Bhuvaneshwari , T Sathiya , S Umamageswari , Mutalik Anirudh , Selvamalar Jerliya
Published: December 2024

Background:
The most economical preventive health measure to safeguard youngsters from vaccine-preventable diseases, ensure a disease-free future, and prevent socio-economic disasters is immunization. The COVID-19 pandemic led to a major backslide in childhood vaccinations. Hence, it is important to assess the parental knowledge, attitudes, and practices (KAP) towards childhood vaccination amid the prevailing pandemic.

Aim:
This study evaluated the KAP of parents and caregivers about immunization.

Methods:
A prospective cross-sectional online questionnaire (Google Form) based study was done using convenient sampling among 105 parents and caregivers at a tertiary care hospital in Coimbatore for 6 months. Descriptive and inferential statistics (ANOVA, chi-square, Pearson correlation test, and unpaired t-test) were used. The results were depicted in terms of numbers and percentages. The data obtained was evaluated using Statistical Package for the Social Sciences, version 28 for Windows.

Results:
The mean KAP scores of parents/caregivers about vaccination were 4.99 ± 2.05, 10.63 ± 2.28, and 6.67 ± 1.77 respectively. 61.9%, 58.1%, and 52.4% had good KAP scores respectively. Participants' knowledge and attitude showed a positive correlation (P<0.032), however, there was no significant relationship between knowledge and attitude with practice. Urban residents and employed respondents had better attitude and practice scores than rural (P<0.029) and unemployed (P<0.033) correspondingly.

Conclusion:
The population under investigation had a good level of KAP; nevertheless, a gap was noticed in practice. Enhancing the study population's awareness through educational campaigns and effective communication could help overcome these obstacles and ensure adequate immunization practices.
EPILEPTIC SEIZURE DETECTION FROM EEG SIGNALS WITH RECURRENT NEURAL NETWORKS BASED CLASSIFICATION MODEL
Authors: Aslan Serpil , Bingöl Harun
Published: December 2024

Epileptic seizures are a neurological disorder that occurs as a result of sudden and uncontrolled electrical activities of the non-contagious brain. This condition may cause the person to lose normal activities temporarily. Epileptic seizures are a severe disease that affects approximately 60 million people in the world, usually manifested by symptoms such as loss of consciousness, muscle twitching, sudden sensory changes, or behavioural changes [1]. Genetics, brain injury, hormonal fluctuations, infections, or metabolic problems are some of the possible causes of epileptic seizures. Although the severity and duration of the seizure varies from person to person, it is usually very short and rarely reaches a point where it endangers human life. However, such seizures need to be recognized as soon as possible in order to improve the quality of life of individuals and reduce the frequency of seizures. Epileptic seizures are a manageable disease with early diagnosis and appropriate treatment. Recognizing epileptic seizures begins with understanding a person's symptoms and triggering factors. These symptoms may include loss of consciousness, muscle twitches, sudden sensory changes, and behavioural changes. The symptoms of seizures, past medical history, and neurological examinations are essential in the diagnosis process. From past to present, many methods have been developed for the early diagnosis and detection of epileptic seizures [2]. One of these is analyzing the brain's neural activities using electroencephalography (EEG), which helps experts make a diagnosis. Although EEG signals are used as a powerful tool in epileptic seizure recognition, distinguishing the signals within them is both costly and requires highly expert experience. Therefore, this study proposed an automatic classification model for pre-processed EEG signals using Dual-Tree Complex Wavelet Transform (DT-CWT) based on deep learning-based Recurrent Neural Networks (RNN) architecture to assist experts. Compared to classical machine learning methods, deep learning-based models require less manual feature engineering because they perform data automatically thanks to deep networks instead of manually selecting and transforming the data features. These advantages make the model more general and flexible. The proposed model aims to classify EEG signals and detect epileptic seizures effectively and quickly in the early stages.
A review on the effect of alloying element on physical properties of Cu-Al-Mn Magnetic Shape Memory Alloy Material
Authors: Mohammed Safar Saeed , Qadir Rezhaw Abdalla , Karim Ayoub Sabir , Kök Mediha
Published: December 2024

One of the best type of smart materials is magnetic shape memory alloy due to their unique combination of magnetic and shape memory properties that this combination of these two properties has given them the opportunity to have more applications in modern technology than many other types of materials. Among all types of magnetic shape memory alloy materials Cu-Al-Mn alloy is more focused on by researchers and scientists because it has some unique properties. Also, the behaviors of Cu-Al-Mn alloy can improve by some techniques, one of these techniques is adding the fourth element into it. In this study the structure and some important properties of Cu-Al-Mn magnetic shape memory alloy material was studied and the effect of adding element by alloying process on the behaviors of Cu-Al-Mn magnetic shape memory alloy material such as transformation-temperature, grain size, superelastisity, and hardness has been reviewed.
Silver Nanoparticle Morphology Control via Fruit Juice: A Comprehensive Review
Authors: Abdulkareem Karzan , Omer Rebaz , Mahmood Karzan , Abdullah Fuad
Published: December 2024

