bluuebunny/crossref_metadata_2025 huggingface dataset:
Design of a Device for Utilizing Hazardous and Toxic Waste as Fuel For a Stove (Burner) with a PID Control System
Authors: Findiastuti Weny , Dafid Ach , Annisa Rullie
Published: January 2025

Used oil waste is treated by spraying oil into the combustion furnace using wind from a blower. Before pouring oil into the furnace, it is necessary to manually heat it up to 300°C to burn off the fat. The controls in this study control the valve and blower to reach the desired temperature up to 800°C by utilizing a k-type thermocouple temperature sensor to detect temperature. This burner stove research uses the PID control method because it has a response that is fast enough to reach the desired temperature. The PID method is a controller that can reduce the error rate in a system to provide an output signal with a fast response, small error rate, and small overshoot. One of the contributions to this research is the importance of reducing the negative impact of hazardous and toxic waste on the environment and being an alternative solution in dealing with hazardous and toxic waste. In other conditions, this research makes an important contribution to the development of technology for processing and utilizing hazardous and toxic waste materials. Hopefully, this research will help contribute ideas and thoughts on preserving the environment and utilizing existing resources more efficiently. From the results of this study, based on the number of test results from seven tests, it can be said that the conditions are optimal because the fire produced from used oil does not contain black smoke. Meanwhile, the maximum temperature generated was 809 °C at the 73rd second, and the temperature continued to fall at the 94th second, and so on until it reached stability. These conditions indicate that the fuel speed ratio (used oil) and applied air pressure have started to improve so that the temperature is stable at 806 °C. In conclusion, the optimum test results at a flame temperature of 806 °C, the resulting flame does not produce black smoke, so the combustion of the used evaporative lubricant produces much cleaner exhaust emissions.
Website Vulnerability Analysis of AB and XY Office in East Java
Authors: Zaidan Muchammad , Noeraini Febyola , Sari Zamah , Akbi Denar Regata
Published: January 2025

Study this aim for analyze and identify vulnerability existing security on AB and XY Service Websites in East Java. Contribution study this is give more understanding deep about type vulnerability specific security and its impact to field website security. Method research used involve data scanning, analysis vulnerabilities, and Brute Force experiments. A total of 2 samples of AB and XY Service Websites were analyzed For identify existing vulnerabilities the data. However so, necessary noted that method study this own a number of limitations. First, size sample used possible limited to AB and XY Service Websites in East Java only, so generalization results study against other websites needs done with be careful. Second, analysis statistics used only covers analysis descriptive, so study this not yet investigate linkages between existing variables. Although thus, results study show exists necessary weaknesses and vulnerabilities corrected on AB and XY Service Websites. A number of findings covers problem website configuration and handling vulnerability that is not adequate. With highlight specific susceptibility, research this give more understanding deep about threat security faced by AB and XY Service Websites. In context field website security, research this own implication important. With understand existing vulnerabilities on AB and XY Service Websites, steps repair proper security can take for protect sensitive data and improve protection security in a manner whole. Kindly whole, research this identify and analyze vulnerability security on AB and XY Service Websites, as well give more understanding Specific about type existing vulnerabilities. Although there are limitations in method study this is the result still give valuable insight in field website security and can become base for repair more security effective and more data protection on both the AB and XY Service Websites.
Sentiment Analysis of Customers’ Review on Delivery Service Provider on Twitter Using Naive Bayes Classification
Authors: Basuki Ari
Published: January 2025

Customer evaluations on social media may help us remain competitive and comprehend our business's target market. By analysing consumer evaluations, a business owner can identify common themes, pain points, and desired features or enhancements.  By analysing customer feedback across multiple channels, such as social media, online reviews, and customer service interactions, businesses can rapidly identify any negative sentiment or potential brand damage. The contribution of our study is to evaluate the performance of the Naive Bayes method for classifying customer feedback on courier delivery services obtained via Twitter. The Naive Bayes algorithm is selected due to its simplicity, which facilitates efficient computation, suitability for large datasets, outstanding performance on text classification, and ability to manage high-dimensional data. In this investigation, the Naive Bayes classifier accuracy is 0.506, which is considered to be low.  According to our findings, the irrelevant feature classification resulting in an error throughout the categorization process. A large number of data appearance characteristics that do not correspond to the testing data category have been identified as a result of this occurrence.
Autoregressive Integrated Moving Average (ARIMA) Model for Forecasting Indonesian Crude Oil Price
Authors: Wati Masna , Haviluddin Haviluddin , Masyudi Akhmad , Septiarini Anindita , Hatta Heliza Rahmania
Published: January 2025

Crude oil is the main commodity of the global economy because oil is used as an ingredient for many industries globally and is the price base used in the state budget. Indonesian Crude Price (ICP) fluctuates following developments in world crude oil prices. A significant increase in crude oil prices will certainly disrupt the economy. Thus, the movement or fluctuation of ICP is essential for business players in the energy market, especially domestically. Therefore, crude oil price forecasting is needed to assist business people in making decisions related to the energy market. This study aims to find a suitable forecasting model for Indonesian crude oil prices using the Autoregressive Integrated Moving Average (ARIMA) method. The forecasting process used ICP time-series data per month for 50 types of crude oil within five years or 63 months. Based on the experimental results, it was found that the most fit ARIMA models were (0,1,1), (1,1,0), (0,1,0), and (1,2,1). The test results for April to September 2020 have a good and proper interpretation, except the type of BRC oil indicates inaccurate forecasts. The ARIMA error rate is very dependent on the value of the data before it is predicted and external factors, the more unstable the data value every month, the higher the error rate.
Development of a Remote Straw Mushroom Cultivation System Using IoT Technologies
Authors: Azman Novi , Habiburrohman Muhammad , Nugroho Endang Retno
Published: January 2025

