bluuebunny/crossref_metadata_2025_split huggingface dataset:
On the Locating Rainbow Connection Number of Trees and Regular Bipartite Graphs
Authors: Bustan Ariestha W. , Salman A. N. M. , Putri Pritta E. , Awanis Zata Y. 
Published: July 2023

Locating the rainbow connection number of graphs is a new mathematical concept that combines the concepts of the rainbow vertex coloring and the partition dimension. In this research, we determine the lower and upper bounds of the locating rainbow connection number of a graph and provide the characterization of graphs with the locating rainbow connection number equal to its upper and lower bounds to restrict the upper and lower bounds of the locating rainbow connection number of a graph. We also found the locating rainbow connection number of trees and regular bipartite graphs. The method used in this study is a deductive method that begins with a literature study related to relevant previous research concepts and results, making hypotheses, conducting proofs, and drawing conclusions. This research concludes that only path graphs with orders 2, 3, 4, and complete graphs have a locating rainbow connection number equal to 2 and the order of graph G, respectively. We also showed that the locating rainbow connection number of bipartite regular graphs is in the range of r-⌊n/4⌋+2 to n/2+1, and the locating rainbow connection number of a tree is determined based on the maximum number of pendants or the maximum number of internal vertices. Doi: 10.28991/ESJ-2023-07-04-016 Full Text: PDF
A Binary Survivability Prediction Classification Model towards Understanding of Osteosarcoma Prognosis
Authors: Muthaiyah Saravanan , Singh Vivek Ajit , Zaw Thein Oak Kyaw , Anbananthen Kalaiarasi S. M. , Park Byeonghwa , Kim Myung Joon 
Published: July 2023

The objective of this study is to explore effective and innovative machine learning techniques that can assist medical professionals in developing more accurate prognoses that can enhance the survivability of osteosarcoma patients by investigating potential prognostic factors and identifying novel therapeutic approaches. A comprehensive analysis was conducted using a dataset of 128 osteosarcoma patients between 1997 to 2011. The dataset included 52 attributes in total that covered a wide range of demographics, together with information on clinical records, treatment protocols, and survival outcomes. Data was obtained from NOCERAL (National Orthopaedic Centre of Excellence in Research and Learning), Kuala Lumpur. Three distinct binary classification methods (i.e., random forest, support vector machine (SVM), and artificial neural network (ANN)) were employed to identify the prognostic factors that are associated with improved survival efficacy measures. The results of this study revealed that both SVM and ANN outperformed random forests in predicting survivability for both the 2-year and 5-year time frames. These findings indicate the potential of SVM and ANN as effective tools for predicting osteosarcoma survivability. The study signifies a significant step towards integrating machine learning techniques into the existing toolkit available to medical practitioners. This study contributes to the medical field by providing a comparative analysis of three prominent machine learning techniques for predicting osteosarcoma survivability. The superior performance of SVM and ANN over random forests highlights the potential of these methods in generating more accurate survivability predictions. Further development and refinement of these machine learning techniques hold promise for enhancing their effectiveness and instilling greater confidence among medical professionals and patients in the predictive capabilities of machine learning and artificial intelligence models for osteosarcoma survivability. Doi: 10.28991/ESJ-2023-07-04-018 Full Text: PDF
Forecasting Solar Power Generation Utilizing Machine Learning Models in Lubbock
Authors: Balal Afshin , Pakzad Jafarabadi Yaser , Demir Ayda , Igene Morris , Giesselmann Michael , Bayne Stephen 
Published: July 2023