This review examines the impact of fruit juice on the morphology of silver nanoparticles. Fruit juice contains reducing agents that can be useful in synthesizing nanoparticles, potentially affecting their shape. The review also discusses the method of synthesizing silver nanoparticles using fruit juice as the reducing agent and the various characterization techniques used to determine their morphology. The results indicate that fruit juice plays a crucial role in controlling the shape of silver nanoparticles. Factors such as the type of fruit, concentration, mixing time, pH, ratio of silver nitrate, and temperature can influence the final size and shape of the nanoparticles. These findings suggest that using fruit juice as a reducing agent in nanoparticle synthesis can be a promising approach for manipulating their morphology. This review introduces new possibilities for the application of nanoparticles in healthcare, electronics, and catalysis.
A Hybrid Method Based On A Genetic Algorithm That Uses Network Packets To Classify Spyware
Authors: Kılıç İrfan , Yaman Orhan , Erdoğan Edanur , Aslan Melisa İrem
Published: December 2024

The emergence of the Internet has led to the emergence of cyber-attacks and malware. Malware installed on mobile devices, including computers, phones, and tablets, can be used by attackers to access users' data. This study aims to use decision trees (DT) and genetic algorithms (GA) using a meta-heuristic approach to detect spyware, a category of malware, by analyzing network packets in a Windows operating system environment. When the literature is examined, it is noteworthy that there is a lack of studies on the detection of spyware using network packets. This situation was the driving force for this study. In order to carry out the study, an experimental environment was created by utilizing the laboratory facilities of Firat University, Faculty of Technology, Department of Forensic Informatics Engineering. In this experimental environment, various network packets were collected using different spyware applications. The data set was subjected to feature extraction using Tshark software. The effectiveness of meta-heuristics compared to the mathematical method of neighborhood component analysis (NCA) is demonstrated on the benchmark dataset. Therefore, a genetic algorithm (GA) was used to select the most weighted features among the extracted features. The selected features were classified with the decision tree (DT) algorithm. The results obtained are at the desired level for future studies.
Machine Learning Methods in IoT Based Embedded Systems for Classifying Physical Faults in Water Distribution Networks
Authors: Kılıç İrfan , Yaman Orhan , Saylan Şeyma , Hörgüşlüoğlu İlayda , Demirelli Betül
Published: December 2024

Water is the most important factor for the survival of living things on Earth. Although 70% of the Earth is water, the amount of drinkable water is approximately 0.3%. Therefore, creating a sustainable water policy and carrying out studies are very important for our world and our future. Most of the potable water resources are physical losses. In the evaluations made based on metropolitan municipalities, it was seen that the water loss rate was approximately 50%. The study aims to find water pipe faults using IoT (Internet of Things) based machine learning classifiers to prevent physical losses in water distribution networks. Within the scope of this study, an experimental environment was created and an IMU (Inertial Measurement Unit) sensor was fixed on plastic pipes of different diameters and lengths. Vibration data collected in different scenarios (pressure, etc. factors) were transferred to the ThingSpeak platform over the internet. The transferred data could be monitored in real-time on a server. Physical damage in the pipes was detected using signal pre-processing, feature extraction, and feature selection algorithms on vibration data. In the study, damages were classified using machine learning-based classification (Decision Trees, k-Nearest Neighbors, Linear Discriminant, Support Vector Machines) methods to predict the type of damage (solid, hole, multi-hole). The data set revealed within the scope of the study is thought to lead to scientific studies in this field. The results obtained are close to the state-of-the-art results.
Empirical Analysis of Judicial Cases on Employment Termination Due to Work Incompetence
Authors: Yunhua Li
Published: December 2024

The Labor Law of the People's Republic of China sets many restrictions on employers' unilateral termination of labor contracts. Termination due to work incompetence is the most common scenario in enterprises' "difficulty in contract termination".In labor disputes arising from termination due to work incompetence, employers have a relatively high rate of losing cases, mainly because the legal characterization of "work incompetence" is unclear, identification standards are ambiguous, and termination procedures are complex. Analysis of judicial big data and individual cases shows that the main reason for employers losing cases is their inability to provide sufficient evidence to prove "incompetence" and the ineffectiveness and unreasonableness of training and job transfers. When terminating employment due to work incompetence in enterprise management, employers should pay attention to the objectivity of evidence, legality of procedures, effectiveness of training, and reasonableness of job transfers to avoid the risk of illegal termination.
PLANO DE CONTAS APLICADO AO SETOR PÚBLICO: UMA FERRAMENTA PARA PROMOÇÃO DA TRANSPARÊNCIA E CONTROLE SOCIAL
Authors: Silva Anderson Ferreira da , Vargas Kelvyn de Aquino , Pacheco Luiz Felipe Freitas , Andrade Adriano Mello de
Published: December 2024