Indonesia's tropical climate creates vast potential for straw mushroom cultivation. However, crop failures are frequent during the rainy season due to lower temperatures. To address this challenge, this paper presents an innovative, IoT-based system designed to remotely control and monitor temperature and humidity in mushroom cultivation sites, thereby minimizing crop failure and optimizing production. The proposed system employs a DHT11 sensor to measure temperature and humidity levels accurately. A DS3231 module is incorporated to schedule automatic watering procedures, ensuring adequate hydration for the mushrooms without manual intervention. For real-time monitoring, an ESP32-Cam is used to capture images of the mushroom cultivation site. The core of this system is a NodeMCU microcontroller, which processes environmental data and automatically adjusts the cultivation conditions. The system triggers a heater if the temperature falls below 30°C, or an exhaust fan if it exceeds 35°C. Similarly, a humidifier activates if humidity falls below 80%, and an exhaust fan turns on when humidity exceeds 90%. To provide users with instant updates, the system integrates with the Blynk application, sending notifications when these specified conditions are met. This feature allows for prompt intervention when necessary, facilitating optimal growth conditions at all times. During testing, the proposed system demonstrated its effectiveness, enabling successful straw mushroom cultivation within nine days. Furthermore, it achieved this with modest power consumption, using a total of 661.608Wh. This system offers a promising solution to improve straw mushroom farming in regions with similar climates to Indonesia.
Experimenting with the Hyperparameter of Six Models for Glaucoma Classification
Authors: Ilham Muhammad , Prihantoro Angga , Perdana Iqbal Kurniawan , Magdalena Rita , Saidah Sofia
Published: January 2025

Glaucoma, being one of the leading causes of blindness worldwide, often presents without noticeable symptoms, making early detection crucial for effective treatment. Numerous studies have been conducted to develop glaucoma detection systems. In this particular study, a glaucoma detection system using the CNN method was developed. The models employed in this study include AlexNet, Custom Layer, MobileNetV2, EfficientNetV1, InceptionV3, and VGG19. For training, an augmented RIM-ONE DL dataset was utilized. Hyperparameter experiments were conducted to determine the most optimal parameters for each model, specifically testing batch size, learning rate, and optimizer. The hyperparameter optimization process yielded the optimal parameters for each model. However, it is important to note that the MobileNetV2, InceptionV1, and VGG19 models exhibited signs of overfitting in the training graph results. Among the models, the custom layer model achieved the highest accuracy of 93%, while InceptionV3 attained the lowest accuracy at 83.5%. Testing of the models was performed using data from Cicendo Eye Hospital and the RIM-ONE DL testing dataset. Based on the testing results, it was found that InceptionV3 outperformed the other models in predicting images accurately. Therefore, the study concluded that high accuracy in training does not necessarily indicate superior performance in testing, particularly when limited variation exists in the training dataset.
Gender Classification Based on Electrocardiogram Signals Using Long Short Term Memory and Bidirectional Long Short Term Memory
Authors: Halim Kevin Yudhaprawira , Nugrahadi Dodon Turianto , Faisal Mohammad Reza , Herteno Rudy , Budiman Irwan
Published: January 2025

Gender classification by computer is essential for applications in many domains, such as human-computer interaction or biometric system applications. Generally, gender classification by computer can be done by using a face photo, fingerprint, or voice. However, researchers have demonstrated the potential of the electrocardiogram (ECG) as a biometric recognition and gender classification. In facilitating the process of gender classification based on ECG signals, a method is needed, namely Long Short-Term Memory (LSTM) and Bidirectional Long Short-Term Memory (Bi-LSTM). Researchers use these two methods because of the ability of these two methods to deal with sequential problems such as ECG signals. The inputs used in both methods generally use one-dimensional data with a generally large number of signal features. The dataset used in this study has a total of 10,000 features. This research was conducted on changing the input shape to determine its effect on classification performance in the LSTM and Bi-LSTM methods. Each method will be tested with input with 11 different shapes. The best accuracy results obtained are 79.03% with an input shape size of 100×100 in the LSTM method. Moreover, the best accuracy in the Bi-LSTM method with input shapes of 250×40 is 74.19%. The main contribution of this study is to share the impact of various input shape sizes to enhance the performance of gender classification based on ECG signals using LSTM and Bi-LSTM methods. Additionally, this study contributes for selecting an appropriate method between LSTM and Bi-LSTM on ECG signals for gender classification.
Object Classification Model Using Ensemble Learning with Gray-Level Co-Occurrence Matrix and Histogram Extraction
Authors: Kurniati Florentina Tatrin , Manongga Daniel HF , Sediyono Eko , Prasetyo Sri Yulianto Joko , Huizen Roy Rudolf
Published: January 2025