Solar energy is a widely accessible, clean, and sustainable energy source. Solar power harvesting in order to generate electricity on smart grids is essential in light of the present global energy crisis. However, the highly variable nature of solar radiation poses unique challenges for accurately predicting solar photovoltaic (PV) power generation. Factors such as cloud cover, atmospheric conditions, and seasonal variations significantly impact the amount of solar energy available for conversion into electricity. Therefore, it is essential to precisely estimate the output of solar power in order to assess the potential of smart grids. This paper presents a study that utilizes various machine learning models to predict solar photovoltaic (PV) power generation in Lubbock, Texas. Mean Squared Error (MSE) and R² metrics are utilized to demonstrate the performance of each model. The results show that the Random Forest Regression (RFR) and Long Short-Term Memory (LSTM) models outperformed the other models, with a MSE of 2.06% and 2.23% and R² values of 0.977 and 0.975, respectively. In addition, RFR and LSTM demonstrate their capability to capture the intricate patterns and complex relationships inherent in solar power generation data. The developed machine learning models can aid solar PV investors in streamlining their processes and improving their planning for the production of solar energy. Doi: 10.28991/ESJ-2023-07-04-02 Full Text: PDF
Advanced Genetic Programming vs. State-of-the-Art AutoML in Imbalanced Binary Classification
Authors: Frank Franz , Bacao Fernando 
Published: July 2023

The objective of this article is to provide a comparative analysis of two novel genetic programming (GP) techniques, differentiable Cartesian genetic programming for artificial neural networks (DCGPANN) and geometric semantic genetic programming (GSGP), with state-of-the-art automated machine learning (AutoML) tools, namely Auto-Keras, Auto-PyTorch and Auto-Sklearn. While all these techniques are compared to several baseline algorithms upon their introduction, research still lacks direct comparisons between them, especially of the GP approaches with state-of-the-art AutoML. This study intends to fill this gap in order to analyze the true potential of GP for AutoML. The performances of the different tools are assessed by applying them to 20 benchmark datasets of the imbalanced binary classification field, thus an area that is a frequent and challenging problem. The tools are compared across the four categories average performance, maximum performance, standard deviation within performance, and generalization ability, whereby the metrics F1-score, G-mean, and AUC are used for evaluation. The analysis finds that the GP techniques, while unable to completely outperform state-of-the-art AutoML, are indeed already a very competitive alternative. Therefore, these advanced GP tools prove that they are able to provide a new and promising approach for practitioners developing machine learning (ML) models. Doi: 10.28991/ESJ-2023-07-04-021 Full Text: PDF
The Effect of Sodium Humate Feed Additives in Diets for Holstein Breed Heifers
Authors: Kairiša Daina , Valdovska Anda , Vircava Ilze , Pilvere Irina , Proskina Liga , Gāliņa Daiga , Gutmanis Guntis , Mešķis Sandijs 
Published: July 2023

The research aim is to examine the possibilities of including the sodium humate (NaHum) additive derived from freshwater sapropel in feed to identify its effects on growth performance, promote haematopoiesis, and modulate the microbiota of the intestinal tract. The research was done under production conditions, complying with Latvian and European Union legislation on the keeping, feeding, and welfare of farm animals. The research had three replications, and for each of them, two groups of Holstein breeding heifers were established: control (3xn=7) and research (3xn=7). The duration of each replication was 9 days in the adaptation period and 105 days in the research period. The heifers of the research group received the NaHum solution additive with feed from the 1st to 35th day (stage 1) at an intake rate of 0.4 mL/kg of live weight, from the 36th to 70th day (stage 2) at an intake rate of 0.5 mL/kg of live weight, and from the 71st to 105th day (stage 3) at an intake rate of 0.6 mL/kg of live weight. The breeding heifers of the research group, receiving NaHum at an intake rate of 0.6 mL/kg of live weight, achieved a significantly higher live weight gain at stage 3 and an overall numerically higher live weight gain (by 4.8 kg) than the control group during the research period. Consequently, a significantly higher relative growth ratio (0.334) was found in the research group at stage 3, which was 0.028 higher than that in the control group. The Lactobacillus spp. count in faecal samples was steady at the end of the research; a significant difference was found between groups, with the average ranging between 6.95 (control group) and 8.49 log CFU/g (research (NaHum) group). The novelty of the research is that it was scientifically proven that feeding the NaHum additive derived from freshwater lake sapropel to the breeding Holstein heifers up to 5 months of age increased their feed intake and live weight gain, as well as activity and health. Doi: 10.28991/ESJ-2023-07-04-023 Full Text: PDF
The Impact of the COVID-19 Epidemic on Gambling Behavior Intention: The Moderating Effect of Anti-Epidemic Measure
Authors: Zhou Jinquan , He Wenjin , Mieiro Susana M. B. 
Published: July 2023