A evolução da contabilidade no setor público ressalta a necessidade de melhorias na gestão e na transparência, refletindo um aumento do interesse da sociedade pelo uso de recursos públicos. Leis como a Lei de Responsabilidade Fiscal e a Lei de Acesso à Informação foram criadas para fomentar a transparência e o controle social. Diante do exposto, o presente estudo propõe apresentar os benefícios do plano de contas na promoção da transparência e no fortalecimento do controle social, visto que o acesso a informação compreende-se pelo principal fator sobre a participação popular acerca das decisões públicas. O objetivo do artigo alça sobre a apresentação clara e objetiva da contabilidade para as entidades públicas, bem como a utilização do plano de contas como ferramenta para incentivo ao controle social e a importância da legislação para uma administração pública mais transparente, abordando a relevância da gestão de recursos e informações sobre gastos públicos.
QUALIDADE BROMATOLÓGICA DA SILAGEM DO CAPIM BRS CAPIAÇU COM O USO DE ADITIVOS SOB DIFERENTES INTERVALOS DE CORTE
Authors: Aguirre Priscila Flôres , Demarco Igor Roberto , Binsfeld Lucas Alfredo , Guzatti Gabriela Cristina
Published: December 2024

O capim-elefante, cv. BRS Capiaçu, possui alto potencial produtivo, vindo de encontro a necessidade de produção de alimento volumoso para ruminantes, entretanto, seu baixo nível de matéria seca, pode resultar em baixa qualidade de fermentação da silagem. Assim, objetiva-se avaliar a composição bromatológica de silagem de BRS Capiaçu ensilado em diferentes intervalos de crescimento e com uso de aditivos. A silagem foi acomodada em micro silos por 60 dias, após a abertura foram analisados o nitrogênio amoniacal, pH, teores de matéria seca, proteína bruta, fibra em detergente neutro e ácido. O delineamento experimental utilizado foi o inteiramente casualizado, com arranjo fatorial 2x3, sendo dois intervalos de crescimento do capim (70 e 110 dias) e três manejos na ensilagem (sem aditivos; com inoculante bacteriano e 10% de milho moído), com quatro repetições. Para o pH as silagens sem uso de aditivo e com inoculante, cortadas aos 70 dias, apresentaram os maiores valores, de 5,2, os menores valores foram encontrados nas silagens com 110 dias, com uso de milho moído e inoculante, de 3,9 e 3,8, respectivamente. Os menores valores de nitrogênio amoniacal, FDN e FDA, foram encontrados nas silagens com adição de milho moído, 5,9; 38,0 e 27,4%, respectivamente, já para os teores de MS e de PB estas apresentaram os maiores valores, 24,4 e 11,6%, respectivamente. A utilização de aditivos melhora a qualidade e a conservação das silagens produzidas com BRS Capiaçu, em especial a adição de milho moído, combinado a idade de 110 dias de rebrota.
Sosyal Medya Etkileyicilerinin Reklamlarına Karşı Açılan Davaların Medeni Usul Hukuku Perspektifinden Değerlendirilmesi
Authors: Kaya Serkan , Havan Muhammet Emirhan
Published: December 2024

Sosyal medya platformlarının yaygınlaşması tüketici davranışlarını yeniden şekillendirmiş, kullanıcılar satın alma kararlarında sosyal media etkileyicilerinin tavsiyelerine giderek daha fazla güvenir hale gelmiştir. Bu güven, sosyal medya etkileyicilerinin ürün ve hizmetleri onaylayarak itibarlarından para kazandıkları yeni bir pazarlama paradigmasına yol açmıştır. Son yıllarda, kullanıcıları sosyal media etkileyicilerin yapmış olduğu aldatıcı reklam uygulamalarından korumak için düzenlemeler yapılmış olsa da, bu modelin medeni usul hukuku açısından değerlendirilmesi ihtiyacı devam etmektedir. Bu çalışmada sosyal medya etkileyicilerinin hukuki niteliği ve bunların reklam verenlerle ilişkileri değerlendirildikten sonra aldatıcı reklamlara karşı açılabilecek haksız rekabet davaları, tüketici davaları ve fikri mülkiyet davaları ele alınmaktadır. Açılabilecek davalar için potansiyel talepler, ilgili taraflar ve görevli ve yetkili mahkemeler incelenmekte ve karşılabilecek hukuki sorunlar ele alınmaktadır.
Predictive Analysis of Employee Turnover: A Comprehensive Model for Attrition Forecasting
Authors: C M Likith Kumar , Ajitha Dr. S , K J Ms Reshma
Published: December 2024

Employee attrition has become a critical concern for organizations seeking to maintain a stable workforce
and minimize turnover-related costs. This study aims to develop a predictive model to forecast employee attrition
by analyzing key factors influencing turnover. The research investigates a range of variables, including push factors
(e.g., job dissatisfaction, workplace conflict), pull factors (e.g., external job opportunities), organizational factors
(e.g., leadership, culture), and external factors (e.g., economic conditions). The data is collected via a structured
questionnaire through Google Forms, which captures responses related to these influencing factors.Using advanced
machine learning techniques, this study evaluates multiple models, including logistic regression, decision trees,
random forests, and support vector machines, to determine the most accurate model for predicting employee
attrition. The evaluation is based on accuracy, precision, recall, and F1-score to ensure a robust prediction. The

findings offer organizations valuable insights into the primary causes of employee turnover and provide a data-
driven approach to proactively address these issues, reducing attrition rates and improving employee retention

strategies. This research contributes to the existing body of knowledge by offering a comprehensive framework for
predicting employee attrition, and its practical implications extend to human resource management, organizational
development, and strategic planning.
Keywords:
Employee attrition, Turnover prediction, Predictive model, Push factors, Pull factors, Organizational factors,
External factors, Machine learning, Logistic regression, Accuracy, Precision, Recall, F1-score, Employee retention,
Human resource management, Workforce stability.
AUDIO TO SIGN LANGUAGE CONVERSION
Authors: Kurian Lisha , K Anil Sreelakshmi , Abhilash Souparnika , Valsan Kashmeera , Venugopal Vinaya
Published: December 2024