In the field of object classification, identification based on object variations is a challenge in itself. Variations include shape, size, color, and texture, these can cause problems in recognizing and distinguishing objects accurately. The purpose of this research is to develop a classification method so that objects can be accurately identified. The proposed classification model uses Voting and Combined Classifier, with Random Forest, K-NN, Decision Tree, SVM, and Naive Bayes classification methods. The test results show that the voting method and Combined Classifier obtain quite good results with each of them, ensemble voting with an accuracy value of 92.4%, 78.6% precision, 95.2% recall, and 86.1% F1-score. While the combined classifier with an accuracy value of 99.3%, a precision of 97.6%, a recall of 100%, and a 98.8% F1-score. Based on the test results, it can be concluded that the use of the Combined Classifier and voting methods is proven to increase the accuracy value. The contribution of this research increases the effectiveness of the Ensemble Learning method, especially the voting ensemble method and the Combined Classifier in increasing the accuracy of object classification in image processing.
Nondestructive Chicken Egg Fertility Detection Using CNN-Transfer Learning Algorithms
Authors: Saifullah Shoffan , Drezewski Rafal , Yudhana Anton , Pranolo Andri , Kaswijanti Wilis , Suryotomo Andiko Putro , Putra Seno Aji , Khaliduzzaman Alin , Prabuwono Anton Satria , Japkowicz Nathalie
Published: January 2025

This study explores the application of CNN-Transfer Learning for nondestructive chicken egg fertility detection. Four models, VGG16, ResNet50, InceptionNet, and MobileNet, were trained and evaluated on a dataset using augmented images. The training results demonstrated that all models achieved high accuracy, indicating their ability to accurately learn and classify chicken eggs’ fertility state. However, when evaluated on the testing set, variations in accuracy and performance were observed. VGG16 achieved a high accuracy of 0.9803 on the testing set but had challenges in accurately detecting fertile eggs, as indicated by a NaN sensitivity value. ResNet50 also achieved an accuracy of 0.98 but struggled to identify fertile and non-fertile eggs, as suggested by NaN values for sensitivity and specificity. However, InceptionNet demonstrated excellent performance, with an accuracy of 0.9804, a sensitivity of 1 for detecting fertile eggs, and a specificity of 0.9615 for identifying non-fertile eggs. MobileNet achieved an accuracy of 0.9804 on the testing set; however, it faced challenges in accurately classifying the fertility status of chicken eggs, as indicated by NaN values for both sensitivity and specificity. While the models showed promise during training, variations in accuracy and performance were observed during testing. InceptionNet exhibited the best overall performance, accurately classifying fertile and non-fertile eggs. Further optimization and fine-tuning of the models are necessary to address the limitations in accurately detecting fertile and non-fertile eggs. This study highlights the potential of CNN-Transfer Learning for nondestructive fertility detection and emphasizes the need for further research to enhance the models’ capabilities and ensure accurate classification.
Topic Detection on Twitter Using Deep Learning Method with Feature Expansion GloVe
Authors: Ramadhanti Windy , Setiawan Erwin Budi
Published: January 2025

Twitter is a medium of communication, transmission of information, and exchange of opinions on a topic with an extensive reach. Twitter has a tweet with a text message of 280 characters. Because text messages can only be written briefly, tweets often use slang and may not follow structured grammar. The diverse vocabulary in tweets leads to word discrepancies, so tweets are difficult to understand. The problem often found in classifying topics in tweets is that they need higher accuracy due to these factors. Therefore, the authors used the GloVe feature expansion to reduce vocabulary discrepancies by building a corpus from Twitter and IndoNews. Research on the classification of topics in previous tweets has been done extensively with various Machine Learning or Deep Learning methods using feature expansion. However, To the best of our knowledge, Hybrid Deep Learning has not been previously used for topic classification on Twitter. Therefore, the study conducted experiments to analyze the impact of Hybrid Deep Learning and the expansion of GloVe features on classification topics. The total data used in this study was 55,411 datasets in Indonesian-language text. The methods used in this study are Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), and Hybrid CNN-RNN. The results show that the topic classification system with GloVe feature expansion using the CNN method achieved the highest accuracy of 92.80%, with an increase of 0.40% compared to the baseline. The RNN followed it with an accuracy of 93.72% and a 0.23% improvement. The CNN-RN Hybrid Deep Learning model achieved the highest accuracy of 94.56%, with a significant increase of 2.30%. The RNN-CNN model also achieved high accuracy, reaching 94.39% with a 0.95% increase. Based on the accuracy results, the Hybrid Deep Learning model, with the addition of feature expansion, significantly improved the system's performance, resulting in higher accuracy.
Optimization of Machine Learning Models with Segmentation to Determine the Pose of Cattle
Authors: Siregar Amril Mutoi , Hartono Wijaya Sony , Fauzi Ahmad , Sen Tjong Wan , Faisal Sutan , Tukino Tukino , Cahyana Yana
Published: January 2025

