bluuebunny/crossref_metadata_2025 huggingface dataset:
Cambio climático: Efectos sobre la salinidad en los estuarios de Florida y respuestas de las ostras, las praderas marinas y otras formas de vida animal y vegetal
Authors: Smyth Ashley , Laughinghouse Haywood Dail , Reynolds Laura , Camp Edward , Havens Karl
Published: February 2025

Los estuarios económicamente importantes de Florida podrían verse fuertemente afectados por el aumento del nivel del mar y la alteración del flujo de los ríos, ambos causados por el cambio climático. La resultante mayor salinidad o salinidad del agua podría perjudicar plantas y animales, alterar el hábitat de peces y aves y reducir la capacidad de los estuarios para proporcionar servicios tan importantes como la producción de mariscos y la protección de las costas contra la erosión. Esta publicación contiene información para las partes interesadas, estudiantes, científicos y agencias ambientales interesadas en comprender cómo los cambios en la salinidad impactan los estuarios de Florida con estudios de casos específicos.
Evaluasi penggunaan obat antibiotika pada pasien anak penderita penyakit pneumonia
Authors: Ramdani Robby , Kartidjo Pudjiastuti , P Suherman Linda , Septiani Vina , Islamiyah Alfi Nurul , Rahmi Adinda
Published: February 2025

Pneumonia merupakan infeksi atau peradangan akut di jaringan paru yang disebabkan berbagai mikroorganisme, pneumonia menjadi kematian utama pada balita di seluruh dunia. Antibiotika merupakan terapi utama untuk penyakit pneumonia. Penggunaan antibiotika yang tepat ialah penggunaan antibiotika yang efektif dengan meminimalkan kemungkinan terjadinya resistensi, peningkatan efek terapeutik, serta dapat meminimalkan biaya obat. Penggunaan antibiotika dikatakan rasional apabila memenuhi beberapa kriteria diantaranya yaitu tepat indikasi, tepat pemilihan obat, tepat dosis, tepat rute pemberian dan tepat interval waktu. Pemberian penggunaan antibiotik yang tidak tepat dapat menyebabkan peningkatan efek samping dan toksisitas antibiotik, pemborosan biaya dan tidak tercapainya tujuan terapi. Tujuan penelitian ini adalah untuk mengevaluasi penggunaan obat antibiotika pada pasien anak penderita penyakit pneumonia. Penelitian ini dilakukan secara retrospektif dengan mengumpulkan data sekunder berupa rekam medis pasien pneumonia anak, dengan total sampel 54 yang telah memenuhi kriteria inklusi. Hasil penelitian menunjukkan bahwa laki-laki merupakan jenis kelamin terbanyak yang menderita pneumonia, sedangkan kelompok usia dengan jumlah penderita paling banyak adalah balita. Antibiotik tunggal yang paling banyak digunakan oleh pasien adalah seftriakson sebanyak 10 pasien (18,52%) sedangkan untuk antibiotik kombinasi adalah injeksi ampisilin dan gentamisin sebanyak 13 pasien (24,07%) Ketepatan penggunaan antibiotik dengan parameter 5T untuk kasus pneumonia anak di instalasi rawat inap Rumah Sakit Dustira diperoleh hasil ketepatan indikasi 100%, ketepatan pemilihan obat (100%), ketepatan dosis (100%), ketepatan rute pemberian (100%), dan ketepatan interval waktu pemberian (100%)
Study of the Mechanics of the Movement of Loose Lumpy Material in the Acceleration Section of the Pneumo-transport Pipeline of the Vibration-pneumotransport Machine of Cyclic action
Authors:   Central Ukrainian National Technical University, Yatsun Volodymyr , Skrynnik Ivan ,   Central Ukrainian National Technical University, Horpynchenko Olha ,   Central Ukrainian National Technical University
Published: February 2025

The purpose of this work is to analyze the processes taking place in the acceleration section of the pneumo-transport pipeline of the vibration-pneumatic machine of cyclic action, control the movement of the aeromixture by changing the parameters of the air flow on the moving material, and identify the optimal technical solutions regarding the conditions of transportation of loose lumpy materials with different physical mechanical properties.
The brought results over of researches of influence of size of parts of mountain breed that is transported, on the parameters of pneumatic portage. The got dependences are for determination of speed of pneumatic portage and charges of the compressed air from the size of parts of material that is transported, taking into account the parameters of the pneumatic portage system.
The combination of the above dependencies allows you to establish the trajectory and time of movement of a piece of loose material in the "detachment from the surface - weighing in the air flow - fall" mode. The obtained data indicate that in the working range of parameters, the length of the particle flight section, depending on the physical and mechanical properties of the material, and in particular on the recovery coefficient when the particle hits the pipeline surface, varies from 0.5 m to 12 m.
The research data will allow to improve the structural scheme of the vibration-pneumatic machine of cyclic action in order to improve technical and economic indicators and work efficiency.
Algorithm for Optimizing the Reliability of Operation and Efficiency of Use of Production Equipment Using Artificial Intelligence Methods
Authors:   Central Ukrainian National Technical University, Aulin Victor , Kovalov Serhiy ,   Central Ukrainian National Technical University, Hrynkiv Andriy ,   Central Ukrainian National Technical University, Varvarov Valeriy ,   Kharkiv National Ivan Kozhedub Air Force University, Kharkiv, Ukraine
Published: February 2025

