Mühendislik Fakültesi

Permanent URI for this communityhttps://hdl.handle.net/20.500.12573/30

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Ball Lens Based Mobile Microscope
(Gazi Univ, 2016) Icoz, Kutay; 0000-0002-0947-6166; AGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümü; Icoz, Kutay; 01. Abdullah Gül University
In this paper we report a low cost, simple and mobile microscope based on attachment of a ball lens to a cell phone. The system's noise and parameters affecting the image quality is investigated. The ball lens provides approximately 100X magnification and together with the cell phone's integrated lens and image sensor, 3,4-micron resolution is reached. The field-of-view of the system is 1500x1500 mu m where the price of the ball lens and the holder is less than 10 cents. By using this system as an optical light microscope, we are able to acquire images of micro particles and micro sensors. When combined with image processing methods, this optical system is capable of doing complex analysis as an alternative to commercial optical light microscopes.
Design and Development of Functional Organic Small Molecules and Polymers for Optoelectronics
(Amer Chemical Soc, 2016) Usta, Hakan; Demirel, Gokhan; Facchetti, Antonio; Muccini, Michele; 0000-0002-0618-1979; AGÜ, Mühendislik Fakültesi, Malzeme Bilimi ve Nanoteknoloji Mühendisliği Bölümü; Usta, Hakan; 01. Abdullah Gül University; 02.07. Malzeme Bilimi ve Nanoteknoloji Mühendisliği; 02. Mühendislik Fakültesi
Effect of Ambient Temperature on the Flexural Behavior of 3D Printed Composite Beams
(Soc. for the Advancement of Material and Process Engineering Janie@sampe.org, 2018) Yildirim, Afsin Talha; Eroglu, Fatih; Yesilyurt, Ogulcan; Albayrak, Kubilay; Sas, Hatice Sinem; Çiftçi, Cihan; 0000-0001-9199-6437; AGÜ, Mühendislik Fakültesi, İnşaat Mühendisliği Bölümü; Yıldırım, Afşin Talha; Eroglu, Fatih; Yesilyurt, Ogulcan; Albayrak, Kubilay; Ciftci, Cihan; 01. Abdullah Gül University; 02.03. İnşaat Mühendisliği; 02. Mühendislik Fakültesi
Adaptation of the additive manufacturing technology with 3D printers may lead to a new track in the manufacturing of composite materials. This additive manufacturing technology aims to mitigate manufacturing challenges and related design limitations of traditional composite manufacturing methods. The implementation of 3D printing of composite materials has the potential of decreasing the material cost by developing scientific methodologies to understand and optimize this printing process. This study focuses on understanding the flexural behavior of 3D printed composite beam elements and providing material data of both matrix and reinforcement components of composite materials. In this study, the flexural performance at different thermal conditions is experimentally investigated. This investigation involves the effect of the matrix material with and without short-fiber reinforcements for a specified fiber placement in the beam and fiber filaments placement in compression and tension sides of the composite beam elements along with the ambient temperature change. © 2018 Elsevier B.V., All rights reserved.
Citation - Scopus: 5
Emotion Detection Using Multivariate Synchrosqueezing Transform via 2D Circumplex Model
(Institute of Electrical and Electronics Engineers Inc., 2018) Ozel, Pinar; Akan, Aydin; Yilmaz, Bulent; Özel, Pınar; Akan, Aydin I.; Yilmaz, Bulent; AGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümü; 01. Abdullah Gül University
Emotion detection by utilizing signal processing methods is a challenging area. An open issue in emotional modeling is to obtain an optimum feature set to use for the classification process. This study proposes an approach for emotional state classification by the investigation of EEG signals via multivariate synchrosqueezing transform (MSST). MSST is a post-processing technique to compose a localized time-frequency representation yielding multivariate syncyrosqueezing coefficients. After obtaining these coefficients from EEG signals for 18 subjects from DEAP dataset, coefficients and self-assessment-mannequins (SAM) labels of those subjects are used for emotional state classification by using support vector machines (SVM) nearest neighbor, decision tree, and ensemble methods. The accuracy rate is 70.6% for high valence high arousal (HVHA), 75.4% for low valence high arousal (LVHA), 77.8% for high valence low arousal (HVLA), and 77.2% for low valence low arousal (LVLA) cases using SVM. © 2019 Elsevier B.V., All rights reserved.