Image pattern recognition poses numerous challenges, particularly in feature recognition, making it a complex problem for machine learning algorithms. This study focuses on the problem of cow pose detection, involving the classification of cow images into categories like front, right, left, and others. With the increasing popularity of image-based applications, such as object recognition in smartphone technologies, there is a growing need for accurate and efficient classification algorithms based on shape and color. In this paper, we propose a machine learning approach utilizing Support Vector Machine (SVM) and Random Forest (RF) algorithms for cow pose detection. To achieve an optimal model, we employ data augmentation techniques, including Gaussian blur, brightness adjustments, and segmentation. The proposed segmentation methods used are Canny and Kmeans. We compare several machine learning algorithms to identify the optimal approach in terms of accuracy. The success of our method is measured by accuracy and Receiver Operating Characteristic (ROC) analysis. The results indicate that using the Canny segmentation, SVM achieved 74.31% accuracy with a testing ratio of 90:10, while RF achieved 99.60% accuracy with the same testing ratio. Furthermore, testing with SVM and K-means segmentation reached an accuracy of 98.61% with a test ratio of 80:20. The study demonstrates the effectiveness of SVM and Random Forest algorithms in cow pose detection, with Kmeans segmentation yielding highly accurate results. These findings hold promising implications for real-world applications in image-based recognition systems. Based on the results of the model obtained, it is very important in pattern recognition to use segmentation based on color even though shape recognition.
THEOLOGY OF ANCIENT EGYPT AS PRE-PHILOSOPHY
Authors: Ziborova Daria
Published: January 2025

The article is devoted to the problem of genesis the philosophical tradition from pre-philosophical components using the example of Ancient Egyptian theology. The author poses the question of criteria - how and on what basis it is possible to identify elements of speculative thinking in religious and mythological texts of ancient cultures. The approaches to the definition of pre-philosophy, its separation from the mythological tradition, and the rational and irrational components in it are discussed. The connection between abstract and mytho-poetic description and expression of reality is considered.

The article contains a review of academic sources that, firstly, consider the influence of the pre-philosophical component of Eastern cultures on the genesis of ancient Greek philosophy (Frankfort, West, Cornford, Bernal, Burkert), and, secondly, analyze religious and mythological representations in the texts of Ancient Egypt as certain explainatory sense constructions that have features of philosophical or pre-philosophical (Assmann, Allen, Wilson, Butler, Manley, etc.).

Based on the literature review, a specific program for the study of ancient Egyptian theology as a pre-philosophical tradition, which can be regarded as universal, i.e., relevant to any ancient tradition, has been created. It is shown that such research should be based on the following semantic contexts analysis: 1. consideration of cosmogonic ancient Egyptian beliefs as a system of metaphysical questions; 2. analysis of the ideas about the essence of the god-creator and the ways of creating the world by him through the research of the texts describing cosmogony and eschatology; 3. identification and interpretation of the main concepts describing and structuring the universe, such as the categories of time-eternity (neheh and djet), which make possible to describe the ontological worldview foundations of the Ancient Egyptians; 4. description of the ideas of justice, world harmony and law (maat) - both in the social and metaphysical dimensions; 5. study of ethical guidelines in the so-called “literature of wisdom” (sebayt), which will allow to describe the existential foundations of human existence in the culture of Ancient Egypt
Менеджмент в умовах глобальних викликів і сучасних реалій. Методологічний аспект
Authors: Гришко Володимир , Гришко Віктор
Published: January 2025

Розвиток сучасних економічних систем супроводжується глобальними викликами і проблемами сучасних реалій, які мають суттєвий вплив на менеджмент і обумовлюють потребу в змінах методології менеджменту в тому числі її ключових принципів, зміни пріоритетів в їх виборі з орієнтацією на адекватність, адаптивність, прагматизм і професіоналізм. У статті розглянуто залежність ефективності методології менеджменту від глобальних викликів і динамічних проблем, викликаних нестабільними реаліями сьогодення України. Вивчено та проаналізовано, систематизовано та узагальнено вагому кількість дефініцій поняття менеджмент, виявлено онтологічну проблему для розв’язання якої запропоновано бачення авторів стосовно визначення поняття менеджмент, яке в лаконічній формі окреслює його сутнісні ознаки. Встановлено, що дієвість класичної управлінської методології обмежується тенденцією зростання динамічних змін обставин і ситуацій в зовнішньому і внутрішньому середовищах, превалюванням нелінійних зв’язків і нефункціональних залежностей між факторами впливу на об’єкт управління. Економічні системи функціонують і розвиваються в умовах невизначенності, все більше ситуацій в організаціях пов’язані з неструктурованими проблемами, які породжують значну ризикованість управлінських рішень. Пропонуються суттєві зміни до методології менеджменту, її осучаснення. Зокрема такої важливої її складової як принципи. Окрім добре відомих класичних принципів, зокрема, поєднання демократизму і централізації, повноважень і відповідальності, єдиноначальності і колегіальності, матеріального і морального стимулювання, економічності та ефективності, спадкоємності господарських рішень, підпорядкування особистих інтересів загальним, автори наголошують на важливості в умовах глобальних викликів і сучасних реалій принципів адекватності, адаптивності, прагматичності і професіоналізму. Наявність різних визначень поняття менеджмент, що з одного боку свідчить про багатозначність цього поняття, а з іншого множинність дефініцій цього поняття приводить до суттєвого розходження у розумінні того, що являє собою об’єкт дослідження, яка його мета і істотні ознаки. Для розв’язання цієї онтологічної проблеми пропонуємо власне визначення поняття менеджмент сучасний менеджмент сучасний менеджмент: творчий процес застосування релевантної управлінської методології по забезпеченню ефективності спільної діяльності людей. Метою даного дослідження є удосконалення, осучаснення методології менеджменту, яка на відміну від природничих наук не характеризується детермінованістю, точністю і об’єктивністю. В ході дослідження використана комбінація кількісних і якісних методів дослідження емпіричного і теоретичного рівня сучасних парадигм наукового дослідження, зокрема, систематизація та узагальнення, аналіз і синтез в тісній комбінації з індукцією і дедукцією.
Проблеми та перспективи розвитку подієвого туризму в Україні
Authors: Тонкошкур Максим , Кравцова Софія
Published: January 2025

