bluuebunny/crossref_metadata_2025 huggingface dataset:
The outer-independent edge-vertex domination in trees
Authors: Kim Kijung
Published: April 2024

Let \(G=(V,E)\) be a finite simple graph with vertex set \(V=V(G)\) and edge set \(E=E(G)\). A vertex \(v \in V\) is edge-vertex dominated by an edge \(e \in E\) if \(e\) is incident with \(v\) or \(e\) is incident with a vertex adjacent to \(v\). An edge-vertex dominating set of \(G\) is a subset \(D \subseteq E\) such that every vertex of \(G\) is edge-vertex dominated by an edge of \(D\). A subset \(D \subseteq E\) is called an \textit{outer-independent edge-vertex dominating set} of \(G\) if \(D\) is an edge-vertex dominating set of \(G\) and the set \(V(G) \setminus I(D)\) is independent, where \(I(D)\) is the set of vertices incident to an edge of \(D\).The \textit{outer-independent edge-vertex domination number} of \(G\), denoted by \(\gamma_{ev}^{oi}(G)\), is the smallest cardinality of an outer-connected edge-vertex dominating set of \(G\). In this paper, we initiate the study of outer-independent edge-vertex domination numbers. In particular, we prove that \(\frac{n- l +1}{3} \leq \gamma_{ev}^{oi}(T) \leq \frac{2n -s -2}{3}\) for every tree \(T\) of order \(n \geq 3\) with \(l\) leaves and \(s\) support vertices. We also characterize the trees attaining each of the bounds.
FACTORS AFFECTING SUPPLY CHAIN COOPERATION: A CASE-BASED STUDY IN THE ORGANIC AGRICULTURE INDUSTRY IN HANOI, VIETNAM
Authors: Hoa Do Thi Thanh , Cuong Ngo Anh , Thang Nguyen Toan , Lan Hoang Thi Phuong
Published: April 2024

Purpose: After the covid 19 pandemic, cooperation has become increasingly necessary and important for the supply chain, especially the organic agricultural supply chain, which has loose and fragmented links. Furthermore, with the need for clean, safe food, organic agriculture is also receiving more attention from the government, consumers and businesses. This study aims to examine factors affecting supply chain cooperation based on a survey sample of 120 managers from businesses in the organic agricultural supply chain in Hanoi, Vietnam. From this analysis, we provide solutions to promote cooperation in the supply chain for the organic agriculture industry in Hanoi, Vietnam.
 
Design/Methodology/Approach: This article uses the research method of analyzing and synthesizing theories about cooperation in the supply chain, thereby providing a research model. Then we use quantitative methods, exploiting the random approach to analyze factors affecting cooperation in the organic agricultural supply chain through surveying subjects that involved in organic agricultural supply chains in Hanoi, Vietnam.
 
Findings: The research results describe the impact of factors affecting cooperation in the supply chain, showing the level of influence of these factors on cooperation. Through the level of impact, the authors propose solutions to enhance cooperation in the organic agricultural supply chain.
 
Originality/Value: To the author's knowledge, this study is original in describing the impacts of factors affecting the cooperation of organic agricultural supply chains in Hanoi, Vietnam. Furthermore, the article uses random approaches, contributing to research through a practical lens.
UNVEILING THE NEXUS BETWEEN LEADERSHIP DYNAMICS AND INNOVATION CAPABILITIES IN DRIVING GREEN CREATIVITY: THE CRUCIAL MODERATING ROLE OF GREEN MOTIVATION AMONG SMES IN PAKISTAN
Authors: Bashir Muhammad Atif , Sarwar Shakeel , Ullah Habib , Asab Muhammad Zulqarnain , Khurshid Rashid , Taimoor Muhammad
Published: April 2024

Objective: This study aims to explore the under-investigated area of green creativity within Pakistani SMEs by examining the influence of leadership dynamics (transformational and transactional leadership) and innovation practices.
 
Theoretical Framework: The research builds upon the concepts of green creativity, transformational leadership, transactional leadership, innovation practices, and green motivation.
 
Method: A survey methodology was employed with a sample of 191 managers and owners of SMEs in Pakistan. Data analysis was conducted using SmartPLS software.
 
Results and Discussion: The findings reveal positive relationships between transformational leadership, transactional leadership, innovation practices, and green creativity. However, green motivation was identified as a negative moderator in the relationship between innovation practices and green creativity. The study emphasizes the significance of leadership styles (transformational and transactional) and fostering a culture of innovation for driving green creativity within SMEs. Green motivation, while positive in itself, seems to hinder the impact of innovation practices on green creativity, requiring further investigation.
 
Research Implications: This research contributes to the understanding of green creativity in SMEs by highlighting the facilitating role of leadership dynamics and innovation practices. It underscores the need for future research to delve deeper into the moderating effect of green motivation.
 
Originality/Value: This study offers a valuable contribution to the existing environmental sustainability literature. It delves into green creativity within Pakistani SMEs, a previously unexplored area.  By examining leadership styles, innovation practices, and the surprising moderating role of green motivation, the research offers valuable insights for both businesses and policymakers to cultivate environmentally friendly practices within SMEs.
LAS COSTURERAS DE LA MEMORIA DEL CONFLICTO ARMADO EN COLOMBIA: UN ANÁLISIS A PARTIR DE LAS POLÍTICAS PÚBLICAS ENCAMINADAS AL RECONOCIMIENTO DE LA MUJER
Authors: García Yadira Esther García , Castiblanco Juan Carlos de los Ríos , Donado Magda Ligia Djanon , Julio Yiseth Paola Ospino
Published: April 2024

RESUMEN.