Due to high demand for inclusive technologies
and the rapid electrons communication age, there is growing
interest in automatic audio to sign language conversion
systems. This article has given the relevant way to solve this
problem by converting spoken language into sign languages in
real time using machine translation that can shape
communication path for deaf and dumb community. In our
method, we use Natural Language Processing (NLP) to
transcribe audio into text and then deep learning for sign
language generation. The system recognizes keywords and
important phrases in the transcribed text, associates them with
corresponding sign language gestures, and presents such signs
animations using an avatar-based visualization. The recent
accomplishment is different from previous systems that work
directly and only translate a sentence to its corresponding sign,
rather focusing on the contextual analysis for better conveying
of meaning.

Key Words: Audio to Sign Language Translation, Speech- to-
Text Conversion, Natural Language Processing (NLP),

Machine Translation, Deep Learning, Gesture Recognition,
Avatar-based Sign Language Visualization, Accessibility,
Multilingual Sign Language
Web Data Mining and Crawling: A Detailed Overview in the Aspect of Googlebot, Apache Nutch and Bingbot
Authors: Nair Divya B , P A Rabeena , raj Athira
Published: December 2024

This paper explores the integration of web data mining
with web crawlers, focusing on how various web
crawlers—Apache Nutch, G-Boats, and Bing Bot—
collect and process web data. Apache Nutch, with its
scalable distributed crawling capabilities and

integration with Hadoop, excels in handling large-
scale data collections. G-Boats offers real-time data

processing with a flexible framework, while Bing Bot
demonstrates advanced algorithms for web indexing
and search engine optimization. The paper compares
these crawlers, highlighting their strengths and
weaknesses in scalability, fault tolerance, content
extraction, and big data integration. The conclusion
provides insights into choosing the appropriate web
crawler based on specific web data mining needs.
CARBONLY
Authors: Nagaraju Dr. V Siva , HS Vedanshu , D Vasundara
Published: December 2024

This project focuses on the development and
implementation of a Carbon Footprint App designed to
empower individuals and organizations to track and
reduce their carbon emissions. By providing real-time
tracking, personalized recommendations, and engaging
features such as gamification and community challenges,
the app aims to foster sustainable practices and raise
awareness about the environmental impact of everyday
activities. The methodology involves collecting user data
on energy use, transportation, food consumption, and
waste management, converting this data into carbon
dioxide equivalents, and offering actionable advice to
lower emissions. The app is applicable across various
sectors, including personal use, corporate sustainability,
policy support, education, supply chain management,
urban planning, and environmental certification. The
results demonstrate that informed individual actions, such
as skipping a weekly cup of coffee or reducing chocolate
consumption, can collectively lead to significant
reductions in carbon emissions. This project underscores
the importance of individual responsibility in combating
climate change and promotes a community-driven
approach to achieving a more sustainable future.

Key Words: Carbon Footprint, Real-time Tracking,
Gamification, Personalized Recommendations,
Sustainability
The Influence of Leadership-Focused Training on Employee Morale and Team Cohesion in Agile Organizations
Authors:   (Assistant Professor, Shri Ram Group of Colleges), Pandey Mrs. Nivedita , Pandey Mr. Navin Prakash ,   (Head- Productions, ISGEC Heavy Engineering Ltd.)
Published: December 2024

In a rapidly transforming business environment, agile organizations necessitate adaptive leaders who can navigate

change, inspire innovation, and cultivate high-performing teams. This study examines the impact of leadership-
focused training on employee morale and team cohesion, specifically within agile organizational frameworks.

Adopting a mixed-methods approach, the research evaluates how tailored leadership programs reshape interpersonal
dynamics, enhance employee satisfaction, and boost organizational performance. The findings underscore actionable
strategies for integrating agility principles into leadership development, emphasizing their role in fostering resilience

and sustainable growth. This study contributes to the evolving discourse on leadership agility by providing evidence-
based insights for practitioners and policymakers.