У статті розглянуто можливості ринку подієвого туризму Україні щодо відновлення після повномасштабного вторгнення російських військ, зокрема організацію культурних та соціальних заходів під час війни. Визначено ключові фактори розвитку цього ринку, серед яких збереження культурної ідентичності, згуртування громадян та підтримка морального духу населення. Досліджено роль культурних подій у підтримці національної стійкості та психоемоційної реабілітації, а також важливість міжнародної солідарності для популяризації України. Проаналізовано проблеми розвитку подієвого туризму, зокрема відсутність належної інфраструктури та економічну нестабільність. Запропоновано шляхи подолання цих проблем через інтеграцію міжнародних стандартів, залучення інвестицій та використання цифрових платформ.
Gender leadership in European countries: The role of women in business transformation
Authors: Kyrychenko Olha , Kyrychenko Mykola
Published: January 2025

This article explores gender equality trends in the European Union, focusing on women’s participation in leadership roles, government cabinets, and political institutions, particularly the European Parliament. It shows that while gender equality at high levels of governance and business is improving, further efforts are needed for true equality. The study highlights an increase in women’s representation in government and political bodies, but they remain underrepresented in senior leadership roles, signaling the need for more proactive measures. In the European Parliament, a rising proportion of women reflects the effectiveness of gender-focused policies, though male dominance persists, requiring continued quotas and support programs. The analysis of women in leadership positions in major European companies shows progress, though full gender balance has yet to be achieved. More active corporate policies are needed to reduce gender imbalances. Overall, the article emphasizes the importance of continued efforts to ensure gender equality, focusing on career advancement and equal access to opportunities.
Modeling of production process by the method of works maximum approximation
Authors: Dyachenko Evgen , Zyma Oleksandr , Pahomov Roman
Published: January 2025

The work is devoted to mathematical modeling of production processes. Existing methods of production processes modeling are analyzed. Calculated workflow schemes are proposed when planning the manufacturing process by maximizing work approximation. The dependences of the time parameters calculation and the conditions of the proposed calculation schemes application are given. The method of the time parameters calculation of production processes execution by the method of works maximum approximation is offered. The procedure of calculation and construction of production processes calendar schedule is given. The advantages of the proposed methodology in comparison with existing modeling methods are analyzed
Utilizing low-frequency ultrasound as a countermeasure to asphalt-resin-paraffin deposition in oil pipelines
Authors: Nazarenko Ivan , Nesterenko Tetiana , Nesterenko Mykola , Bernyk Iryna
Published: January 2025

The experimental data on the low-frequency ultrasound effect on asphalt-resin-paraffin deposits (ARPD) occurring in oil transportation through pipelines are presented. As a result of the empirical data statistical processing, a correlation was obtained, which enables the prediction of the ultrasonic exposure time required to remove ARPD from the surface of the pipes. The temperature regime changed from the time of ARPD formations exposure to the ultrasonic influence was analyzed. The proposed algorithm for finding the ultrasonic treatment optimal operational parameters can be used not only in the selection of ultrasonic equipment parameters, which control ARPD in pipelines but also in the run-in hole ultrasonic equipment’s operating parameters selection in certain fields conditions
Many years of experience of standarding the medium component of wind load on building structures
Authors: Pichugin Sergii , Klochko Lina
Published: January 2025

The article contains a systematic review of scientific and technical publications on the problems of wind load for the 90-year period from the 30s of the twentieth century to the present. It is emphasized that this load on the buildings has a complex physical nature and changeable nature. These features are reflected in the sections of design standards of building structures that contain codes of wind load. The main attention is paid to the analysis of the evolution of structural design codes in terms of changes in wind territorial zoning and design factors, the appointment of specified and design values ​​of wind load. It is noted that most of the parameters of wind load codes are probabilistic in nature and require the use of statistical methods to justify them. There is a high scientific level of domestic standards DBN B.1.2-2006 "Loads and loadings", which have a modern probabilistic basis and are associated with Eurocode standards. Scientific results which can be included in the following editions of codes of wind loading are allocated
Comparative analysis of calculation models of soil behavior on the example of the tray experiment`s modeling
Authors: Vynnykov Yuriy , Razdui Roman
Published: January 2025