Objetivo: El objetivo central es identificar cómo a través de los aportes filosóficos que enmarcan la historia del sufrimiento de la cultura violenta hacia la mujer se determinan políticas públicas encaminadas a la protección especial de las mismas.

Marco Teórico: Se basa en diversas corrientes y enfoques, incluyendo los estudios de género, la memoria histórica, los estudios de conflicto armado, y las políticas públicas, buscando proporcionar un análisis integral y multidisciplinario del tema, que permita comprender las dinámicas de género en la construcción de la memoria y el reconocimiento en el contexto del conflicto armado en Colombia.

Método: La investigación se realizó a través de una revisión documental, el enfoque utilizado fue el cualitativo con un corte descriptivo-histórico de la memoria narrada por las costureras con relación al conflicto.

Resultados y Discusión: Los resultados encontrados evidencian como el factor económico, social y cultural son las categorías esenciales que le permiten al gobierno establecer a partir de las terapias de “reconocimiento y aceptación” las garantías encauzadas al bienestar de todas las mujeres colombianas.

Implicaciones de la investigación: Se destaca la importancia de reconocer el papel fundamental de las mujeres en la construcción de la memoria histórica y la reconciliación en contextos de conflicto y la necesidad de incorporar políticas públicas que garanticen su reconocimiento.

Originalidad/Valor: Este estudio contribuye a llenar distintos vacíos existentes en la literatura académica y a destacar la importancia de reconocer y valorar las contribuciones de las mujeres en los procesos de reconciliación y construcción de la paz.
O GERENCIAMENTO EFICIENTE DE RESÍDUOS NA UNIDADE DE TERAPIA INTENSIVA (UTI)
Authors: Resende Ana Clara Almada , Resende Jaíne das Graças de Oliveira , Resende Jane Daisy de Sousa Almada , Santos Andreia Andrade dos
Published: April 2024

Os Resíduos de Serviços de Saúde (RSS) mal gerenciados, representam um sério risco para a saúde pública e o meio ambiente.

Objetivo: O objetivo do artigo foi analisar o processo de gestão de resíduos na UTI com o intuito de identificar boas práticas e possíveis áreas de melhoria para garantir a segurança dos pacientes, dos profissionais de saúde e do meio ambiente.

Referencial Teórico: Apesar de representarem uma fração menor do volume total de resíduos produzidos diariamente, os RSS constituem risco significativo para a saúde da população, sendo assim, foi criado instrumentos legais e políticas com o intuito de harmonizar a gestão de resíduos sólidos no Brasil.

Método: Revisão da literatura e observação direta às atividades relacionadas ao gerenciamento de resíduos na UTI e registradas detalhadamente as práticas realizadas pelos profissionais de saúde.

Resultados e Discussão: Os resultados obtidos revelaram que a gestão adequada e responsável dos resíduos hospitalares provenientes da UTI estavam em conformidade com exigências das legislações. A classificação dos resíduos foi realizada de maneira eficaz, o que se mostra fundamental para o processo de gerenciamento desses materiais.

Implicações da Pesquisa: Fornecer insights sobre otimização do gerenciamento de resíduos na UTI, melhorando a segurança dos pacientes e do ambiente hospitalar, além de contribuir para o desenvolvimento de diretrizes e protocolos mais eficazes.

Originalidade/Valor: A originalidade e valor deste estudo residem na análise detalhada e específica do gerenciamento de resíduos na UTI, proporcionando novas perspectivas e estratégias para aprimorar as práticas de gestão de resíduos em serviços de saúde.
PRODUCTIVISM IN UNIVERSITIES: EVALUATION AS AN INSTRUMENT OF NEOLIBERAL LOGIC IN HIGHER EDUCATION
Authors: Francisco Thiago Henrique Almino , Martins Georgia Carolina Carvalho , Oliveira Carla Carolina Dias de , Moser Giancarlo
Published: April 2024

Objective: This study aims to explore the influence of academic productivism within the framework of Brazilian public Higher Education Institutions (HEIs) since the adoption of the new postgraduate evaluation policy by CAPES (Coordination for the Improvement of Higher Education Personnel) in 1977. It seeks to understand how neoliberal productive logic applied to universities as organizations correlates with the assessment policies in Brazil.

 

Theoretical Framework: The research is grounded in the concepts of productive and reproductive work, aiming to establish a connection between neoliberal productivist logic in universities and the close relationship with evaluation policies. Key theories and models explored include the knowledge society and market-oriented capitalist productivity within academic settings, providing a solid foundation for the study's context.

 

Method: The methodology involves a historical contextualization of the university as an object of study, supplemented by a bibliographic analysis. Data collection was based on an extensive review of literature pertinent to the evolution of university roles under neoliberal capitalism and the impact of quantitative assessment tools serving market-oriented educational paradigms.

 

Results and Discussion: Preliminary findings indicate a significant influence of market-driven productivity logic on academic environments, shaped by the assessment mechanisms perceived as instruments serving this logic. These results are discussed in relation to the theoretical framework, highlighting the implications and connections identified, with a consideration of potential discrepancies and limitations of the study.

 

Research Implications: The practical and theoretical implications of this research provide insights into how the findings might be applied or influence practices in the field of higher education management. These implications extend to areas impacted by neoliberal assessment policies and their effects on academic productivity.