This paper presents an innovative approach that involves the optimization of maintenance for production equipment by leveraging advanced artificial intelligence (AI) algorithms. The study explores the application of Markov process theory within the context of reinforcement learning and its integration into the modeling of production environments. The focus of this research is to address critical issues related to enhancing the reliability and efficiency of production processes. This is achieved by reducing maintenance costs and minimizing equipment downtime.
The proposed model for optimizing the use of the production equipment system is described as an environment with discrete states, where an agent operates with the capability to perform specific actions. This model emphasizes the implementation of the Q-learning algorithm, a form of reinforcement learning that aims to optimize production processes by enabling the agent to learn and make decisions that enhance system performance. Through the iterative process of Q-learning, the agent evaluates the potential benefits of various actions in different states, gradually refining its strategy to maximize long-term rewards.
Q-learning, with its ability to handle environments with unknown dynamics, is particularly effective in this context. It helps the agent to develop an optimal maintenance policy by balancing immediate maintenance costs against the long-term benefits of reduced downtime and extended equipment lifespan. The iterative nature of Q-learning ensures continuous improvement and adaptation, making the system robust against varying operational conditions and unforeseen disruptions.
Through rigorous analysis and experimentation, the findings demonstrate a significant improvement in the reliability and productivity of the production equipment system. The introduction of AI technologies, specifically through the Q-learning framework, not only streamlines maintenance practices but also ensures a more efficient utilization of resources, ultimately leading to a more robust and cost-effective production environment. The results of this study highlight the potential of AI in transforming traditional production maintenance strategies and setting new standards for operational excellence.
Justification of Diagnostic Parameters for a Comprehensive UAV-based Remote Diagnostic System for Overhead Power Lines
Authors:   Central Ukrainian National Technical University, Kozlovskyi Oleksandr , Rendzinyak Serhiy ,   Ivan Franko National University of Lviv
Published: February 2025

The article presents the results of substantiating diagnostic parameters for a multiparametric remote monitoring system of overhead power lines based on the use of an unmanned aerial vehicle (UAV).
Significant wear of the structural elements of overhead power lines (OHL) in the IPS of Ukraine, exacerbated by the impact of climate change, leads to an increase in the number of damages. This makes proper maintenance of OHL a priority task. Existing technical diagnostic systems based UAVs are mainly aimed at solving narrow specialized tasks. Therefore, there is a need to develop more universal and comprehensive systems. The analysis of operational defects in the structural elements of OHL has shown that most of these defects manifest as visible mechanical damages, while others remain hidden. Detection of such defects is possible through remote non-destructive testing methods. Based on typical defects, a list of diagnostic parameters for a 110 kV overhead line was formulated. Considering that OHL elements have the same probability of failure, only those defects that may pose a threat to its operability in the near future were considered. Based on the selected defects and diagnostic parameters, a table of possible states of the OHL was compiled. The selection of the necessary and sufficient group of diagnostic parameters was carried out based on their average informativeness, which characterizes the degree of entropy reduction of the overhead line.
The main key aspects of the study are:
- existing technical diagnostic systems for overhead power lines based on UAVs are mainly focused on solving specialized tasks for specific power grid areas and are not universal. This limits their adaptation to different operating conditions and indicates the need for more comprehensive systems capable of addressing a wide range of power grid issues;
- the majority of defects in the structural elements of overhead power lines appear as various cracks, chips, fractures, breaks, loss of fastening elements, and corrosion, while the remaining defects are hidden, such as weakened wire connections and zero insulators. All these defects can be detected using remote non-destructive testing methods;
- given the accepted limitations, the most informative group for diagnosing the state of an overhead power line consists of seven parameters, including visual signatures of defects, temperatures of conductors and contact connections, as well as discharge activity of insulators and conductive parts.
Application of Waterproofing Coatings for Corrosion Protection of Road Culverts Made of Corrugated Metal Structures
Authors:   National Transport University, Harkusha Mykola
Published: February 2025