Graphs of settlements of stamp experiment in the modeling of the tray experiment with variable reinforcement parameters to determine the effect of reinforcement with vertical soil-cement elements (SCE) of weak clay bases of strip foundations of buildings are shown. The simulation results of the experiment using the Mohr-Coulomb ideal elastoplastic model of soil behavior and the Hardening soil model isotropic compaction model of soil behavior by the finite element method for estimating the stress-strain state of the "soil-cement base – rigid strip stamp" system when using different models of the SCE assignment are presented. A comparison of the methods of modeling the stress-strain state with the capabilities of the Plaxis 3D software package is carried out. The most optimal models of soil behavior for the simulation of SCE under existing soil conditions have been determined
Determination of the vibrating table kinetic energy
Authors: Korobko Bogdan , Zhyhylii Serhii , Korotych Yuriy
Published: January 2025

The article determines the total kinetic energy of the vibrating table, in which the vibrator is fixed on a lever vertically in the center under the vibrating plate. To find the total kinetic energy, a kinematic diagram of the vibrating table under study was drawn up, and the functional dependence of the vibrating table total kinetic energy on the factors acting on it obtained. A graph of the change in the vibrating table kinetic energy under study was drawn depending on the lever length, on which the vibrator was fixed. The analysis of the resulting dependence indicates an increase in the kinematic energy of the vibrating table with an increase in the lever length. The obtained kinetic energy is necessary for the development of an above-mentioned equipment mathematical model, which will be compiled later using Lagrange equations of the second kind
Meta Analysis: Factors Affecting Alcohol Consumption in Adolescents
Authors:   Masters Program in Public Health, Universitas Sebelas Maret, Indonesia, Hanif Ihsan , Mardiah Ardiana ,   Masters Program in Public Health, Universitas Sebelas Maret, Indonesia, Yolanda Rachmawaddah ,   Masters Program in Public Health, Universitas Sebelas Maret, Indonesia, Murti Bhisma ,   Masters Program in Public Health, Universitas Sebelas Maret, Indonesia, Munawaroh Siti Mar'atul ,   School of Health Sciences Mambaul Ulum, Surakarta, Indonesia
Published: January 2025

Background: Since alcohol is obtained easily, so it tends to be widely abused. The factors that cause a teenager to consume alcohol are individual factors/individual personality, and envi¬ron¬mental factors. This study aims to estimate the factors that affect alcohol consumption in adolescents.

Subjects and Method: This study used systematic review and meta-analysis using PICO. Population: adolescents. Interventions: drinking parents, drinking friends, smoking. Comparison: non-drinking parents, non-drinking friends, non-smoking. Result: alcohol consumption. The articles used in this study were derived from 2 databases, namely Google Scholar and Science Direct. The article's keywords were ""teenager" AND "drinking parents" AND "drinking friends" AND "smoke" AND “alcohol consumption". The articles included in this study were full paper articles, cross-sectional study design, publication year ranged from 2019-2023 and the measure of association used was Adjusted Odds Ratio. The articles were analyzed using the Review Manager 5.4
application.

Results: Seven cross-sectional studies showed that drinking friends increased alcohol consumption by 5.09 times compared to non-drinking friends, and the result was statistically significant (aOR=5.09; CI 95%= 2.64 to 9.81; p= 0.001). Seven cross-sectional studies showed that drinking parents increased alcohol consumption by 1.99 times compared to non-drinking parents, and the result was statistically significant (aOR=1.99; CI 95%= 1.50 to 2.64; p= 0.001). Seven cross-sectional studies showed that smoking can increase alcohol consumption by 2.09 times compared to nonsmoking, and the result was statistically significant (aOR=2.09; CI 95%= 1.32 to 3.30; p= 0.001).

Conclusion: Smoking-adolescents, drinking parents, and drinking friends increase their likelihood of consuming alcohol.

Keywords: smoking, drinking friends, alcohol consumption.
The Influence of Audit Firm Culture on the Adoption of Artificial Intelligence in Audit Firms
Authors: Ma-Nlep Massoda
Published: January 2025

Today, automation, digitization, and integration of AI are becoming increasingly pervasive in the work environment, and as AI applications become integral to the rapid evolution of digital workplaces, a critical audit concern revolves around how professionals respond to this new milieu; in this realm, the adoption of AI in professional practice may require a cultural shift given that auditors tend to be cautious individuals (Davidson & Dalby, 1993).
As a cutting-edge information technology, AI can offer several advantages in auditing, including the ability to process large amounts of data, such as bank statements and legal contracts, much faster than human auditors, leading to more efficient reconciliation of accounts and improved audit quality. AI also minimizes over testing, allowing auditors to perform more efficient and targeted audit procedures (Dennis, 2024).
However, there are significant challenges to analyzing such data and producing up-to-date audit documentation, such as AI's inability to perform actions or controls independently and its lack of ability to make moral or ethical judgments (CPA Canada & AICPA, 2020). The challenges posed by AI, coupled with the inherently risk-averse nature of auditors, particularly audit partners facing potential litigation risks, highlight the significant influence of tone at the top in shaping audit firm culture. This risk aversion may contribute to auditors' reluctance to adopt a new and relatively unproven technology such as AI.
Conservation Laws and Symmetry Multi-Reductions of Two (2 + 1)-Dimensional Equations: The Zakharov-Kuznetsov (ZK) Equation and a Nonlinear Wave Equation
Authors: Kakuli Molahlehi Charles , Sinkala Winter , Masemola Phetogo
Published: January 2025