 

Originality/Value: This research contributes to the literature by offering a historical perspective on the transformation of universities under neoliberal capitalism, analyzed through the lens of academic productivism and assessment policies. Its value lies in the elucidation of how these dynamics affect higher education in Brazil, offering implications for policy and practice in the sector.
Investigating the Effect of Financial Mismanagement on Municipalities Service Delivery: A Case Study of eThekwini Municipality-South Africa
Authors: Mabunda Lungile Tim , Mvunabandi Jean Damascene , Chonco Celumusa Makepeace
Published: April 2024

Purpose: This study investigated the effect of financial mismanagement on municipalities’ service delivery with a particular case study of eThekwini Municipality South Africa and to suggest how financial mismanagement can be addressed.  

Design/Methodology/Approach: Scoping review of literature methodological framework was employed followed by Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA).

Findings: This study indicates that financial mismanagement in eThekwini Municipality is one of the major concerns due to a lack of knowledgeable and skilled workers as well as political involvement from the administration. The results showed that there are various skill shortages, and it was noted that untrained people were being hired. The finding also said that poor municipal budget management is prevented by the political administration.

Implications/Originality/Value: The findings of this study have significant implications for improving the eThekwini Municipality's financial management. This article contributes to the to the current body of knowledge and deepens understanding on the root causes of financial mismanagement and effect of financial mismanagement on municipalities’ service delivery, particularly in eThekwini Municipality-South Africa. The study further recommends municipality to hire suitably qualified staff with sound ethics to improve municipal financial management. This study is crucial for fraud and forensic practitioners, academia, and policymakers. It provided research agenda for future researchers.
SPECIAL GRAPHS AND THEIR ZAGREB INDICES: A COMPARATIVE STUDY
Authors: Pushpalatha A. P.
Published: April 2024

A simple, finite and connected graph is denoted by G=(V,E). The primary Zagreb index, denoted as M1(G), characterizes the graph topologically by representing a squared degree sum of their vertices. Similarly, M2(G) denotes a second Zagreb index, that offers a topological measure of summing the degree of the product for adjacent vertices of graph G. We investigate a study of this topological indices M1(G)&M2(G) and got some interesting results also.
AN ANALYTICAL APPROACH TO THE NON-OSCILLATORY NONLINEAR MECHANICAL SYSTEMS HAVING INTEGRAL MULTIPLE ROOTS AND STRONG NON-LINEARITY
Authors: Uddin Nasir
Published: April 2024

The existence of over-damped nonlinear differential equations results from a variety of engineering conundrums and physical natural occurrences. Non-oscillatory dynamics with forced over-damping are used in the simulation of nonlinear differential systems. For non-oscillatory nonlinear differential systems, it is possible to derive approximations of solutions using a variety of analytical methods, both with and without external forcing. This paper introduces a novel method for estimating solutions for highly nonlinear damped vibration systems subject to parameterized external forcing. The extended Krylov-Bogoliubov-Mitropolsky (KBM) technique and harmonic equilibrium (HM), which have both been previously developed in the literature, are the foundation of the suggested method. This method was initially created by Krylov-Bogoliubov to discover periodic details in second-order nonlinear differential equations. Several examples are provided to show how the suggested technique is applied. The process is fairly simple and straightforward, and using this formula, the result can be found with very marginal errors from the previous citations. The primary significance of this approach is in its ability to provide approximate analytical solutions of the first order that closely align with the findings obtained by numerical methods. These solutions are applicable to a variety of beginning scenarios and are distinct from those presented in earlier literature. Also, we illustrated the two-dimensional graph of all the solutions that we got in this article by using the data from the mentioned table. The results that we obtained from this method are effective and reliable for better measurements of strong nonlinearities.
QUALITATIVE BEHAVIOR OF THIRD-ORDER DAMPED NONLINEAR DIFFERENTIAL EQUATIONS WITH SEVERAL DELAYS
Authors: Kumar M. Sathish
Published: April 2024

In this article, we examine the oscillation of a class of third-order damped nonlinear differential equations with multiple delays. Using the integral average and generalized Riccati techniques, new necessary criteria for the oscillation of equation solutions are established. The major effect is exemplified by an example.
ANALYSIS OF METRO NETWORK BY APPLYING GRAPH THEORETICAL NOTIONS
Authors: Barman Kamal Jyoti
Published: April 2024

Indian cities are extending and growing very rapidly with the increase in population. As a result, there is a need to implement mass transit systems such as metro rail to meet their day-to-day mobility requirements. In recent years metro rail has grown in many Indian cities. Much like a graph that is made up of vertices and edges, a metro network is composed of stations and a metro route connecting them, where each station represents a vertex and any two vertices are adjacent whenever there is a link (metro route) between them. In this paper, we try to study the structure of a metro network via a graph theoretical approach.
NEURO-TAXONOMY-BASED STRATEGY DESIGN FOR EMPLOYEE ENGAGEMENT
Authors: Barman Arup
Published: April 2024

Employee engagement is a crucial element in the triumph of any organization. It encompasses the degree of emotional commitment and devotion that employees possess towards their work and the organization. Enthusiastic employees exhibit higher levels of motivation, productivity, and job satisfaction. Additionally, they are more inclined Hussainy & Wahaibi (2022) to remain with the company and contribute to its development and achievement. To attain a more profound comprehension of employee engagement, it is imperative to delve into the role of the brain in this process. The brain, being a multifaceted organ, governs our thoughts, emotions, and actions. It assumes a significant position in shaping our encounters and perspectives within the workplace Coffey (2021). By comprehending the neuro-scientific aspects of employee engagement, organizations can construct strategies and interventions that effectively captivate their employees.From a behavioural and psychological perspective, employee engagement is an issue connected to the deep neuro-psychological thread of analysis and interpretation which is rare. Considering the backdrop designing a taxonomy of the word connecting to engagement is a need of hour. The paper meticulously designs taxonomies of components of neuro-behaviour and brain-connecting employee engagement to interpret brain-based engagement. The study forwarded a host of neuro-based strategies for employee engagement to management practitioners, academia, and researchers for future research.
Improving Algorithm Performance using Feature Extraction for Ethereum Forecasting
Authors: Tri Julianto Indri , Kurniadi Dede , Rohmanto Ricky , Alisha Fauzia Fathia
Published: April 2024