Road culverts made of corrugated metal structures were initially used as small pipes in both length and diameter. Today, road culverts made of corrugated metal structures are used with a span of 40 m and are a composite soil-steel system and are widely used in the field of transport construction. Road culverts made of corrugated metal structures are economical, aesthetically attractive, have the advantage of quick construction with minimal maintenance in the future, the estimated service life is usually from 50 to 100 years.
Constantly operating in wet conditions, road culverts made of corrugated metal structures are subject to corrosion and abrasion due to environmental influences. Corrosion occurs in several places, for example, on the surface in contact with the soil, on the inside of the pipe where flowing water is present, or on the surface exposed to air. This is due to aggressive substances in the air, water or soil backfill material, such as salts, metals or other aggressive chemicals. Corrosion is the main cause of the destruction of metal structures. The rate of degradation of materials depends on environmental conditions. The expected service time of road culverts is determined by the durability of the material and the durability of the structure. The durability of the material refers to the ability of the pipe to resist wear due to the natural processes of corrosion, abrasion and erosion. When designing road culverts made of corrugated metal structures, it is important to understand the environmental conditions throughout its service time in order to assess the suitability of the material. To ensure compliance with the design service time requirements, the steel structure is protected with an anti-corrosion coating.
The paper considers various protective coatings to increase the durability of road culverts from corrosion.
Studying and influence of professional motivation of students when studying graphic disciplines
Authors:   Yanka Kupala State University of Grodno, Tarantey Victor , Tuleuova Gulmarzhan ,   S.Seifullin Kazakh Agro Technical Research University, Karipbayev Zhassulan ,   E.A. Buketov Karaganda University
Published: February 2025

This article explores the issues of quality management in teaching graphic disciplines in higher technical education. Special attention is given to the need for continuous monitoring of students' academic performance, incorporating various assessment methods such as written assignments, oral examinations, computer-based testing, and independent project defense. Analyzing the correlation between these assessment methods allows for a more objective evaluation of students' knowledge levels and helps identify weaknesses in the educational process, contributing to its optimization and increased efficiency. As part of the study, a survey was conducted among students majoring in "Architecture" and "Design" to examine their professional motivation and interest in the subject "Engineering Graphics." The results showed that many students do not fully recognize the importance of engineering graphics in their future careers, which negatively affects their motivation to study the subject. At the same time, the findings revealed that incorporating modern educational technologies and practice-oriented teaching methods contributes to a deeper understanding of the material. The article also discusses possible ways to enhance the teaching of engineering graphics, including the integration of digital technologies, increasing the number of practical lessons, and implementing an individualized approach to learning.
Backgrounds for creating unified criteria for systemically important banks at the EAEU level: clustering approach
Authors:   Narxoz University, Dalke A. , Ruziyeva E. ,   Almaty Technological University, Nurgaliyeva A. ,   Narxoz University
Published: February 2025

The problems of identifying systemically important banks have not lost their relevance for more than 10 years, and the issues of developing uniform criteria for them in economic unions are of particular interest. The formation of clusters of SIBs (systemically important banks) within the EAEU will improve the quality of financial services provided by the banks in the participating countries, and will also strengthen the innovative potential of the economic union. The purpose of the study is to examine, through the application of clustering methodology (Euclidean distance metrics and Hamming models), the backgrounds and fundamental possibilities for developing uniform criteria for identifying SIBs for Kazakhstan, Belarus and Russia, as participating countries of the Eurasian Economic Union. At the same time, methodological recommendations for national systemically important banks developed by the Basel Committee on Banking Supervision are taken into account. The results of the study showed that the grouping of banks classified in individual EAEU countries as SIBs is logical when three clusters are identified: Level 1 (integration), Level 2 (country), and Level 3 (potential). The analysis emphasizes that when developing unified criteria, it is
necessary to develop indicators that are not approximated with each other. In addition, the criteria must be clearly and strictly defined, and similar features (indicators) must be significantly different. The present study is comprised of two sections; this paper is part of the second section.
The role of social entrepreneurship in the innovative development of the state: the cluster approach
Authors:   University "Turan-Astana", Tusupbaeva B. , Iskakov В. ,   University "Turan-Astana", Tuzubekova M. ,   University "Turan-Astana"
Published: February 2025

The article discusses the importance and role of social entrepreneurship in the innovative development of the state. The authors described social entrepreneurship as an effective business model aimed at solving social problems of society and analyzed its impact on the development of an innovative ecosystem. The main goal of the scientific work is to determine the development of methods and mechanisms for the development of social entrepreneurship using a cluster approach. This approach aims to strengthen partnerships between social enterprises, government agencies, research institutes and the private sector. The article highlights the role of clusters based on social entrepreneurship in increasing innovative potential at the regional and national levels.

