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New Trends in Contemporary Economics, Business and Management. 15th International Scientific Conference “Business and Management 2025”
No full textBiblioteka informuoja, 2025 Nr. 45 (742)
No full textNaujai į Web of Science ir Scopus įtrauktų Vilnius Gedimino technikos darbuotojų publikacijų sąrašai ir kitos bibliotekos aktualijos.45 (742)202
Optimized Fruit Detection in Complex Environments Using YOLOv11n for Smart Agricultural Applications
No full textThis study explores the application of the YOLOv11 object detection algorithm for precise and efficient fruit detection in complex image environments. The research focuses on leveraging YOLOv11’s advanced single-stage detection architecture and Transfer Learning to enable real-time fruit identification while maintaining high detection accuracy, particularly for edge computing scenarios where computational efficiency is essential. To evaluate the effectiveness of the proposed system, the model was trained on a specialized fruit dataset consisting of images taken from real-world agricultural settings. The dataset comprises eleven distinct fruit classes captured under diverse conditions, including varying lighting, occlusions, and different angles. Experimental results revealed that the model achieved a mean average precision (mAP) of 90%, demonstrating its ability to localize and classify fruits with a high degree of reliability. The findings of this study have significant implications for the agricultural sector, particularly in automation-driven applications such as fruit harvesting, post-harvest processing, quality assessment, and inventory management. By integrating YOLOv11-based detection systems in the process, farms and agribusinesses can improve efficiency, reduce labor costs, and enhance productivity.Taip / Ye
Biblioteka informuoja, 2025 Nr. 36 (733)
No full textNaujai į Web of Science ir Scopus įtrauktų Vilnius Gedimino technikos darbuotojų publikacijų sąrašai ir kitos bibliotekos aktualijos.36 (733)202
Experimental Analysis of the Effect of Frequency on Power Transformer Size, Cost, and Losses
No full textThis paper investigates the differences between 50 Hz and 60 Hz power transformers, focusing on key design aspects such as cost, size, and losses. Four different power ratings (1250 kVA, 1600 kVA, 2000 kVA, and 2500 kVA) are compared under the assumption that the leakage impedance and magnetic flux density remain constant for both transformer types. The study explores how frequency impacts transformer size, cost, and efficiency. It is found that transformers operating at 60 Hz generally exhibit smaller transformer sizes and reduced copper losses compared to their 50 Hz counterparts, resulting in differences in physical dimensions and material costs. Core losses tend to be higher in 60 Hz transformers. The paper concludes by offering insights into how frequency affects the selection of transformers based on size, cost considerations, and efficiency, providing guidance for optimal transformer choice in different power applications.TUBİTAKTaip / Yes118C10
Acceptance of and attitude towards “Slow Fashion”. an explorative study based on an evaluation among different generations in Germany
No full textThe market for slow and sustainable fashion is growing; especially in Europe it is a very promising topic.