This study focuses on how the COVID-19 epidemic affects gambling motivation and behavior. This research also analyzes the behavioral intervention effects of the anti-epidemic measures on the COVID-19 epidemic and the relationship between the epidemic impact and gambling motivation and behavior. To investigate these connections, this research used Structural Equation Modeling to analyze 334 valid questionnaires collected during COVID-19 from gamblers from mainland China who visited the Macao Special Administrative Region. The results showed that the epidemic impact negatively affected gambling motivation and behavior, and gambling motivation partially mediated the relationship between epidemic impact and gambling behavior. Anti-epidemic measures positively moderated the epidemic’s impact on gambling motivation and behavior. This paper offers a theoretical contribution by proving the influence of the social environment on human motivational behavior, especially the effect of the COVID-19 crisis, and the support of government and enterprise anti-epidemic measures for behavior intervention theory. The practicality of this study consists of behavioral interventions from anti-epidemic efforts by regional government and industry to cope with the epidemic. These measures should influence the gamblers’ behavior intentions by considering the health and safety strategies that may reduce the impact of the COVID-19 epidemic on mainland Chinese gamblers. Doi: 10.28991/ESJ-2023-07-04-024 Full Text: PDF
Industrial, Collaborative and Mobile Robotics in Latin America: Review of Mechatronic Technologies for Advanced Automation
Authors: Cornejo Jose , Barrera S. , Herrera Ruiz C. A. , Gutierrez F. , Casasnovas M. O. , Kot Leonardo , Solis M. A. , Larenas R. , Castro-Nieny F. , Arbulú Saavedra M. R. , Rodríguez Serrezuela R. , Muñoz Londoño Y. , Serna Alejandro , Ortega-Aranda D. , Aranda-Miramontes S. , Chang I. , Cardona M. , Carrasquilla-Batista A. , Palomares R. , Rodriguez R. , Parisuaña Ruben , Bórquez Miguel , Navarro Oscar , Sanchez Fernando , Bonev I. A. , Coulombe Jonathan , Martín Rico F. , Treviño-Elizondo B. L. , García-Reyes H. , Sollazzo A. , Dubor A. , Markopoulou A. , De Marinis C. , Chacin Marco , Mora Andres , Pérez-Ruiz M. , Ribeiro A. , L'Huillier E. A. 
Published: July 2023

Mechatronics and Robotics (MaR) have recently gained importance in product development and manufacturing settings and applications. Therefore, the Center for Space Emerging Technologies (C-SET) has managed an international multi-disciplinary study to present, historically, the first Latin American general review of industrial, collaborative, and mobile robotics, with the support of North American and European researchers and institutions. The methodology is developed by considering literature extracted from Scopus, Web of Science, and Aerospace Research Central and adding reports written by companies and government organizations. This describes the state-of-the-art of MaR until the year 2023 in the 3 Sub-Regions: North America, Central America, and South America, having achieved important results related to the academy, industry, government, and entrepreneurship; thus, the statistics shown in this manuscript are unique. Also, this article explores the potential for further work and advantages described by robotic companies such as ABB, KUKA, and Mecademic and the use of the Robot Operating System (ROS) in order to promote research, development, and innovation. In addition, the integration with industry 4.0 and digital manufacturing, architecture and construction, aerospace, smart agriculture, artificial intelligence, and computational social science (human-robot interaction) is analyzed to show the promising features of these growing tech areas, considering the improvements to increase production, manufacturing, and education in the Region. Finally, regarding the information presented, Latin America is considered an important location for investments to increase production and product development, taking into account the further proposal for the creation of the LATAM Consortium for Advanced Robotics and Mechatronics, which could support and work on roboethics and education/R+D+I law and regulations in the Region. Doi: 10.28991/ESJ-2023-07-04-025 Full Text: PDF
Desktop vs. Headset: A Comparative Study of User Experience and Engagement for Flexibility Exercise in Virtual Reality
Authors: Thamrongrat Pornpon , Khundam Chaowanan , Pakdeebun Pornpitak , Mohd Nizam Dinna Nina 
Published: July 2023