The authors have the task of determining their effectiveness by comparing international and domestic practices of a cluster approach focused on social entrepreneurship using theoretical, comparative and system analysis methods. Describes the main directions of state policy to support social entrepreneurship, including the tools necessary to realize the potential of the cluster approach. The results of the study suggest effective ways to integrate social entrepreneurship in ensuring innovative development strategies and socio-economic stability.
Prospects for the global oil market in the scenarios of the Russian Energy Agency
Authors: Drebentsov V. V. , Ivanov N. A. , Semikashev V. V.
Published: February 2025

The article describes the development of the world oil market, presented by the Russian Energy Agency of the Ministry of Energy of Russia within the framework of working out longterm scenarios for the future of world energy until 2050. The analysis focuses on oil extraction and peak oil consumption in various macroregions. A comparison is made with scenario forecasts of the International Energy Agency, the US Energy Information Administration, OPEC, McKinsey, BloombergNEF and bp Energy Outlook. Recommendations are given for the development of the Russian oil industry within the framework of the Rational Technological Choice scenario.
Forgotten classics: J. A. Schumpeter’s theory of imperialism
Authors: Kapeliushnikov R. I.
Published: February 2025

The paper analyses the littleknown essay of one of the classics of economic thought, J. A. Schumpeter (1883—1950), “The sociology of imperialisms,” where he appears not as an economic theorist, but as an economic sociologist. Schumpeter was interested in the problem of imperialism almost throughout his scientific career. His theory was polemically directed against various Marxist interpretations, in which imperialism was viewed as a product of late (“monopolistic”) capitalism and which he subjected to sharp criticism. Schumpeter defined imperialism as objectless disposition on the part of a state to unlimited forcible expansion, finding examples of it throughout history from Ancient Egypt to the present day. Unlike Marxist authors, he saw capitalism not as a source, but, on thecontrary, as an antipode of imperialism. His key idea was that imperialism was an atavism that is rooted in social structures and psychological attitudes inherited by the modern world from the precapitalist era. According to his forecast, in the course of the further capitalistic development, these relics of the past will be eliminated and imperialism will disappear along with them. Many ideas expressed by Schumpeter in his essay are still of considerable interest.
Optimizing Data Flow in Multi-Cloud Environments: A Technical Deep Dive
Authors: Srujan Reddy Anugu
Published: February 2025

The widespread adoption of multi-cloud strategies has fundamentally transformed enterprise computing architectures, introducing opportunities and challenges in modern IT environments. This article examines data flow optimization between multiple cloud providers, focusing on performance constraints, integration complexities, and security requirements. The article investigates advanced optimization techniques, including direct cloud interconnection, data fabric implementation, intelligent replication strategies, and edge computing integration. Through this article, enterprise deployments across various sectors, the article demonstrates that properly implemented multi-cloud optimization strategies significantly enhance operational resilience, reduce costs, and improve system performance. The article highlights the importance of standardized APIs, comprehensive monitoring frameworks, and emerging AI-driven optimization approaches in achieving efficient multi-cloud operations. This article provides valuable insights for organizations seeking to optimize their multi-cloud environments while maintaining security and compliance requirements.
Enhancing ResNet with Ghost Weight Normalization For Improved Retina Disease Classification
Authors: Baihaqi Galih Restu , Shalsadilla Shafatyra Reditha , Argaputri Maulida Khairunisa
Published: February 2025

Retinal disease is a dangerous disease. If left untreated, it can cause blurred vision and even cause permanent blindness. Recently, deep learning approaches are widely used to classify medical diseases. A widely used model to classify medical diseases is ResNet. To train the ResNet model, the data used is data obtained from Kaggle with the name Retinal OCT Images (Optical Coherence Tomography) consisting of 4 classes namely choroidal neovascularization (CNV), DRUSEN, diabetic macular edema (DME), and Normal with a total of 83,600 data. The ResNet base model showed accuracy and f1-score of 92%. Modifying the ResNet Base model with the addition of Ghost Weight Normalization (GWN) which aims to provide more weight normalization opportunities shows an increase in accuracy and f1-score to 94%. GWN can also increase the accuracy of CNN Base from 77% to 81%. This improvement shows that GWN can improve the accuracy of Deep learning models with its weight normalization variation technique. Although the training load and training time when using GWN can increase, the accuracy and f1-score of the ResNet model with GWN of 94% can make the chance of misclassification of retinal diseases smaller.
Optimized Scheme for the Combination of Shared Energy Storage Business Models
Authors: Liu Bulong , Lu Junjie
Published: February 2025

The Stackelberg game model between shared energy storage stations and renewable energy generators optimizes pricing strategies to maximize both parties' profits. The energy storage station, acting as the leader, sets pricing strategies for capacity leasing, peak-valley arbitrage, and frequency regulation services, while the renewable energy generator, as the follower, selects the optimal service package based on the station's pricing schemes. This paper employs a Genetic Algorithm (GA) to optimize the energy storage station’s profits and applies NSGA-II to assist the generators in finding the optimal package combination, thereby improving overall profitability. The study demonstrates that this approach effectively facilitates optimal collaboration under complex market conditions and in the experimental validation, the interactions between the energy storage station and the generators were simulated under different market scenarios. The results show that the proposed game model significantly improves station profitability and optimizes generator strategies. The model’s potential applications and future optimization possibilities are discussed, providing theoretical support for the practical operation of shared energy storage business models.
The Future of Enterprise Systems Integrating Metaverse, Web 3.0, and Extended Reality
Authors: Setiawan Randi , Sulistiani Heni
Published: February 2025