The construction of invariant solutions is a key application of Lie symmetry analysis in studying partial differential equations. The generalised double reduction method, which uses both symmetries and conservation laws of a PDE or system of PDEs, provides a powerful framework for constructing such solutions. This paper contributes to the application of the generalised doublereduction method by analysing two (2 + 1)-dimensional equations: the Zakharov-Kuznetsov (ZK) equation and a nonlinear wave equation. We extend the work of Bokhari et al. [6, 7] on the nonlinear wave equation by performing a second symmetry reduction using previously unused inherited symmetries. For the ZK equation, we identify its Lie point symmetries, construct four conservation laws using the multiplier method, and determine their associated Lie point symmetries. This allows for symmetry reductions using each conservation law. This paper provides a detailed account of the generalised double reduction method, including the exploitation of inherited symmetries at each reduction step.
The Learning Skills and Level of Understanding of Grade 9 Students on a Mathematics Lesson on Sequences and Series
Authors: Luga Mary Joy , Samson Harold , Buan Amelia , Nabua Edna , Salazar Douglas
Published: January 2025

This study assesses the Algebra skills of Grade 9 students at IDS post-pandemic, using an open-ended mathematics questionnaire during the first week of the second quarter. It evaluates students' critical and creative thinking, and problem-solving abilities. Results show that while students have made progress in creative thinking and can generate original ideas, their understanding of Algebra remains at a basic level. Critical thinking and problem-solving skills are also at a benchmark level, indicating that students often replicate information without thorough analysis or questioning. To address these issues, the study recommends targeted remediation to enhance students' comprehension and skills in Algebra. It also suggests conducting a comparative qualitative study and exploring how different skill levels relate to overall understanding.
Generalized Conformable Hamiltonian Dynamics with Higher-Order Derivatives
Authors: M. Alawaideh Yazen , Ramazanova Aysel , Issaadi Hayat , Al-khamiseh Bashar. M. , Bilal Muhammad , Baleanu Dumitru Baleanu
Published: January 2025

In this paper, we investigate higher-order calculus using the conformable derivative and integral. We use a fractional variant of the calculus of variations to obtain the Euler-Lagrange equation. Our route integral quantization approach streamlines the procedure by integrating solely over canonical coordinates q, eliminating the requirement to integrate higher-order derivatives . In addition, we employ the conformable derivative to develop canonical conserved energy-momentum and Ostrogradsky’s Hamiltonian. Furthermore, we generalized the Hamilton formulation for higher order derivatives and applied this new formulation to obtained equations of motion for a one dimensional point particle.
Jordan $\varphi$-centralizers on Semiprime and Involution Rings
Authors: Ansari Abu Zaid , Shujat Faiza , Kamel Alwaleed , Fallatah Ahlam
Published: January 2025

The intention of the current investigation is to demonstrate that if an additive mapping $\mathcal{H}:R\to R$ fulfills any one of the following identities:\begin{enumerate}\item [$(i)$] $3\mathcal{H}(r^{3p})=\mathcal{H}(r^p)\varphi(r^{2p})+\varphi(r^p) \mathcal{H}(r^{p})\varphi(r^p)+ \varphi(r^{2p})\mathcal{H}(r^p)$\item [$(ii)$] $2\mathcal{H}(r^{2p})=\mathcal{H}(r^p)\varphi(r^{p})+\varphi(r^p)\mathcal{H}(r^{p})$\item [$(ii)$] $\mathcal{H}(r^{3p})=\varphi(r^p) \mathcal{H}(r^{p}) \varphi(r^p)$ for all $r\in R$,\end{enumerate}then $\mathcal{H}$ is a $\varphi$-centralizer on $R$, where $R$ is any suitable, torsion-free semiprime ring and $p$ is a fixed integer greater than or equal to 1. As a result of the primary theorems, involution $I_v$ related observations are also provided.  We will also consider   criticism and discussion alongside the proofs of theorems. Suitable  examples given in favor of justification.
A Certain Class of Filters in Generalized Complemented Distributive Lattices
Authors: Sirisetti Ramesh , Gunda Jogarao , Bandaru Ravikumar , Shukla Rahul
Published: January 2025

In this paper, we introduce $K^g$-filters jointly  derived from the class of ideals and the class of generalized complementations  in a generalized complemented distributive lattice. We obtain some algebraic properties on the obtained class, and we provide some counter-examples. Mainly we derive some Boolean algebras (distributive lattices) through the class of $K^g-$filters in a generalized complemented distributive lattice. Finally, we introduce normal $K^g$-filters in a generalized complemented distributive lattice and then prove that the class of normal $K^g$-filters is a Boolean algebra.
Achieving Edge Consensus in Hybrid Multi-AgentSystems: Scaled Dynamics and Protocol Design
Authors: Park Choonkil , Donganont Siriluk , Donganont Mana
Published: January 2025

In contrast to existing research on consensus problems that primarily addresses the node dynamics of multi-agent systems, this study focuses on achieving consensus among the states of edges within a network. Initially, the scaled consensus of edge dynamics in hybrid multi-agent systems is investigated for both undirected and directed topologies. Subsequently, necessary and sufficient conditions are derived for both directed and undirected topologies to facilitate the design of consensus protocols aimed at resolving edge consensus challenges. Finally, numerical examples are provided to substantiate the effectiveness of the theoretical results.
Edge Geodetic Dominating Sets of Some Graphs
Authors: Quije Clint Joy , Mariano Rochelleo , Ahmad Eman
Published: January 2025