This study aimed to investigate the effectiveness of Virtual Reality (VR) technology for flexibility exercise and compare the physical outcomes, user experience, and engagement of VR desktops and VR headsets. The VR exercise application was designed using motion capture technology and exported to different VR devices. Each of the devices was used by 30 participants to perform a flexibility exercise in VR. Physical outcomes were measured using the sit-and-reach test, and user experience and engagement were evaluated using questionnaires and group discussions. The results showed that VR desktop participants had higher sit-and-reach scores. However, VR headset participants reported a more immersive experience (reality judgment) and motivation (value and usefulness). They also had higher engagement (focused attention and reward) levels than VR desktop participants. There were no significant differences between the two approaches in terms of enjoyment, effort, pressure, choice, correspondence, absorption, perceived usability, and aesthetic appeal. The study highlights the importance of considering physical outcomes, user experience, and engagement by comparing two different VR approaches for flexibility exercise. Further research is needed to explore the limitations and potential benefits of VR technology for physical activity. Doi: 10.28991/ESJ-2023-07-04-03 Full Text: PDF
Impact of Continuing Education on Employee Productivity and Financial Performance of Banks
Authors: Hajdari Muhamet , Qerimi Fidan , Qerimi Arbëresha 
Published: July 2023

Objectives: This research aims to measure the impact of continuing education on employee productivity and that of the latter on the financial performance of commercial banks in Kosovo. Methods: A quantitative approach was employed to achieve the research objectives and questions. The statistical population comprised 3636 employees working at commercial banks operating in Kosovo. We obtained data from the Central Bank of Kosovo (CBK). A sample of 360 employees was then determined using Slovin's formula to include the representative sample. Findings: The Ordinary Least-Squares (OLS) model demonstrated that continuing education affects employee productivity, and the latter affects the financial performance of commercial banks in Kosovo. The findings indicated that 40.2% of employee productivity is explained by continuing education, while 20.4% of financial performance is explained by employee productivity. Novelty/improvement:This research showed that commercial banks could receive feedback on the importance of employees’ continuing education in increasing their productivity and, subsequently, the bank's financial performance. This can improve effectiveness and productivity at work and the organization's financial results, especially cost optimization and income generation. Doi: 10.28991/ESJ-2023-07-04-09 Full Text: PDF
NILAI-NILAI PENDIDIKAN KARAKTER DALAM KUMPULAN CERITA ANAK AKU CINTA RAMADHAN SUNTINGAN DELLY RAIN FELLO
Authors: Sugiarti  , Syaiful Anam  , Lailatul Khanifah  
Published: July 2023