Nevertheless, the actual purchase decision for “Slow Fashion” can be influenced by various factors and as a result on
the acceptance of and attitude towards “Slow Fashion”. In many cases, a positive attitude towards sustainability is not
reflected in the actual purchase. This explorative study tries to shed light on differences in acceptance and attitudes
among different generations’ consumers. Findings of a survey in Germany are presented, which confirm the existence
of differences in motivations and drivers related to purchase decisions. To increase market shares of “Slow Fashion” it
is important to better understand these underlying motives of behaviour.Taip / Ye
Research and testing of the noise-absorbing efficiency of different cardboard samples
No full textTyrime analizuojamas kartono atliekų mėginių efektyvumas garso sugerčiai, siekiant įvertinti jų potencialą
kaip alternatyvių, pakartotiniai panaudojamų garsą sugeriančių medžiagų. Buvo tiriamos įvairaus tankio ir storio
plokštės, pagamintos iš perdirbtų kartono atliekų. Rezultatai parodė, kad perdirbtas kartonas turi reikšmingą garso
sugerties potencialą – prototipų efektyvumas siekia iki 0,41. Tyrimas taip pat išryškino kartono, kaip tvarios ir lengvai
perdirbamos medžiagos, svarbą, siūlant jo taikymą pigesnėms akustinėms plokštėms gaminti. Šie sprendimai galėtų
būti ypač naudingi socialiai jautrioms grupėms ir aplinkai draugiškoms statybų inovacijoms. Nustatyta, kad garso
sugerties koeficientas vidutinių dažnių diapazone (2000 Hz iki 3150 Hz) siekė iki 0,28, o aukštų dažnių diapazone
(3150–5000 Hz) – iki 0,41. Šio tyrimo tikslas – nustatyti kartono ir klijų kompozitinės medžiagos garso sugerties savybes
ir pasiūlyti alternatyvias, lengvai pagaminamas garsą sugeriančias plokštes.The study analyses the sound absorption efficiency
of cardboard waste samples in order to clarify their potential
as alternative reusable sound-absorbing materials. The
studies examined panels of various densities and thicknesses
made from recycled cardboard waste. The results showed
that recycled cardboard has sound absorption potential, and
the efficiency of prototypes reaches up to 0.41. The study
also emphasises the importance of cardboard as a sustainable
and easily recyclable material, suggesting its application
for the production of cheaper acoustic panels. These solutions
could be useful for socially sensitive groups and environmentally
oriented construction innovations. It was found
that the sound absorption coefficient in the medium frequencies
(2000 Hz to 3150 Hz) reached up to 0.28, and in the high
frequencies (3150–5000 Hz) – up to 0.41. This study aims to
determine the sound absorption properties of cardboard and
adhesive composite material and to propose alternative, easily
manufactured sound-absorbing panels.Taip / Ye
Development of Management Information System using Geospatial Modeling Analysis and Predictive Algorithms (Geo-MAPA): A Smart-Monitored Alert and Response Technology for Forest Fire Readiness and Early-warning System (SMARTFIRES) For Leyte Sab-a Basin Peatland
No full textThis research presents the development and implementation of MIS-GeoMAPA, a comprehensive Management Information System utilizing geospatial modeling and predictive algorithms for forest fire readiness and early warning in Leyte's Sab-a Basin Peatland (LSBP). Employing an iterative-waterfall development approach, we integrated real-time environmental sensor data, including temperature, humidity, wind speed, and soil moisture, with advanced geospatial analysis. Predictive models, particularly linear and logistic regression, were developed to forecast fire risks, achieving high accuracy validated through statistical tests like the Wilcoxon signed-rank test. The system’s performance, reflected in a Mean Squared Error (MSE) of 0.25 and an 88% accuracy rate, underscores its potential in enhancing fire preparedness and response. This study highlights the critical role of environmental monitoring and predictive analytics in mitigating forest fire impacts, offering a scalable solution for environmental management and disaster readiness.Taip / Ye
iBon: A Web Application for Aerial Fauna Identification and Counting Using Machine Learning
No full textAbstract:
With the alarming decline in aerial fauna populations worldwide, the need for timely and accurate tools to monitor species trends and support conservation strategies has become critical. This paper aims to develop and evaluate iBon, a web-based application that provides automated bird identification and counting using advanced machine learning models. Traditional methods like manual observation are time-consuming, prone to observer bias, and inconsistent across datasets. iBon addresses these challenges by employing a Convolutional Neural Network (CNN) for bird identification, achieving 94% accuracy across 17 datasets, with performance boosted through a pre-trained MobileNet feature extractor. The system integrates YOLOv8, a fast and accurate object detection model for bird counting. Both models are assessed using accuracy, F1-score, and robustness to dataset variations. iBon delivers a reliable and user-friendly platform that empowers researchers, conservationists, and citizen scientists with efficient tools for biodiversity monitoring and data-driven decision-making.Taip / Ye