Let $G$ be a simple graph. A subset $D$ of vertices in $G$ is a dominating set of $G$ if every vertex not in $D$ has at least one neighbor in $D$. The domination number $\gamma(G)$ of $G$ is the minimum cardinality of a dominating set of $G$. An edge geodetic set of $G$ is a set $S \subseteq V(G)$ such that every edge of $G$ is contained in a geodetic joining some pair of vertices in $S$. The edge geodetic number $g_e(G)$ of $G$ is the minimum cardinality of edge geodetic set. A set of vertices $S$ in $G$ is an edge geodetic dominating set of $G$ if $S$ is both an edge geodetic set and a dominating set. The minimum cardinality of an edge geodetic dominating set of $G$ is its edge geodetic domination number and is denoted by $\gamma_{g_e}(G)$. In this study, we determined the edge geodetic domination number of graphs obtained through the deletion of independent edges of complete graphs and graphs resulting from the $K_r$-gluing of complete graphs. It is also shown that for any positive integers $2 \leq a \leq b$, there exists a connected graph $G$ such that $g_e(G)=a$ and $\gamma_{g_e}(G)=b$.
New Improvements to Heron and Heinz Inequality Using Matrix Techniques
Authors: Rashid Mohammad H.M. , Mohammad Salameh Wael Mahmoud
Published: January 2025

This paper presents a comprehensive study on matrix means interpolation and comparison, extending the parameter $\vartheta$ from the traditional closed interval $[0,1]$ to encompass the entire positive real line, denoted as $\mathbb{R}^+$. The research delves into further results involving Heinz means, proposing novel scalar adaptations of Heinz inequalities that integrate Kantorovich's constant. Additionally, the operator version of these inequalities is strengthened. A key contribution of this work is the development of refined Young's type inequalities tailored for the traces, determinants, and norms of positive semi-definite matrices. These refinements offer deeper insights into matrix analysis, especially in the context of operator theory and inequality theory. Through these advancements, the paper enhances the mathematical framework for studying matrix means and their associated inequalities, providing useful tools for both theoretical exploration and practical applications in linear algebra and related fields.
On the Closability of Class Totally Paranormal Operators
Authors: Rashid Mohammad H.M. , Alnabulsi Salam
Published: January 2025

This article explores the analysis of various spectral properties pertaining to totally paranormal closed operators, extending beyond the confines of boundedness and encompassing operators defined in a Hilbert space. Within this class, closed symmetric operators are included. Initially, we establish that the spectrum of such an operator is non-empty and provide a char-acterization of closed-range operators in terms of the spectrum. Building on these findings, we proceed to prove Weyl’s theorem, demonstrating that for a densely defined closed totally paranormal operator T, the difference between the spectrum σ(T) and the Weyl spectrum σw(T) equals the set of all isolated eigenvalues with finite multiplicities, denoted by π00(T). In the final section,we establish the self-adjointness of the Riesz projection Eμ corresponding to any non-zero isolated spectral value μ of T. Furthermore, we show that this Riesz projection satisfies the relationships ran(Eμ) = ker(T − μI) = ker(T − μI)∗. Additionally, we demonstrate that if T is a closed totally paranormal operator with a Weyl spectrum σw(T) = 0, then T qualifies as a compact normal operator.
Analysis and Irregularity Measurements in the Identical Structures of Carbon nanocones $\boldsymbol{C N C}_{\boldsymbol{t}}(\mathrm{m})$
Authors: Jebreen Kamel , Kanj Hassan , Nawajah Inad , Chendeb Nancy , Amro Rami M.
Published: January 2025

Irregularity indices are topological indices by nature. They are highly helpful for determining the quantitative topography of nonregular graphs' molecular structures. Both the quantitative structure-property relationship (QSPR) and the quantitative structure-activity relationship (QSAR) depend heavily on the computation of abnormalities in a graph. It is made up of several chemical and physical characteristics, including resistance, enthalpy, entropy, toxicity, melting and boiling points, and entropy. This paper examines the application of different irregularity indices to identify irregularity measurements (IMs) in the network of carbon nanocone molecules $C N C_t(m)$, for $t=4,5$, and $t$. We have used different irregularity indices such as $\operatorname{Irdif}\left(\xi_t\right)$ $, \operatorname{Al}\left(\xi_t\right), $ $ \operatorname{Irl}\left(\xi_t\right), \operatorname{Irlu}\left(\xi_t\right), \operatorname{Irlf}\left(\xi_t\right), \operatorname{Irf}\left(\xi_t\right), \operatorname{Irla}\left(\xi_t\right)$, $\operatorname{Ird} 1\left(\xi_t\right), \operatorname{Ira}\left(\xi_t\right), \operatorname{Irga}\left(\xi_t\right), \operatorname{Irb}\left(\xi_t\right) \& \operatorname{Irr}{ }_t\left(\xi_t\right)$. Comparative graphic measures of irregularity in $C N C_4(\mathrm{~m}), C N C_5(\mathrm{~m})$ and $C N C_t(\mathrm{~m})$ have also been examined and presented. We are interested in creating new formulas to gain a better understanding of irregularity measures in carbon nanocones using the indices described above.