Ethereum is a cryptocurrency that is now the second most popular digital asset after Bitcoin. High trading volume is the trigger for the popularity of this cryptocurrency. In addition, Ethereum is home to various decentralized applications and acts as a link for Decentralized Finance (DeFi) transactions, Non-Fungible Tokens (NFTs) and the use of smart contracts in the crypto space. This study aims to improve the performance of the forecasting algorithm by using feature extraction for Ethereum price forecasting. The algorithms used are neural networks, deep learning, and support vector machines. The research methodology used is Knowledge Discovery in Databases. The data set used comes from the yahoo.finance.com website regarding Ethereum prices. The results show that the neural network Algorithm is the best Algorithm compared to Deep Learning and support vector machine. The root mean square error value for the neural network before feature selection is 93,248 +/- 168,135 (micro average: 186,580 +/- 0,000) Linear Sampling method and 54,451 +/- 26,771 (micro average: 60,318 +/- 0,000) Shuffled Sampling method. Then after feature selection, the root mean square error value improved to 38,102 +/- 31,093 (micro average: 48,600 +/- 0,000) using the Shuffled Sampling method
Development of an Early Warning System Using Social Media for Flood Disaster
Authors: I Ketut Kasta Arya Wijaya  , Siagian Ruben Cornelius
Published: April 2024

This research paper introduces an innovative prototype system that uses IoT technologies to monitor floodwater levels. Integration of an ultrasonic sensor, ESP8266 microcontroller, Arduino IDE, and the ThingSpeak platform aims to establish a robust flood monitoring solution. The paper provides a thorough exploration of the system's background, the problem it addresses, the methodology employed, and the obtained results, along with insights into future research directions. The study meticulously describes the design, implementation and programming code for data collection and transmission within the system. Through extensive field testing and meticulous data analysis, the paper evaluates the precision and effectiveness of the proposed flood monitoring solution. In particular, research underscores the advantages of IoT, emphasizing real-time data collection, logging, and analysis as essential components for efficient flood management. Additionally, the paper elucidates step-by-step instructions for configuring Telegram notifications through the ThingSpeak React app, enhancing the practical applicability of the developed system. The research effectively highlights the potential of IoT in flood monitoring, showcasing its superior accuracy and effectiveness compared to traditional methods. By demonstrating the feasibility and advantages of IoT in the context of flood monitoring, this study contributes valuable information, enriching existing knowledge, and paving the way for future advances in the field. Research encourages the continued exploration of advanced techniques to strengthen flood monitoring and management strategies. Ultimately, this work presents a comprehensive IoT-based prototype for floodwater monitoring, offering valuable information and fostering the promising role of IoT technologies in this critical domain.
The Design of a C1 Document Data Extraction Application Using a Tesseract-Optical Character Recognition Engine
Authors: Ircham Aji Nugroho  , Susanti Bety Hayat , Mareta Wahyu Ardyani  , Nadia Paramita R.A.
Published: April 2024

The 2019 election process used the Vote Counting Information System, also known as Sistem Informasi Penghitungan Suara (Situng), to provide transparency in the recapitulation process. The data displayed in Situng is from document C1 for 813,336 voting stations in Indonesia. The data collected from the C1 document is entered and uploaded into Situng by the officers of the Municipal General Election Commission (GEC). Since this process is performed by humans, it is not immune to errors. In the recapitulation process of the 2019 election results, there were 269 data entry errors, and the data entry process also did not run according to the specified target, resulting in delays. Furthermore, there were cases of C1 document modification, raising concerns about the data's authenticity. To avoid human errors and increase data entry speed, automatic data entry is a plausible option. The data entered are text data in image documents with the same template format, so that optical character recognition (OCR) can be used to read the text while improving image quality and alignment, resulting in a more accurate OCR reading area. In this study, we developed a C1 document data extraction application using the waterfall SDLC method, which has undergone a systematic and thorough process. The application was developed using Tesseract optical character recognition. Tesseract is an open-source OCR engine and command-line program that allows for the recognition of text characters within a digital image. The accuracy obtained by using this method is still not optimal as a substitute for Situng's data entry officer. To guarantee the integrity of the C1 document, we use the RSA-2048 digital signature scheme. The use of the Tesseract-OCR Engine for character recognition, combined with digital signature capabilities, provides a comprehensive solution to reduce the human error factor that can lead to miscalculations and inaccurate processes.
Investigating the Impact of ReLU and Sigmoid Activation Functions on Animal Classification Using CNN Models
Authors: M Mesran  , Sitti Rachmawati Yahya  , Fifto Nugroho  , Agus Perdana Windarto
Published: April 2024