Nilai karakter penting dalam pendidikan. Karya sastra memiliki banyak jenis dan ragamnya. Salah satu jenisnya adalah cerita anak. Beberapa ciri cerita anak adalah sebagai berikut. Ditinjau dari segi isi, dalam cerita anak tidak diperkenankan menuangkan hal-hal negatif. Selanjutnya dari sisi penyajian, cerita anak harus menggunakan bahasa yang lugas dan sederhana. Tujuanya adalah untuk mendeskripsikan nilai-nilai pendidikan karakter yang terkandung di dalam kumpulan cerita anak Aku Cinta Ramadhan suntingan Delly Rain Fello. Metode dalam artikel ini bersifat studi pustaka, yang datanya berupa dokumen (kumpulan cerita anak) dan bukan berupa angka-angka. Berdasarkan analisis yang telah dilakukan, hasil penelitian ini menunjukkan bahwa terdapat banyak sekali nilai-nilai pendidikan karakter yang terkandung di dalam kumpulan cerita anak Aku Cinta Ramadan suntingan Delly Rain Fello. Nilai-nilai pendidikan karakter tersebut banyak dimunculkan melalui tingkahlaku para tokoh cerita. Disimpulkan bahwa kumpulan cerita anak Aku Cinta Ramadan suntingan Delly Rain Fello mengandung banyak nilai pendidikan karakter. Nilai-nilai tersebut dituangkan melalui dua teknik, langsung dan tidak langsung. Adapun nilai-nilai pendidikan karakter tersebut meliputi nilai religius, disiplin, peduli sosial, bekerja keras, tanggung jawab, toleransi, menghargai prestasi, bersahabat/ komunikatif, gemar membaca, mandiri, dan semangat kebangsaan.
Pengaruh Perilaku Kerja Inovatif dan Manajemen Pengetahuan terhadap Kinerja Organisasi pada Usaha Mikro dan Kecil
Authors: Sundara Helena Yosa , Gunawan Agus , Kornarius Yoke Pribadi , Caroline Angela 
Published: July 2023

Micro and Small Enterprises in the food and beverage industry contribute significantly to Indonesia’s economic growth. Micro and small businesses rely heavily on innovation to survive in the face of increasing competition. This study aims to determine and analyze the effect of innovative work behavior and knowledge management on the organizational performance of Micro and Small Enterprises (MSEs) in Bandung. The study sample, consisting of 34 employees, was selected from six food and beverage businesses. Data processing results show that innovative work behavior and knowledge management do not affect organizational performance at micro and small enterprises. However, it was found that employee age plays a role in innovative work behavior and knowledge management.
TRADITIONS OF NONVERBAL GREETINGS
IN INTERCULTURAL SPACE
Authors: Fetsko Ivanna 
Published: July 2023

The behaviour of each person is determined by the values and norms of the culture and society in which he exists. They determine the verbal and non-verbal means of communication that people use in a certain situation. Since there are several cultures that are different from each other, the participants of the communication can also belong to different cultures. Belonging to the interlocutors in the same culture makes communication easier, but in different cultures it makes it much more difficult. The participants of normal interpersonal communication understand all verbal and non-verbal nuances. Knowledge of the non-verbal language of another nation is an essential component of intercultural communication and the very first step to establishing successful communication between representatives of different nations and cultures. Addressing a person tactlessly for a certain culture due to ignorance of non-verbal features can make communication impossible even before it begins. The article reveals the peculiarities of non-verbal communication as a necessary component of foreign language proficiency and one of the main components of intercultural competence. The category of politeness, which occupies one of the central places in the implementation of successful communication, is considered. A detailed analysis of non-verbal greeting signs characteristic of speakers of different languages and cultures was carried out, and their role in the intercultural communication was indicated. It was found that the most common forms of greeting are a handshake, a kiss, a hug, a greeting with a look, and a smile. In everyday polite and public-official communicative situations, greetings are closely related to bows, which are inherent in Eastern peoples. Little-known greeting gestures that are characterized only for certain peoples are also described in the manuscript.
Non-verbal means of communication retain ethnic features, despite the development of international political, economic, and cultural ties, which promotes the interaction of national communication styles and forms uniform parameters of communication, including non-verbal communication. Therefore, you should use non-verbal means very carefully, even if they seem natural and understandable to everyone.
Thus, mastery of non-verbal means of communication and knowledge of their features in different cultures contributes to the development of intercultural competence of a person in the modern globalized world. Mastering a foreign verbal communication system, that is, a foreign language, should be supplemented by mastering non-verbal communication skills in order to promote more effective and conflict-free communication between representatives of different countries.
Key words: intercultural communication, language, non-verbal communication, gesture, greeting.