Citation - Scopus: 1
Man-Hour Prediction for Complex Industrial Products
(Institute of Electrical and Electronics Engineers Inc., 2023) Unal, Ahmet Emin; Boyar, Halit; Kuleli Pak, Burcu Kuleli; Cem Yildiz, Mehmet; Erten, Ali Erman; Güngör, Vehbi Çağrı; 0000-0003-0803-8372; AGÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü; Gungor, Vehbi Cagri; 01. Abdullah Gül University
Accurately predicting the cost is crucial for the success of complex industrial projects. There can be several sources contributing to the cost. Traditional methods for cost estimation may not provide the required accuracy and speed to ensure the success of the project. Recently, machine learning techniques have shown promising results in improving cost estimation in various industrial products. This study investigates the performance of gradient-boosting machine learning models and feature engineering techniques on a private dataset of metal sheet project man-hour costs. A comparison of distinct models is conducted, key aspects influencing cost are identified, and the implications of incorporating domain-specific knowledge, including its advantages and disadvantages, are assessed based on performance outcomes. Experimental results demonstrate that LightGBM and XGBoost outperform other models, and feature selection and synthetic data generation techniques improve the performance. Overall, this study highlights the potential of machine learning in metal sheet sampling projects and emphasizes the importance of feature engineering and domain expertise for better model performance. © 2024 Elsevier B.V., All rights reserved.
Novel Method Based on Photothermal Cleavage of Thermolabile Molecules on Au Nanoparticles for Controlled Release
(Amer Chemical Soc, 2016) Goren, Ekrem; Cavusoglu, Halit; Yavuz, Emine; Usta, Hakan; Citir, Murat; Yavuz, Mustafa Selman; AGÜ, Mühendislik Fakültesi, Malzeme Bilimi ve Nanoteknoloji Mühendisliği Bölümü; Usta, Hakan; Citir, Murat; 01. Abdullah Gül University; 02.07. Malzeme Bilimi ve Nanoteknoloji Mühendisliği; 02. Mühendislik Fakültesi
Rehabilitation of Water and Environment of The TKI - GELI/YLI Opencast Mine Lakes
(Chamber of Mining Engineers of Turkey maden@maden.org.tr, 2013) Delibalta, Mahmut Suat; Uzal, Niǧmet; https://orcid.org/0000-0002-0912-3459; AGÜ, Mühendislik Fakültesi, İnşaat Mühendisliği Bölümü; Uzal, Niğmet; 01. Abdullah Gül University; 02.03. İnşaat Mühendisliği; 02. Mühendislik Fakültesi
During the search, production and enrichment process of mining operations the air, soil, water resources and living organisms are affected adversely. In coal opencast production, with the rise of surface water and ground water level large or small ponds are composed. The most important environmental problems of these ponds are low pH (acidic characteristic) and high metal concentrations (Fe, Mn, Al, Cu, Pb, Zn etc.) of these ponds, besides the sulfide minerals containing (S04) and the waste materials. These ponds needed to be rehabilitated for is one the sustainability of natural resources. In this study, the average pH values 6.22-7.79, turbidity (NTU) 0.63-6.71, sulphate content 840-1720 mg/L, KOI 2.27-61.5mg/L and electrical conductivity 1.72 -2.71 mS/cm have been measured during the monitoring study of three different lignite opencast mine post-production lakes of the TKI -GELI and YLI. The results were evaluated within the framework of relevant laws and regulations. Analyses were performed in three-month periods. © 2014 Elsevier B.V., All rights reserved.