The convergence of emerging technologies such as the metaverse, Web 3.0, and extended reality (XR) is poised to reshape the landscape of enterprise systems, offering unprecedented opportunities for innovation and user experience. This paper explores the transformative potential of these technologies within the context of enterprise systems, focusing on their implications for user interaction, data management, business processes, and collaboration. We delve into the unique features of each technology and how they can be integrated into existing enterprise systems to enhance user engagement, streamline workflows, and foster new business models. Furthermore, we analyze the challenges and ethical considerations associated with implementing these cutting-edge technologies, highlighting the need for responsible development and ethical guidelines. Ultimately, this paper aims to shed light on the exciting future of enterprise systems as they embrace the transformative power of the metaverse, Web 3.0, and XR, paving the way for a more immersive, interconnected, and innovative business landscape.
Intelligent Visual Inspection System of Ship Draft Based on UAV
Authors: Lai ChuangXin , Lu JunJie
Published: February 2025

Accurately calculating the weight of cargo after shipping is an important issue in ocean transportation. Existing methods mainly indirectly calculate the weight of cargo by obtaining the draft of the ship. To estimate the draft of ships passing through waterways and ports, it is necessary to collect sounding line data. However, the current methods for collecting sounding line data mainly rely on manual measurement, which is inefficient, inaccurate, and has safety hazards. To address these issues, this paper combines artificial intelligence and deep learning technologies to design an unmanned aerial vehicle-based intelligent detection system for ship drafts. Detailed research is conducted on image acquisition, image segmentation, image recognition algorithms, etc., and an intelligent measurement platform for ship drafts is developed.
Utilization of YouTube as a Learning Media Algorithms of Programming for Students Informatics Engineering UNIPMA
Authors: Nita Sekreningsih , Wicaksono Dayu Agung
Published: February 2025

YouTube as an information sharing site is an application that is provided free of charge and is easy to access and use in various activities, on of which is for creating learning media. Learning with YouTube can improve skills and strengthen learning in the form of videos, making it easier to study and develop discussion material for Professional Educators.  The purpose of using learning media via YouTube is to help Informatics students understand teaching material more easily and can motivate them to learn. The method in this research uses descriptive qualitative and collects primary and secondary data, namely students who take the 1st semester Algorithms of Programming course, class 1A, 1B, 1C totaling + 50 people and other internet users who watch videos on YouTube and library journals that are relevant to the research topic . The process and steps for making YouTube as a learning media include, 1) Making storyboards for material concepts 2) Making ppt files as discussion material 3) Making learning videos 4) Editing videos 3) Uploading videos to YouTube. The final result was +250 views, comments and likes. Whereas, learning videos can be viewed via the YouTube channel at the link https : // www.youtube.com / watch?v = bRsSFCc8kV0.    The conclusion of this research is that using YouTube as a learning media makes learning more interesting, effective and very useful in the learning process and increases student motivation in learning more optimally because it can be played back to understand the material more deeply
Visual Identity of Tlogo Land Tourism to Enhance Brand Awareness
Authors: Fernanda Rico Alan , Wardani Lely Surya
Published: February 2025

Tlogo Land is a tourist destination in Malang Regency that faces issues with visual identity inconsistency, including the use of different logos across various social media platforms. This study aims to design a consistent and integrated visual identity to enhance brand awareness and attract tourists. The research employs a non-participatory approach, with data collected through direct observation of Tlogo Land and interviews with the management. The process of designing the visual identity follows the Design Thinking method, consisting of five stages: Empathize, Define, Ideate, Prototype, and Test. The results show that the designed visual identity, including the logo, colors, and other graphic elements, effectively reflects the character and values of Tlogo Land as a nature-based tourist destination. The implementation of the visual identity on media such as business cards, staff uniforms, and stamps proves to be effective in increasing recognition and creating a positive image of Tlogo Land among visitors. This study concludes that developing a consistent visual identity can be an effective strategy for brand awareness of tourist destinations, while also strengthening Tlogo Land's image as a professional and attractive tourist destination
The Quantum-Assisted Fingerprint Biometrics: a Novel Approach To Fast And Accurate Feature Extraction And Synthetic Generation
Authors: Sospeter Birir Kipchirchir , Odoyo Wilfred , Akinyi Laura
Published: February 2025