VGG16 is a convolutional neural network model used for image recognition. It is unique in that it only has 16 weighted layers, rather than relying on a large number of hyperparameters. It is considered as one of the best vision model architectures. This study compares the performance of ReLU (rectified linear unit) and sigmoid activation functions in CNN models for animal classification. To choose which model to use, we tested 2 state-of-the-art CNN architectures: the default VGG16 with the proposed method VGG16. A data set consisting of 2,000 images of five different animals was used. The results show that ReLU achieves higher classification accuracy than sigmoid. The model with ReLU on convolutional and fully connected layers achieved the highest accuracy of 97.56% on the test dataset. However, further experiments and considerations are needed to improve the results. Research aims to find better activation functions and identify factors that influence model performance. The data set consists of animal images collected from Kaggle, including cats, cows, elephants, horses, and sheep. It is divided into training and test sets (ratio 80:20). The CNN model has two convolution layers and two fully connected layers. ReLU and sigmoid activation functions with different learning rates are used. Evaluation metrics include precision, precision, recall, F1 score, and test cost. ReLU outperforms sigmoid in accuracy, precision, recall, and F1 score. However, other factors such as the size, complexity and parameters of the data set must be taken into account. This study emphasizes the importance of choosing the right activation function for better classification accuracy. ReLU is identified as effective in solving the vanish gradient problem. These findings can guide future research to improve CNN models in animal classification.
Anatomy Identification of Bamboo Stems with The Convolutional Neural Networks (CNN) Method
Authors: Rustandi Dede , Sony Hartono Wijaya  , Mushthofa  , Ratih Damayanti
Published: April 2024

It is important to note that some species of bamboo are protected and considered endangered. However, distinguishing between traded and protected bamboo species or differentiating between bamboo species for various purposes remains a challenge. This requires specialized skills to identify the type of bamboo, and currently, the process can only be carried out in the forest for bamboo that is still in clump form by experienced researchers or officers. However, a study has been conducted to develop an easier and faster method of identifying bamboo species. The study aims to create an automatic identification system for bamboo stems based on their anatomical structure (ASINABU). The bamboo identification algorithm was developed using macroscopic images of cross-sectioned bamboo stems and the research method used was the convolutional neural network (CNN). CNN was designed to identify bamboo species with images taken using a cellphone camera equipped with a lens. The final product is an Android automatic identification application that can detect bamboo species with an accuracy of 99.9%.
Image Preprocessing Approaches Toward Better Learning Performance with CNN
Authors: Tribuana Dhimas , Hazriani  , Arda Abdul Latief
Published: April 2024

Convolutional neural networks (CNNs) are at the forefront of computer vision, relying heavily on the quality of input data determined by the preprocessing method. An undue preprocessing approach will result in poor learning performance. This study critically examines the impact of advanced image pre-processing techniques on computational neural networks (CNNs) in facial recognition. Emphasizing the importance of data quality, we explore various pre-processing approaches, including noise reduction, histogram equalization, and image hashing. Our methodology involves feature visualization to improve facial feature discernment, training convergence analysis, and real-time model testing.  The results demonstrate significant improvements in model performance with the preprocessed dataset: average accuracy, recall, precision, and F1 score enhancements of 4.17%, 3.45%, 3.45%, and 3.81%, respectively. Additionally, real-time testing shows a 21% performance increase and a 1.41% reduction in computing time. This study not only underscores the effectiveness of preprocessing in boosting CNN capabilities, but also opens avenues for future research in applying these methods to diverse image types and exploring various CNN architectures for comprehensive understanding.
Data Mining Techniques for Predictive Classification of Anemia Disease Subtypes
Authors: Setiawan Johan , Amalia Dita , Prasetiawan Iwan
Published: April 2024

Anemia, characterized by insufficient red blood cells or reduced hemoglobin, hinders oxygen transport in the body. Understanding the different types of anemia is vital to tailor effective prevention and treatment. This research explores the role of data mining in predicting and classifying anemia types, focusing on complete blood count (CBC) and demographic data. Data mining is the key to building models that help healthcare professionals diagnose and treat anemia. Employing the cross-industry standard process for data mining (CRISP-DM), with its six phases, facilitates this effort. Our study compared Naïve Bayes, J48 Decision Tree, and Random Forest algorithms using RapidMiner tools, evaluating precision, mean recall, and mean precision. The J48 decision tree outperformed the others, highlighting the importance of algorithm choice in anemia classification models. Furthermore, our analysis identified renal disease-related and chronic anemia as the most prevalent types, with greater occurrence among females. Recognizing gender disparities in the prevalence of anemia informs customized healthcare decisions. Understanding demographic factors in specific types of anemia is crucial to effective care strategies.
Visual Impaired Assistance for Object and Distance Detection Using Convolutional Neural Networks
Authors: Parenreng Jumadi Mabe , Andi Baso Kaswar  , Ibnu Fikrie Syahputra
Published: April 2024

Vision is a very valuable gift from God; Most aspects of human needs in the body are dominated by vision. Based on data from the World Health Organization (WHO) there are around 180 million people in the world experiencing visual impairment, while the prevalence of blindness in Indonesia reaches 3 million people (1.5% of Indonesia's population), so we designed a system in the form of a prototype that could detect objects around the user and convey data in the form of sound to the user. This research discusses the application of a machine learning model using the Convolutional Neural Network method to detect objects optimally. The objects that have been collected will be trained on machine learning and produce a model to be embedded in the system's main machine, namely the Raspberry PI 4B. The training of the machine learning model was carried out several times by changing the compositions of several layers until a model with optimal accuracy was obtained; however, the size of the resulting model was quite large, so the researchers carried out SSDMobileNetV2 transfer learning to obtain the optimal model. The optimal model was obtained with a model precision of 92% and a model size of 18 MB. Object detection tests carried out under 3 test conditions resulted in an average object detection accuracy of 84.3%, and distance detection tests carried out under 10 conditions resulted in an average distance detection error of 2.1 cm. The results show that the system was accurate and effective.
Indonesian Crude Oil Price (ICP) Prediction Using Support Vector Regression Algorithm
Authors: Des Suryani  , Fadhila Mutia
Published: April 2024