Citation - WoS: 10
Self-Healing Performance of Biogranule Containing Microbial Self-Healing Concrete Under Intermittent Wet/Dry Cycles
(Gazi Univ, 2021) Ersan, Yusuf Cagatay; 0000-0003-4128-0195; AGÜ, Mühendislik Fakültesi, İnşaat Mühendisliği Bölümü; Ersan, Yusuf Cagatay; 01. Abdullah Gül University
Development of self-sensing and self-healing concrete is essential to minimize the labour-intensive monitoring and repair activities conducted for the maintenance of concrete structures. A type of self-healing concrete can be achieved by using microbial agents that induce calcium carbonate precipitation inside a concrete crack. Recently, biogranules consist of nitrate reducing microorganisms were presented as a new generation microbial healing agent and biogranule containing specimens revealed decent healing performance under completely submerged conditions. However, their performance under intermittent wetting conditions, a common case for various concrete structures, remains unknown. This study presents the self-healing performance of biogranule containing biomortar specimens under intermittent wet/dry conditions. In-house produced biogranules were incorporated into mortar specimens at a dose of 1.45% w/w cement (1.00% of bacteria w/w cement) and self-healing performance of cracked specimens were investigated under alternating wet/dry conditions for a crack width range of 50 to 600 um. Upon alternating wet/dry treatment for 4 weeks, cracks up to a 400 um crack width were effectively healed in biomortar specimens. Their water tightness regain was 44% better than control specimens due to their enhanced healing performance. Overall, non-axenic biogranules appear to be useful in development of self-healing bioconcrete for applications under spraying or intermittent wetting conditions.
Citation - Scopus: 2
Street Vendor Detection: Helping Municipalities Make Decisions With Actionable Insights
(IEEE, 2021) Agba, Hatice Nur; Tahir, Abdullah; AGÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü; Agba, H.N.; Tahir, A.; 01. Abdullah Gül University
Street vendors are quite common in countries across the world. By the prevalence of mobile surveillance systems, increasing demand for automatic detection of street vendors for further decisions and planning by the city administrators emerged. In this paper, an object detector is developed using a MobileNet SSD object detection algorithm to detect vendors on the street. For this study images were used, however, in the future this technique could be used for real time video footage from street cameras. Since this is the first study tackling this issue, a data set was created from scratch. The accuracy achieved by the algorithm is promising considering the size of the data set and the minimal computational power available. The goal of this research is to pave the way for more work to be done in this area and help municipalities improve their decision making process regarding street vendor activities in countries like Mexico, Pakistan, China, Turkey, etc.
Sustainable Water Management and Rehabilitation in the Mining Lakes, Ilgin-Konya, Turkey
(Agro Arge Danismanlik San ve Tic As, 2016) Delibalta, M. S.; Uzal, N.; Lermi, A.; AGÜ, Mühendislik Fakültesi, İnşaat Mühendisliği Bölümü; Uzal, Natalia E.; 01. Abdullah Gül University; 02.03. İnşaat Mühendisliği; 02. Mühendislik Fakültesi
The processes during the search, production and enrichment of mining operations naturally affects the air, soil, water resources in turn the natural environment and living organisms. In general, the environmental impact of coal opencast mining operations is much more significant than that of underground mining and mineral processing. After stripping of the material filling the holes in coal opencast production, with the rise of surface water and ground water level is composed of large or small ponds. Low pH (acidic characteristic) and high metal concentrations (Al, Ca, Mn, Fe, Cu, Zn, Pb) of these ponds, containing sulfide minerals and the waste materials, for the sustainability of natural resources is one of the biggest environmental problems. This paper is to investigate geochemical characteristics of the pond waters in the Ilgm Coal deposit area. Geochemical analyses were made by ICP-MS in waters taken from ponds in each three-month periods. Highest heavy metal contents 1839 ppb Mn and 9777 ppb Fe, the average pH values 6.49-7.81, turbidity (NTU) 0.1263.6, sulphate content 0.05-2.67 mg SO4/L, chemical oxygen demand 4-136 mg O-2/L, and electrical conductivity 285 mu S/cm4.68 mS/cm have been measured during the monitoring study of five different lignite opencast mine post-production lakes of the TKI GLI Ilgm. Analyses were performed in three-month periods. The results were evaluated within the framework of relevant laws and regulations.

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