This research explores the integration of artificial intelligence (AI) and quantum computing to enhance fingerprint biometrics through improved feature extraction and synthetic fingerprint generation. Traditional fingerprint biometrics face challenges related to processing speed and scalability, particularly when managing large datasets or creating synthetic fingerprints for testing and training purposes. We propose a dual approach: using convolutional neural networks (CNNs) to extract distinctive fingerprint features—such as loops, whorls, and minutiae points—and employing generative adversarial networks (GANs) for the synthesis of high-quality fingerprint images that preserve realistic patterns and variations. To address computational limitations in processing these data-intensive tasks, we explore the use of quantum computing algorithms. Specifically, we implement a hybrid quantum-classical model, using quantum support vector machines (QSVM) for feature classification and quantum-enhanced GANs (QGAN) to speed up synthetic fingerprint generation. Preliminary results indicate that quantum-assisted models demonstrate promising efficiency gains in both feature extraction and image synthesis, potentially enabling faster processing and improved scalability compared to classical models alone.This study contributes to biometric security by providing a framework for faster, more accurate fingerprint biometrics using cutting-edge AI and quantum methodologies. The findings hold potential applications in security systems, law enforcement, and digital identity management, where real-time analysis and synthetic data generation can strengthen verification and identification processes. Future work includes optimizing quantum components for larger datasets and further refining AI models to improve the realism of generated fingerprint images.
Enterprise Architecture Planning Information System at Bus Rental Service Company
Authors: STT Latjuba Sofyana , Yunitasari Yessi , Budi Belca Setya
Published: February 2025

In increasing customer satisfaction, convenience and improving the quality of the company. The company engaged in bus rental services is PT. Transaba wants to have a digital platform and an integrated management system in the Company. One way is to do enterprise architecture planning to find out what systems/applications are urgent to create. The EAP framework provides the direction desired by the Company with its stages, including planning initiation, business modeling, current systems and technologies, data architecture and application architecture, and technology architecture. In this planning, the Company's directions and guidance regarding what must be done first to achieve the objectives, namely Procurement and installation of infrastructure, Customer Management System, Reservation management system, Scheduling and route system and Human Resources Training
Application of FFT and KNN Methods for the Process of Identifying Sound Signals
Authors: Yunitasari Yessi , Saifulloh Saifulloh , Harly Daniswara Andhika Putra
Published: February 2025

Everyone has a different kind of voice. Sound is a unique thing and has a certain range of frequencies and intensity of sound that can and cannot be heard by humans. we can detect important characteristics of the sound. The Fast Fourier Transform (FFT) algorithm is an algorithm for calculating Discrete Fourier Transform (DFT). Process of Identifying Sound Signals beginning with the sound data was preprocessed, feature extraction using FFT, classification using KNN and finding the nearest distance using the Euclidean distance method, an accuracy result of  79% of the tested data was obtained.
The Effectiveness of Watching Movies Using English Subtitles in Teaching Vocabulary
Authors: Firmansyah Imam , Irnanda Septhia , Yoestara Marisa
Published: February 2025

This study assesses the effectiveness of using movies with English subtitles for teaching vocabulary. Experimental research refers to a method in which one explores variables for their causing effect through manipulation and observes the impact on another variable. The present study was conducted experimentally with SMPN 1 Peukan Bada grade VIII students. The study's sample consists of 57 students divided into two classes: one, VIII 5, as an experimental class in which the movies were shown with subtitles in English, and the other, VIII 7, as a control class where the movie was presented without subtitles. Data has been collected in the form of pre-and post-tests to measure the improvement in vocabulary acquisition by students. The average of pre-tests was 58 for the experimental and 56 for the control classes. It was observed that the experimental class had a steep increase in their vocabulary score as compared to the control class. The mean post-test score of the experimental class was 90 while the average of the control class climbed up to 76. Data were analyzed using both independent t-tests and paired t-tests to determine the significance of differences between the two groups by SPSS. The results of the statistical analysis indicated that there was indeed a significant difference between the two classes, with the p-value less than <0.001. Therefore, it would be proper to conclude that the use of English subtitles while watching movies effectively enhances vocabulary acquisition for students.
Challenges in Supply Chain Management for MSMEs in Maintaining Financial Stability in the Digital Era
Authors: Ramadhani Ananda , Nelly Nelly , Nengsih Rita , Ardana Galang , Yonatada Ardifal
Published: February 2025

Micro, Small, and Medium Enterprises (MSMEs) play a strategic role as a cornerstone of the economy in various countries, including Indonesia. However, the era of globalization and digitalization presents complex challenges in supply chain management that threaten the financial stability of MSMEs. Some of the key issues faced include dependency on single suppliers, limited access to digital technology, minimal transparency within the supply chain, and rapidly changing global market dynamics. These obstacles often lead to uncertainty in inventory management, increased operational costs, and reduced production efficiency. This article not only identifies these challenges but also provides an in-depth analysis of their impact on the sustainability of MSMEs. Using a solution-based approach, the article offers practical strategies such as supplier diversification to mitigate dependency risks, digital technology integration to enhance supply chain efficiency, and collaboration within supply chain ecosystems to create stronger synergies. Furthermore, the article discusses the role of governments and business communities in supporting digital infrastructure development and providing training for MSMEs to adapt to technological changes.To illustrate the implementation of these strategies, the article includes flowcharts, graphs, and real-world case analyses as practical guides for MSMEs. With this approach, MSMEs are expected to maintain financial stability, improve competitiveness, and achieve sustainable growth amidst the challenges of globalization and digital transformation.
IT Infrastructure Security Optimization Strategies for Today's Organizations
Authors: Antoni Kevin Rizki , Sulistiani Heni , Antoni Kevin Rizki , Nunyai Reiza Fahlevi
Published: February 2025