Indonesian crude oil prices (ICP) experience fluctuating movements, influenced by several factors and other conditions that make ICP prices difficult to predict. ICP price prediction can be done with the Support Vector Regression (SVR) method. The information utilized originates from the Ministry of Energy and Mineral Resources' official website, specifically focusing on crude oil pricing data for six primary types of crude oil: SLC, Attaka, Duri, Belida, Banyu, and SC. The data applied covers the time period from January-August 2023. The forecast of the ICP relies on the Dates Brent variable and the Alpha factor through the use of Support Vector Regression (SVR). In the case of a linear kernel, the parameters (epsilon) and C (cost) are determined using the Grid Search algorithm. In the Dated-Brent variable, the best parameter value is obtained with the value of C = 100 and e = 1 while for the Alpha variable, the best parameter value for the type of SLC crude oil is C = 0.01 and e = 0.01, SC value C = 10 and e = 1, Banyu value C = 100 and e = 0.1, Banyu value C = 100 and e = 0.1, Belida value C = 0.01 and e = 0.1, Attaka value C = 0.1 and e = 0.01 and Duri value C = 1 and e = 1. The Alpha value of the main crude oil type is the Duri crude oil type with the lowest RMSE value of 0.9651. The MAPE value for SC crude oil type = 19.55% and Duri = 19.46% is in the good category. The R2 value for Banyu crude oil = 0.60610, SC = 0.42717 and Duri = 0.50421 is in the good category and the MAPE value for Dated-Brent of 49.73% is included in the fair category.
Comparison of Machine Learning Algorithms in Detecting Tea Leaf Diseases
Authors: Ihsan Candra Nur , Agustina Nova , Naseer Muchammad , Gusdevi Harya , Rusdi Jack Febrian , Hadhiwibowo Ari , Abdullah Fahmi
Published: April 2024

Tea is one of the top ten export products sent from Indonesia to foreign countries. However, in recent years, the amount of tea leaf exports from Indonesia has decreased, although the value of the export impacts the country’s economic structure. In addition to market competition, Indonesia must maintain tea leaf production so that the increase in export decline is not significant or even increases tea leaf export production. To improve production quality and reduce production costs, early detection of tea leaf diseases is necessary. This study aims to classify tea leaf images for early detection of tea leaf disease so that appropriate treatment can be carried out early. This study compares machine learning algorithms to determine the best algorithm for detecting tea leaf diseases. The algorithms tested as performance comparisons in classifying tea leaf diseases are random forest (RF), support vector classifier (SVC), extra tree classifier (ETC), decision tree (DT), XGBoost classifier (XGB), and convolutional neural algorithms. Network (CNN). As a result, the average accuracy performance generated by ETC produces a higher value than other algorithms, i.e., getting an average accuracy performance of 77.47%. Another algorithm, SVC, has an average accuracy of 76.57%, RF of 76.12%, DT of 65.31%, XGB of 71.62%, and the lowest is CNN of 59.08%. ETC has been proven to be the most superior machine learning algorithm for detecting tea leaf diseases in this study.
THE IMPACT OF REMOTE LEARNİNG ACTİVİTİES ON VİSUAL ARTS TEACHER CANDİDATES' TECHNOLOGİCAL PEDAGOGİCAL CONTENT KNOWLEDGE SELF-EFFİCACY LEVELS
Authors: HİÇYILMAZ Yahya
Published: April 2024

Bu araştırmanın amacı, Görsel Sanatlar Öğretimi 2 dersi kapsamında gerçekleştirilen uzaktan eğitimle öğrenme faaliyetlerinin, öğretmen adaylarının Görsel Sanatlar Teknolojik Pedagojik Alan Bilgisi (GS-TPAB) öz-yeterlik düzeylerine
etkisini incelemektir. Araştırmada, zayıf deneysel desenlerden tek grup ön test ve son test deseni kullanılmıştır. Çalışma grubu, Türkiye'nin doğusundaki bir üniversitenin Resim-İş öğretmenliği programında üçüncü sınıfta öğrenim
gören toplam 27 öğretmen adayından oluşmaktadır. Veriler, “GS-TPAB Öz-Yeterlik Ölçeği” kullanılarak elde edilmiştir. Araştırmada, Görsel Sanatlar öğretmen adaylarının genel ölçek ve alt boyutlar açısından ön test ve son test ortalama
puanları arasında anlamlı bir fark olduğu tespit edilmiştir. Ayrıca, cinsiyete göre son test puanlarında anlamlı bir fark olduğu görülmüştür. Elde edilen sonuçlar doğrultusunda, eğitimde teknoloji tabanlı yaklaşımların benimsenmesi
ve öğretmen adaylarının dijital araçlarla etkileşimli materyaller tasarlama ve uygulama becerilerinin kazandırılması önerilmektedir.
EXPLORING EDUCATOR PERCEPTIONS TOWARD ARTS: INSIGHTS FROM ERASMUS PROGRAM PARTICIPANTS
Authors: Polat Bülent , Pilsudskienė Jūratė , Güneş Doğan , Basílio Cristina de Fátima Seixas , Plumeri Palma , Miśkowicz Ewa , Styś Katarzyna
Published: April 2024