Keywords: Leadership development, agile frameworks, employee satisfaction, team collaboration, organizational
performance
Diabetes Disease Prediction using Machine-Learning with AI-Powered Health Advice
Authors: Nagaraju Dr. V Siva , Reddy M. Sai Rakesh , Chand D. Ravi
Published: December 2024

The integration of machine learning and
artificial intelligence is transforming various industries,
including healthcare. With the vast amount of patient data
available, there is an unprecedented opportunity to utilize
machine learning for improving disease detection and
diagnosis. This research introduces an advanced
prediction system designed to identify multiple diseases
simultaneously, addressing the limitations of
conventional systems that typically focus on single
diseases with varying accuracy levels. The current scope
of this system includes predictions for five critical
diseases: Heart Disease, Liver Disease, Diabetes, Lung
Cancer, and Parkinson’s Disease, with plans to expand its
capabilities in the future.
The system leverages Convolutional Neural Networks
(CNN) to process disease-specific parameters, enabling
users to input their data and receive accurate predictions.
Advanced feature engineering techniques were applied to
enhance model performance, achieving a prediction
accuracy of 85%. This platform empowers users to
monitor their health proactively, facilitating early
interventions and improving quality of life. By harnessing
the power of machine learning, this project aims to make
a meaningful impact on healthcare, offering reliable and
actionable insights to help individuals manage their
health effectively.
Beyond providing accurate disease predictions, this
system empowers users to actively monitor their health,
offering personalized insights that facilitate early
detection and timely interventions. By proactively
addressing potential health risks, the platform aims to
enhance the quality of life for individuals by enabling
them to manage their health more effectively.
Key Words: Machine Learning, Artificial Intelligence,
Convolutional Neural Networks (CNN), Feature
Engineering, Disease Prediction, Healthcare Monitoring,

Proactive Health Management, Predictive System, Deep
Learning, Neural Network, AI in Healthcare, Smart
Diagnostics.
SIGN LANGUAGE TO TEXT CONVERTOR
Authors: Suresh Hrithik , Ismail Noufal , Krishna V Hari , Sudhakaran Vysakh M , M Santhi
Published: December 2024

Sign language is a vital form of
communication for the Deaf and Hard of Hearing
community, yet there remains a significant barrier in real
time interaction with non-sign language users. This
project proposes the development of a Sign Language to
Text Converter, an innovative system designed to
translate sign language gestures into written text. The
goal of the system is to produce an accessible real-time
tool that transcends the communication gap between the
Deaf people and those who are not familiar with sign
language, thus enhancing interaction in diverse spheres
such as education, healthcare, and social settings. This
system will utilize techniques such as computer vision
and machine learning in recognizing and interpreting
hand gestures.
The system processes real-time video input using
OpenCV for image processing and MediaPipe for hand
and pose detection, extracting key features such as hand
positions, movements, and orientations. These features
are then fed into a Convolutional Neural Network (CNN)
trained to classify individual sign language gestures. The
output is translated to text, which can either be displayed
on a screen or used with the text-to-speech systems to
provide an auditory output.
Key Words: MediaPipe, Convolutional Neural Network
(CNN), Text To Speech(TTS), American Sign Language
(ASL)
Web Application for WIFI based Library Book Locator
Authors: Nagaraju Dr V Siva , Manikanta P Pavan Sri , Kumar A Pradeep
Published: December 2024

Utilizing Wi-Fi and RFID for Efficient
Library Book Search and Navigation. In an era of
information overload, efficient navigation within
physical libraries remains a challenge. This project
proposes a novel Wi-Fi-based book locator system
utilizing Radio-Frequency Identification (RFID) tags and
existing library infrastructure. Users access a mobile app
or web portal to search for books, triggering location
queries to Wi-Fi access points equipped with RFID
readers. The system identifies and pinpoints the nearest
available copy, significantly reducing search time and
frustration. Integration with library data provides book
availability status, turn-by-turn navigation, and
reservation capabilities. This innovative approach
leverages existing technology to enhance user
experience, optimize library organization, and foster a
more productive and engaging library environment.

Key Words: RFID, Libraries, Navigation , Efficiency of
time
AI-Driven Real-Time Sales Analytics and Customer Feedback Insights Platform
Authors: K Ananthiga , J Harshini , alamon V Jeslar John S , V Mahalakshmi , K Kalaivani
Published: December 2024

This project focuses on developing an interactive, real-
time dashboard designed to empower businesses with

actionable insights into sales performance and
customer feedback. The platform simplifies data
analysis by allowing users to upload CSV or Excel
files containing sales and customer data. Using
advanced analytics and visualization techniques, it
transforms raw data into meaningful insights to
optimize business decisions.
Key features include comprehensive sales analytics
through dynamic charts and plots, sentiment analysis
for customer feedback using TextBlob, and KPI
tracking to monitor critical performance metrics such
as total revenue, monthly sales trends, and customer
satisfaction levels. By leveraging predictive analytics
via linear regression, the dashboard enables accurate
sales forecasting, empowering users to anticipate
trends and make proactive strategies.
This tool bridges the gap between data complexity and
business strategy, equipping organizations to enhance
customer satisfaction, streamline operations, and drive
sustainable growth. Its user-friendly interface ensures
accessibility, while the AI-driven insights provide
precision and clarity, helping businesses stay
competitive in a dynamic market environment.
Keywords: AI-Driven Analytics, Sales Insights,
Customer Feedback Analysis, Data Visualization,
Predictive Analytics, Sentiment Analysis, Business
Growth, KPI Tracking, Proactive Decision-Making,
Real-Time Dashboards.
Herbal Remedies in Burn Wound Management: A Comprehensive Review
Authors: ansari Javed , kumar Rishu , Sahu Sandeep , Sahu Bishesar , Sahu Anjali , Sharma Harish , Sahu Gyanesh Kumar
Published: December 2024