Information technology (IT) infrastructure security is one of the top priorities for organizations in the digital age. The rapid adoption of technologies such as cloud computing, the Internet of Things (IoT), and artificial intelligence has presented great opportunities for innovation, but also increased the risk of cyberattacks, data theft, and system vulnerabilities. This research aims to identify and develop IT infrastructure security optimization strategies that can enhance the protection of an organization's digital assets. The approach used includes risk analysis, implementation of a comprehensive security framework, and adoption of advanced defense technologies such as encryption, next-generation firewalls, and artificial intelligence-based threat detection systems. The results show that an integrated, adaptive strategy supported by solid policies can improve system resilience while supporting operational flexibility. Thus, this research provides practical recommendations for organizations to build an IT infrastructure that is secure, resilient, and ready to face future challenges.
Progress in the Application of Artificial Intelligence in Mental Health Education for College Students in Universities
Authors: Shuai Peng , Liu Yue
Published: February 2025

The purpose of this paper is to explore how artificial intelligence technology can help mental health education in colleges and universities, analyse the progress of its application in personalised education, mental health monitoring and evaluation, ecological transient intervention, etc., and analyse its current situation, strengths, challenges, and future development direction.
Empowering Sustainable Startups in Kenya Through Blockchain Technology
Authors: Hamba Loyce Aoko , Kangethe Brian Muchiri , Odoyo Wilfred Onyango
Published: February 2025

This study investigates the potential applications of blockchain technology to offer a solid basis for supporting long-term, sustainable Kenyan entrepreneurs. The study investigates how blockchain technology's decentralized, transparent, and secure features might increase investor confidence, increase stakeholder engagement, and speed up funding processes for sustainable projects. The key findings indicate that blockchain can significantly improve transparency, reduce inefficiencies in the fundraising process, and attract a diverse range of investors to support companies. However, barriers including ambiguous laws, complex technology, and poor awareness make widespread adoption challenging. To solve problems, the paper emphasizes the need for an all-encompassing framework that includes capacity building, policy alignment, and clever public-private partnerships. By prioritizing these initiatives, stakeholders may unlock blockchain's transformative potential to assist Kenya's green development goals, foster innovation, and accelerate sustainable startup growth.
Risk Analysis of Computer Network Security Focusing on Phishing Attacks in Fintech Platform
Authors: Sangha Zahra Kharisma , Sulistiani Heni
Published: February 2025

The advancement of Science and Technology, particularly in Information Technology such as the internet, has significantly facilitated individuals in achieving their life goals quickly, either through legal or illegal means. One prominent threat is phishing, which employs social engineering techniques to deceive users by impersonating authoritative entities. Phishing targets various industries, with the fintech platform sector being one of the primary targets. The main factors contributing to phishing in fintech platform services include users' lack of knowledge, psychological factors, and insufficient privacy protection on social networks. Therefore, computer network security is a critical measure to prevent phishing attacks on fintech platform services. This research employs a qualitative method with a descriptive approach.
Artificial Intelligence Capability in Education to Enhance Human Resources Quality from Economic Perspective
Authors: Agit Alamsyah , Muharram Susilawati , Oktavianty Oktavianty
Published: February 2025

Application of artificial intelligence (AI) in education contributes significantly to improving the quality of human resources (HR). This study aims to analyze the relationship between AI technology and HR quality from an economic perspective. Using a qualitative approach based on literature studies, this study explores the contribution of AI in supporting interactive learning, operational efficiency, and improving critical skills. The results show that AI accelerates the learning process, personalizes learning experiences, and prepares students to face the challenges of the digital job market. At the company level, AI implementation improves productivity, efficiency, and data-driven decision-making. This study recommends the development of a curriculum that supports technological literacy and collaboration between educational institutions, the government, and the private sector to ensure HR readiness to face the demands of the digital era. Practical implications include sustainable training strategies and AI integration to support adaptive digital transformation. This study emphasizes the importance of investing in education and training to optimize technological potential, improve business performance, and support sustainable economic growth
Heritage in Augmented Reality
Authors: Ramadhan Seno Surya , Ganendra Firzatullah Danevan , Brilian Ramdlan Siraj Rio , Yahya Saiful
Published: February 2025