This study explores the perceptions of educators toward arts, focusing on participants of the ERASMUS Program. Employing a correlational survey method, data was collected using the "Attitudes toward Arts Scale" from 52 educators. Descriptive
statistics revealed moderate to high attitudes across subscales, with a total mean score of 92.73 out of a possible 115. Subscale analysis highlighted nuanced perceptions across four dimensions: Necessity of Arts, Valuing Arts
Education, Personal Artistic Inclination, and Participation in Artistic Activities. Analysis of variance (ANOVA) and independent samples t-tests were conducted to explore differences in attitudes based on gender, age, and years
of service. Gender-based analysis showed no significant differences, while age-based analysis revealed variations in attitudes toward arts. Despite limitations, such as a small sample size, this study contributes to the understanding
of educator perceptions toward arts, offering implications for future research and educational practice within international exchange programs.
A Lei de Liberdade Econômica e seus reflexos no licenciamento de atividades econômicas pelos municípios
Authors: Lustoza Helton Kramer , De Lazari Rafael
Published: April 2024

o presente artigo apresenta uma reflexão sobre as diretrizes da Lei da Liberdade Econômica e seus reflexos na competência municipal em fiscalizar o comércio local. A pretexto de estabelecer normas gerais sobre a proteção da liberdade econômica do mercado, promovendo a dispensa de qualquer ato público para desenvolvimento de atividade econômica de baixo risco, contrariou a regra de competência constitucional. Além de outros pontos elencados nesta pesquisa, também se identifica a inconstitucionalidade quanto a este aspecto, por representar uma ofensa ao sistema federativo - ao promover a centralização da decisão sobre a regulação das atividades econômicas de interesse local.
200 Anos da Constituinte de 23: Normas Pré-Constitucionais
Authors: Martins Antunes Marcus Vinicius
Published: April 2024

RESUMO: O presente artigo baseia-se em investigação feita em pós-doutoramento na Universidade Federal do Rio Grande do Sul, nos anos 2016/2017. No campo do direito constitucional, versa sobre a existência de sucessivos atos, quase todos escritos, normativos, no período dos anos 1821/ 1823, que antecedem a convocação da assembleia constituinte de 1823, e posteriores à sua reunião e dissolução, até a outorga da Constituição de 1824. O objetivo era confirmar a existência de normas pré-constitucionais, estudadas em publicação anterior, capazes de pré-conformar o exercício do poder constituinte pela assembleia, e mesmo no ato formal de outorga da Constituição. Foi feita pesquisa primária de documentos, de bibliografia, através do método histórico-dialético. Confirma-se a hipótese inicial, com ajustes necessários. O exame dos decretos, conteúdo e circunstâncias, permite perceber uma linha de continuidade em direção ao processo de constitucionalização liberal, enquanto a linha de acesso à soberania nacional é elíptica, recua e avança, numa segunda etapa. O texto da constituição de 1824 é virtualmente a consolidação de tudo que se construiu no período entre fevereiro de 1821 a março de 1824.
A Pandemia de Covid-19 como Excludente de Responsabilidade na Inexecução de Contratos Administrativos
Authors: Bazzaneze Thais , Castro Junior Acidy Martins de
Published: April 2024

O presente trabalho, que toca a seara administrativa dos Municípios, apresenta análise acerca da inexecução do contrato administrativo no âmbito da inevitabilidade da força maior e da culpabilidade administrativa, mediante a aplicação de sanções das Leis Federais nº 8666/93 e nº 14.133/2021. Mediante a aplicação dos métodos bibliográfico e dedutivo, alcançou-se conclusões sobre a possibilidade de responsabilização das empresas nos casos de inadimplementos contratuais, especialmente quando verificada a falta de aptidão para o cumprimento das obrigações desde o momento da celebração do contrato.
ABORDAGEM ATUALIZADA SOBRE CETOACIDOSE DIABÉTICA: UMA REVISÃO ABRANGENTE DOS MECANISMOS FISIOPATOLÓGICOS, DIAGNÓSTICOS E ESTRATÉGIAS TERAPÊUTICAS.
Authors: Barbosa Vitoria Zabotte , Pelicioni Gabriel Bortolotti , Figueiredo Eduardo Lopes de
Published: April 2024

A cetoacidose diabética (CAD) é um distúrbio metabólico, caracterizada por hiperglicemia, desidratação, cetose e acidose metabólica, representando uma das complicações agudas do diabetes mellitus tipo
Caderno de Inovação - Artigos e Estudos de Caso do Programa ALI 2022/2023 - RURAL
Authors: Malta Alan Oliveira de , Arrais Aline Matos , Croccia Anderson Gonçaves , Santos Andressa Genezini dos , Sousa Andressa Rodrigues de Oliveira , Bezerra Andreza Marcolino , Moraes Anidene Christina Alves de , Rodrigues Beatriz , Santos Bruna Hanielle Carneiro dos , Aick Carlos Daniel Maciel , Lima Claudiana Alexandre de , Sá Diana Franco de , Araujo Neto Edgar Rodrigues de , Jesus Edilma Nunes de , Lopes Ely Ewerton Amorim , Silva Gabriela Sanches de Freitas , Silva Gleydson de Freitas , Souza Gustavo Batista de , Vernegue Henrique da Silva , Gomes Jaqueline de Sousa , Lauer Joice , Oliveira Kelly Souza de , Chaves Lívia Francyne Gomes , Macêdo Luciana de Paula Costa Alves , Silva Mariany Cruz Alves da , Carvalho Marina Feitosa , Silva Marquidones Teixeira da , Calhau Michelle Cruz Costa , Sousa Milena Ferreira de , Lucas Morgana Gomes Chaves , Bonfim Rosiane Costa , Silva Samira Souza da , Figueiredo Sayonara Maria Dantas de , Lemos Stella Vannucci , Matsuda Suzana da Costa , Moreira Thais de Castro , Rodrigues Zaqueu Ferreira , Sá Leila Francisca Campos de , Gonçalves Angelo Oliveira , Melo Valéria Franco de
Published: April 2024