This study focuses on the formulation and evaluation of a herbal burn healing cream using Jatropha curcas latex
extract. The cream combines Jatropha curcas latex with compatible excipients to optimize stability, texture, and
therapeutic efficacy. Various physicochemical, rheological, and pharmacological evaluations were conducted to
assess its suitability for burn wound management. The cream demonstrated desirable pH, viscosity, spreadability, and
consistency, along with significant antimicrobial activity against common wound pathogens. The formulation aims
to harness the anti-inflammatory, antimicrobial, and wound healing properties of Jatropha curcas latex for effective
burn treatment.

Keywords: Healing Cream, Rheological, Anti-Microbial, Anti-Inflammatory
Solanum Surratense: Unveiling its Therapeutic Potential
Authors: Sinduja S Mrs , Thomas Mrs.Asi
Published: December 2024

Solanum surratense plant is tropical plant mostly found in vellore district tamilnadu ,it has traditional history and
potential health benefits.
This review aids to summarize the current knowledge on phytochemical and pharmacological activities.this
solanum surratense has bio active compounds that includes alkaloids,glycosides,flavanoids tannins terpenoids and
phenolics that have exhibits antibacterial ,antioxidant,anti diabetic,anti inflammatory and anticancer activites
We conduct molecular studies to unveil the therapeutic properties of solanum surratense
This review highlights the importance of further research to explore possible applications that could be helpful for
treatment and prevention of numerous disesase.
Keywords

Solanum surratense phytochemicals , pharmacological , Hepatoprotective anti -bacterial ,anti oxidant, anti-
diabetic , Neuroprotective Effects, anti- inflammatory and anti- cancer
Analisis Kepuasan Pelanggan Berdasarkan Dimensi Servqual Menggunakan Metode Importance Performance Analysis
Authors: Mardiana Irma , Rubiyanti R. Nurafni
Published: December 2024

PT. Telkom is the largest telecommunications company in Indonesia that plays an important role in the development of the national telecommunications. In 2012, PT Telkom launched IndiHome (Indonesia Digital Home), that is is a multi product bundling packages of Telkom consisting landlines, internet and interactive television services (USee Tv). As the largest telecommunications company in Indonesia, PT. Telkom should provides satisfaction through good quality services in accordance with expected by the customer.The purpose of this study is to know how satisfied customers IndiHome Witel Bandung by comparing the level of customer expectations and IndiHome Witel Bandung’s performance levels-based method SERVQUAL. Data collection method is done by distributing questionnaires to 100 customers of IndiHome Witel Bandung that currently active subscription (existing). The results of data from questionnaires, processed by using Gap analysis to know the level of customer satisfaction, after that reprocessed by using Important Performance Analysis (IPA) or also called Kartesius Diagram analysis to know which attributes or dimensions that need to be a priority IndiHome Witel Bandung for improved performance levels and any attributes or dimensions that need to be retained by the company. Based on the results of data processing, it is known customer’s appraisal on 21 of performance attributes and 21 of expectations attributes indicate that all the attributes or dimensions have a gap between customers' perception of indihome’s performance and customer expectations. As well as with the level of conformity obtained is still below 100%, ie 79.5%. It means that Indihome’s performance still has not filled customer expectations. Based on the Kartesius diagram on Important Performance Analysis (IPA), there are eight indicators and two dimensions, they are reliability dimensions and responsiveness dimensions that Indihome should be the focus to be immediately rectified their performance.
Pengaruh Ukuran Perusahaan, Profitability, Dan Debt Equity Ratio Terhadap Ketepatan Waktu Pelaporan Keuangan
Authors: Aprianti Ine
Published: December 2024

The research objective was to show how the development of the growth of company size, profitability and debt to equity ratio of the timeliness of financial reporting. This study uses deskiptif research and verification. With data analysis techniques using parametric statistics. The population in this study amounted to 43 companies’ sector of food and beverages industry and textile industry sectors in the study period of 2006 to 2008. That was then acquired 15 companies in the sample using purposive sampling method of sample collection techniques with particular consideration.
The data used in this research is secondary data derived from the Corner Exchange ITB and www.idx.co.id official website that the company's financial statement data sectors of food and beverages industry and textile industry sectors listed on the Stock Exchange. The results of multiple linear regression t test showed that the variables of profitability and debt to equity affect the timeliness of financial reporting, while the size of the company does not affect the timeliness of financial reporting. In the F test shows that together variables company size, profitability and debt to equity affect the timeliness of financial reporting.
Pengaruh Budaya Organisasi Dan Kompetensi Pedagogik Terhadap Kinerja Guru
Authors: Danasasmita Windi Matsuko
Published: December 2024