This research explores the application of augmented reality (AR) technology to promote the historical heritage of colonial architecture in East Java, with a focus on Malang. By creating immersive 3D visualizations of iconic buildings, the project aims to document and preserve cultural heritage, raise public awareness, and support sustainable urban planning. The project aligns with Sustainable Development Goals (SDGs) 4 and 11, fostering quality education and sustainable cities.
ТРЕНДИ ВИКОРИСТАННЯ ЛЮДСЬКИХ РЕСУРСІВ ЗА УМОВ ЦИФРОВОЇ ЕКОНОМІКИ
Authors: Прохоровська С. А. , Ілляш І. Д.
Published: February 2025

Актуальність дослідження зумовлена трансформаційними процесами глобального та національного характеру, поширенням цифрових технологій, впровадженням автоматизації процесів та робіт, а відтак, відтоком попиту на людські ресурси тих спеціальностей, робота яких може бути алгоритмізована, зміною тенденцій у використанні ресурсів праці. У статті узагальнено та виокремлено новітні тренди у використанні робочої сили у цифрову добу. Вивчено поступ України у процесі цифровізації економіки, зміни тенденцій та форм зайнятості, які стають характерними за умов діджиталізації. Висвітлено особливості гібридних форм кар’єри, паралельної зайнятості завдяки використанню онлайн-платформ, розвиток гнучких режимів праці, пріоритетність добробуту співробітників, різноманітність робочих місць, безперервне навчання, впровадження HR-аналітики, штучного інтелекту, автоматизації рутинних завдань за допомогою систем автоматизованого управління людськими ресурсами та автоматизованих платформ навчання співробітників. Проаналізовано нові напрямки в управлінні та використанні людських ресурсів, зокрема екологічний підхід, орієнтація на досягнення life-work balance, завдяки гнучким системам організації праці. Обґрунтовано, що інклюзивність робочих місць стає глобальним трендом. Вивчено доцільність у використанні систем управління талантами, забезпечення їх потреби у безперервному навчанні на основі нових форм і підходів. Аргументовано доцільність аналітичного підходу (використання інструментів HR-аналітики та Big Data) в управлінні людськими ресурсами за умов цифрової економіки. Визначено, що попри наявну низку переваг, новітні тенденції у сфері використання людських ресурсів створюють і загрози, такі як слабка соціальна захищеність працівників, непостійність отримання доходу, складність у формуванні організаційної культури та залученості, важливість пошуку новітніх форм управління кар’єрою та лояльністю працівників, що своєю чергою вимагає докорінного перегляду принципів роботи з людськими ресурсами організацій.
ІМЕРСИВНЕ ЗБЕРЕЖЕННЯ: ВИКОРИСТАННЯ ВІРТУАЛЬНОЇ РЕАЛЬНОСТІ ДЛЯ ЗАХИСТУ КУЛЬТУРНОЇ СПАДЩИНИ
Authors: Снігур Володимир
Published: February 2025

Віртуальна реальність є доволі мало використовуваною технологією, коли йдеться про збереження культурної спадщини. Це пов’язано з тим, що використання віртуальної реальності як інструменту важче виправдати порівняно з традиційними методами архівування, поширеність яких, однак, є надзвичайно корисною у випадках, коли йдеться про створення цифрового архіву. Імерсивний формат може слугувати ще одним способом, за допомогою якого ми можемо захистити і зберегти нашу спільну культуру чи історію у багатьох її проявах, починаючи від одягу, архітектури, творів декоративного та образотворчого мистецтва і до ландшафтів. Це надзвичайно корисно, оскільки дає нам можливість популяризувати свої культурні досягнення і розповісти про них світові у спосіб, який є другим найкращим після безпосереднього відвідування музеїв і галерей. Це також вимагає абсолютно нових методів дослідження, категоризації та презентації, але це справедливо для будь-яких нових технологій, а крім того, опосередковано приносить користь і суміжним галузям знань. Наприклад, для демонстрації архітектурних комплексів їх необхідно відсканувати, змоделювати в цифровому форматі та надати їм відповідну текстуру, що надасть нам не лише 3D-модель для VR-середовища, але й модель, придатну для неінвазивних досліджень. У випадку, якщо будівля перестане існувати, ми матимемо достатньо даних, щоб відновити її до оригінального стану, якщо буде вирішено, що це є оптимальним варіантом дій. За допомогою віртуальної реальності можна повернути до життя саму історію через відтворення реальних подій у їхньому оточенні, що може бути використано для зацікавлення людей у минулому їхньої країни та опосередкованого збереження його для наступних поколінь у майже такий самий спосіб, як це робилося раніше. Оскільки сам процес потребує подальшого дослідження і, як очікується, буде максимально адаптованим до кожного конкретного випадку, ми залишимо його обговорення поза увагою цієї статті. Натомість ми розглянемо сучасні, здебільшого вільнодоступні, проекти, які успішно виконали це завдання і можуть бути використані як приклади для майбутньої роботи в цьому напрямку.