O ALI Rural iniciou suas atividades em campo em dezembro de 2021 e ao longo de três ciclos, atuou com 578 bolsistas em 22 estados brasileiros, impactando mais de 14 mil negócios rurais. A metodologia aplicada em oito encontros individuais presenciais e dois encontros coletivos presenciais, promove uma jornada de inovação capaz de transformar a gestão dos negócios rurais. Ao todo foram mais de 14.966 negócios rurais acompanhados, com o aumento de 17,1% de faturamento nos negócios acompanhados, com 61% das empresas implementando ações proposta no Plano de Melhorias.
Do ponto de vista do conhecimento cientifico, a produção blibliográfica dos nossos Agentes Locais de Inovação, reflete um diagnóstico que observa as diversas especificidades do “rural”, produzindo um riquíssimo acervo de pesquisa sobre setores e cadeias de valores ligados ao setor. Estamos falando de um programa que atende a uma premissa de investigação cientfica in loco, nos rincões do Brasil.
O ALI Rural, nesse sentido, têm desenvolvido a cultura de inovação, mesclando a ação de extensionismo e de pesquisa, permitindo uma visão sistemica em relação ao cenário dos pequenos negócios rurais. É sob a estratégia de divulgação cientitica do programa ALI Rural, teremos uma representação dessas pesquisas aplicadas, como parte do conhecimento cientifico produzido nos Ciclos 1 e 2 do programa.
Sejam bem vindos e bem vindas à dimensão acadêmica de um dos maiores programas de extensão e pesquisa em relação ao universo dos pequenos negócios rurais. Que a leitura desses cadernos possa promover reflexões importantes acerca de estratégias possíveis para alavancar a condição empreendedora dos pequenos Produtores, bem como possibilitar um ambiente fértil de políticas públicas em relação a esse setor.

Ana Carolina Westrup
Victor Rodrigues Ferreira
Desafios e Perspectivas para a Conservação da Caatinga: Um Estudo Abrangente sobre a Biodiversidade e os Ecossistemas
Authors: Santos Geane Barbosa
Published: April 2024

Introdução
A Caatinga é um bioma único e rico em biodiversidade, porém enfrenta ameaças crescentes devido à expansão agrícola, desmatamento e mudanças climáticas. Neste estudo, investigamos os desafios enfrentados pela conservação da Caatinga e exploramos estratégias para proteger sua rica diversidade biológica e seus ecossistemas frágeis.
Metodologia
Realizamos uma revisão abrangente da literatura para compreender os padrões atuais de uso da terra, perda de habitat e mudanças climáticas na região da Caatinga. Além disso, conduzimos levantamentos de campo para avaliar a biodiversidade de diferentes áreas e analisamos os dados utilizando métodos estatísticos avançados.
Resultados e Discussões
Nossos resultados revelam uma redução alarmante na cobertura vegetal da Caatinga, com consequências diretas para a fauna e flora endêmicas. Identificamos áreas prioritárias para conservação, destacando a importância de corredores ecológicos e medidas de restauração para garantir a conectividade entre os fragmentos remanescentes. Além disso, discutimos o papel crucial das comunidades locais na conservação da biodiversidade e propomos estratégias de engajamento comunitário para promover a sustentabilidade na região.
Conclusão
Este estudo ressalta a urgência de ações coordenadas e eficazes para proteger a Caatinga e sua biodiversidade única. Propomos a implementação de políticas de conservação mais robustas, juntamente com iniciativas de desenvolvimento sustentável que valorizem os conhecimentos tradicionais e promovam a coexistência harmoniosa entre as populações humanas e a vida selvagem.
ANALISIS HUBUNGAN KERUGIAN NEGARA AKIBAT KORUPSI DENGAN DEMOGRAFI KORUPTOR DI MALUKU MENGGUNAKAN MODEL LOG LINEAR
Authors: Andini Nur , Kondo Lembang Ferry , Van Delsen M. S. Noya
Published: April 2024

Korupsi merupakan salah satu masalah pemerintahan yang terjadi hampir di seluruh Negara termasuk di Indonesia. Korupsi sangat berdampak buruk bagi kehidupan bangsa dan Negara. Dampak buruk dari korupsi diantaranya ialah angka kemiskinan yang kian meningkat, memiliki perekonomian yang tidak baik dan tidak stabil, ketertinggalan pembangunan daerah, serta tidak adanya kepercayaan terhadap lembaga pemerintah. Indonesia menjadi salah satu dari sepuluh negara di dunia dengan tingkat korupsi terparah. Dari data yang diperoleh di Pengadilan Negeri Ambon, kasus korupsi yang terjadi pada tahun 2015-2017 adalah sebanyak 153 kasus. Tujuan dari penelitian ini adalah untuk  menganalisis hubungan antara besarnya kerugian Negara akibat korupsi dengan variabel demografi koruptor di Provinsi Maluku menggunakan model Log Linier. Model Log Linier adalah suatu model statistika untuk menganalisis hubungan antara variabel dengan data yang bersifat kualitatif .Oleh karena itu, model ini dianggap tepat untuk mengkaji hubungan antara besarnya kerugian Negara akibat korupsi dengan variabel demografi koruptor.