In managing the organization, there must be an appropriate strategy to regulate the workers to work as a team. The primary goal is achieving the optimum goal. Likewise, the existing organization at school must implement the proper strategies to produce the excellent teachers’ performance. The organizational culture and teachers’ competence influence their performance in an organization. This study aims to determine the impact of organizational culture and pedagogical competence on teachers’ performance. This study examined a population of teachers in a high school in Bandung. The data analysis technique of this study is path analysis. The results reveal that there is an influence of organizational culture and pedagogical competence on teachers’ performance. This finding indicates a conducive organizational culture and adequate pedagogical competence improve the teachers’ performance.
Pengaruh Kepuasan Kerja Dan Komitmen Organisasi Terhadap Organizational Citizenship Behavior Serta Dampaknya Terhadap Kualitas Pelayanan Pada Universitas X di Kota Bandung
Authors: Lukitasari Lenni
Published: December 2024

This study aims to determine and analyze the permanent lecturer job satisfaction of the University of X in the city of Bandung, permanent lecturer organizational commitment of the University of X in Bandung, a permanent lecturer at University X in Bandung, service quality at the University of X in Bandung. Organizational Citizenship Behavior, the magnitude of the influence of organizational commitment on Permanent Organizational Citizenship Behavior of University X in Bandung, the influence of Organizational Citizenship Behavior on the Quality of Service and the influence of job satisfaction and organizational commitment on the quality of University services X in the city of Bandung. This research conducted at the University of X in the city of Bandung. The population in this study were 64 Permanent Lecturers at the Faculty of Economics, University of Bandung.Based on the purpose of the research to be carried out, the research method used is descriptive analysis to describe the nature of something and examine the causes of a particular phenomenon and answering questions concerning something at the time of the ongoing research process. The analysis used is path analysis and using the SPSS program. Based on the results of the study, it appears that job satisfaction has a direct influence of 20.34%, the indirect effect of job satisfaction through organizational commitment is 12.43%, so the total effect of job satisfaction is 32.77%. Organizational commitment has a direct influence of 27.14%, the indirect effect of organizational commitment through job satisfaction is 12.43%, so the total influence of organizational commitment is 39.57%. The overall total effect is 72.34%. The effect of other factors not examined on Organizational Citizenship Behavior is indicated by the value = 0.2766 or 27.66% and the magnitude of the influence of Organizational Citizenship Behavior on service quality is 75.3%, the effect of other factors not examined on service quality is indicated by the value = 0.247 or equal to 24.7%.
Pengaruh Faktor-Faktor Kualitas Pelayanan Terhadap Kepuasan Pelanggan Dan Implikasinya Terhadap Loyalitas Pelanggan Di Green Café & Resto Bandung
Authors: Megawati Imelda
Published: December 2024

The purpose of this research is to determine and to overview the influence factors of service quality to customer satisfaction and its implications for customer loyalty.
The object of research in this thesis is Green Café & Resto Bandung and the subject of this study is its customers which consists of 110 people.
And the method of this research is hypothesis testing with path analysis. These results indicate that the variable tangible, empathy and customer satisfaction are at fairly high category, variable responsiveness, reliability and customer loyalty at the high category and variable assurance is at the low category.
The influence factors of service quality on customer satisfaction are 79,7% and very high where the remaining 20,3% influenced by other factors. Total influence of tangible variables on customer satisfaction is 19%, empathy is 24.31%, responsiveness is 16,88%, reliability is 12,51% and assurance is 7,07%.
The implications of service quality to loyalty is 86,1% and very high where the remaining 13,9 % influenced by other factors.
Pengaruh Celebrity Endorser Dan Word of Mouth Terhadap Keputusan Pembelian Produk Sweater Online Shop Alco Di Media Sosial Instagram
Authors: Fildzah Nur Amalina , Sari Devilia
Published: December 2024

Alco is a small and medium businesses producing knit sweaters. Alco admitted about an increase in sales after endorsement to celebrity endorser. But there is a decline in sales in the mid 2016 even Alco been using celebrity endorser. From the initial survey results that the researcher conducted to prove recognition of Alco, these survey results showed that respondents knew Alco online shop and make a purchase decision from celebrity endorser, word of mouth, and explore Instagram. Inside Instagram, in addition to celebrity endorser that can affect a person's buying decision contained in a photo caption in the social media Instagram. And from the caption can be said as a word of mouth expressed by consumers an online shop on Instagram. explore Instagram is a feature from Instagram Thus, this study uses independent variable celebrity endorser and word of mouth. This study was conducted to know the influence of celebrity endorser and word of mouth partially and simultaneously on the purchase decision of sweater in an online shop Alco in social media Instagram. The type of research used is descriptive and causal research with the method used is quantitative. This study was involving 100 respondents of Alco consumers in social media Instagram. The sampling technique was using a non-probability sampling type of incidental sampling. This study uses multiple regression analysis technique. The results showed that simultaneously celebrity endorser and word of mouth are significantly influencing purchase decisions. Partially celebrity endorser and word of mouth are significantly influencing purchase decisions.
Perilaku Kedermawanan Muslim di Indonesia Studi Mengenai Intensi Dan Perilaku Bersedekah
Authors: Setianagara Mohamad Ivan
Published: December 2024

This paper is to analyzes the factors that influencing the intention and behavior of charity of Muslim society in Indonesia. What elements are the most powerful contributors in charitable intentions and does the current Muslim community in Indonesia have an addiction to charity?Theory of Planned Behavior is used to examine intention and behavior in charity. This research uses descriptive research approach to explain the profile of the respondents, their behavioral tendency incharity. This research is also trying to find out what factors affect the individual in charity so thatthis behavior becomes an addicted thing.The statistical method used in analyzing the data is the Structural Equation Modeling (SEM) method with the assisted of LISREL (Linear Structural Relation) program version 9.30.The results of the study found that the most influential factor on the intention of charity of Muslim society in Indonesia is Perceived Behavioral Control.Also illustrated that the Muslim community in Indonesia has not reached the level of "addiction" in charity. The dominant frequency of charity is 73% as much as 1 - 5 times in a month, while thehypothesis of addiction is the frequency of giving alms more than 5 times within a month.
Examining the impact of cultural literacy on students' attitudes of tolerance towards diversity
Authors: Nirmayani L. Heny , Lasmawan I Wayan , Suastika I Nengah , Margunayasa I Gede
Published: December 2024

This study aims to identify the influence of cultural literacy on students' understanding of attitudes of tolerance towards diversity. This quasi-experimental study was conducted using a post-test-only control group design. This study was conducted in an elementary school in Bali involving groups of fourth-grade students, who were students from two different classes and selected using statistical matching techniques. One group became the experimental group, and the other became the control group. The research data were collected using an understanding test of attitudes of tolerance towards diversity. The post-test was given to the two groups after the experimental group had been taught cultural literacy, and the control class was taught using conventional materials commonly used by teachers for eight meetings. The results of the post-test were analyzed quantitatively using descriptive statistics, independent t-test, and Cohen’s d. From the results of the descriptive statistical analysis, it was found that students in the control class had better average scores in terms of understanding attitudes of tolerance towards diversity than the control group. The results of the independent t-test showed that the difference in the average value was proven to be significant. Furthermore, the results of the effect size test also showed that cultural literacy has a large and significant influence on students' understanding of attitudes of tolerance towards diversity. Thus, from these results, it can be concluded that cultural literacy is effective in improving students' understanding of attitudes of tolerance towards diversity.
Factors influencing creative labor of intellectuals in Vietnamese universities: Empirical insights
Authors: Hang Vu Thi , Toan Nguyen Quoc , Thuy Nguyen Thi , Bac Ha Thi , Huong Pham Thi Thu , Sang Do Van
Published: December 2024

Intellectuals play a critical role in Vietnam's industrialization, modernization, and knowledge-based economy. This study explores the motivating environment fostering creative labor among intellectuals in universities, a key segment of this workforce. Using data from 256 staff members across 30 universities, the research employs expert methods and the Relative Importance Index (RII) to evaluate 16 influential factors. Results show that factors such as salary policies, work supervision, recognition of creative ideas, and intellectuals’ self-learning spirit have the highest impact on fostering creativity. This study highlights the need for comprehensive institutional reforms to enhance intellectual motivation and creativity in higher education, offering actionable insights for policy and practice.
Exploration of patient loyalty through value integration and customer satisfaction in class B university hospitals on Java Island
Authors: Sutrisno Sutrisno , Andjarwati Tri , Budiarti Endah
Published: December 2024

This study aims to analyze the relationship between accessibility, brand image, and service quality on customer value, customer satisfaction, and revisit intention at the University Hospital (RSPT). The main focus of the study is the mediating role of customer value and customer satisfaction in influencing patient loyalty. With a holistic approach, this study highlights the unique dynamics of RSPT that integrates education and health care functions. The findings indicate that accessibility and service quality have a significant influence on customer value, while brand image has a more limited contribution in this context. In addition, customer satisfaction plays an important role in bridging the relationship between customer value and revisit intention, making it a strategic dimension in increasing patient loyalty. A statistical approach using the SmartPLS method was carried out to evaluate the validity and reliability of the research model. The test results showed that the Average Variance Extracted (AVE) value of all constructs was greater than 0.50, reflecting that convergent validity was met. The Composite Reliability and Cronbach's Alpha values were each greater than 0.70, indicating good internal consistency. Discriminant Validity is assessed through the Heterotrait-Monotrait Ratio (HTMT) with a value of less than 0.85, ensuring clear differences between constructs. The results of the path analysis show that accessibility (X2) significantly affects customer value (Z) with a coefficient of 0.826 (T = 6.993, p < 0.000). Likewise, service quality (X3) has a positive effect on customer value with a coefficient of 0.291 (T = 2.521, p < 0.012). In contrast, brand image (X1) does not have a significant effect on customer value (coefficient -0.192, T = 1.783, p = 0.075). Customer value has a significant effect on customer satisfaction (coefficient 0.922, T = 55.068, p < 0.000), which in turn affects patient revisit intention (coefficient 0.922, T = 53.495, p < 0.000). This study provides theoretical contributions by expanding the healthcare management literature, especially in the unique context of RSPT. Practically, these findings recommend improving accessibility and service quality to enhance patient loyalty. This study also opens up opportunities for further research with a longitudinal approach to understand changes in patient perceptions over time.