Mekatronik Mühendisliği Bölümü Yayın Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/255

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  • Conference Object
    Fluorescent On-Chip Imager by Using a Tunable Absorption Filter
    (Ieee, 2017) Arpali, Caglar; Yıldırım, Ender; Yildirim, Ender; Arpali, Çağlar; Arpali, Serap Altay; Arpali, Serap; Makine Mühendisliği; Mekatronik Mühendisliği; Elektronik ve Haberleşme Mühendisliği
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    High-Throughput Screening of Blood Samples Based on Structured Illumination On-Chip Imaging
    (IEEE, 2013) Arpali, Serap; Arpali, S.A.; Arpali, Çağlar; Arpali, C.; Coskun, A.F.; Chiang, H.-H.; Ozcan, A.; Mekatronik Mühendisliği; Elektronik ve Haberleşme Mühendisliği
    We demonstrate a high-throughput fluorescent on-chip imaging platform, using structured illumination that can rapidly screen large volumes of scattering media such as undiluted whole blood samples (e.g., ~ 0.3-0.7 mL) for detection of fluorescent micro-objects at low concentrations (e.g.,≤50-100 particles/mL). This imaging modality might especially be useful for rare cell applications involving whole blood samples, such as detection of circulating tumor cells. © 2013 OSA.
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    Citation - Scopus: 2
    An Optimization Model To Coordinate Scheduling and Controling in Projects: Case With Instantaneous Control Constraints
    (National Technical University of Athens, 2014) Schmıdt, Klaus Werner; Hazir, Ö.; Schmidt, K.W.; Eryilmaz, U.; Mekatronik Mühendisliği
    Today, many enterprises in different industries take part in various projects, and organizational performances depend more and more on project performances. In order to maximize performance, effective management of project functions is crucial. In this regard, we focus on scheduling and control functions and their relation. Characteristics of data sharing among them and possible integration strategies are theoretically investigated. A model base for a decision support framework that accounts for these interdependencies and supports managers is developed. To solve the formulated integrated project scheduling and control problem, a tabu search algorithm is combined with optimal control techniques. As a result, a project schedule as well as the means and timing of interventions are determined such that the project cost is minimized. The obtained results are supported by computational experiments. Integrated models and algorithms to be developed aim to fill an important theoretical gap in project management.
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    Controller Design for Cacc With Time-Varying Communication Delays
    (Ieee, 2023) Soysal, Gokhan; Schmidt, Klaus Werner; Bingol, Hilal
    Cooperative Adaptive Cruise Control (CACC) aims at the safe and comfortable travel of vehicles at short distances in the form of platoons. Hereby, it is generally desired to attenuate disturbances along vehicles in a platoon, which is captured by different string stability conditions. In this paper, we focus on L-infinity string stability. This condition ensures reducing the magnitude of the acceleration signal along the platoon, which helps to avoid actuator saturation and increases driving comfort. Since the performance of CACC is adversely affected by time-varying communication and actuator delays, we develop the first controller design method for L-infinity-string stability, combining the Lyapunov-Krasovskii method and our custom bisection algorithm. Simulation experiments demonstrate the effectiveness of our method.
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    Comprehensive Comparison of Various Machine Learning Algorithms for Rf Fingerprints Classification
    (Institute of Electrical and Electronics Engineers Inc., 2023) Ergezer, H.; Gundogan, B.
    In these days, the use of drones has become quite common. Remote controls can do the control of these drones with RF signals. It is important to prevent security vulnerabilities caused by using drones in our daily lives. A complex dataset was created by extracting the characteristics of the RF signals and preprocessing them. To solve this complex data set and problem, the application of models including Support Vector Machine (SVM), Random Forest, Decision Tree, Gradient Boosting, XGBoost and Neural Network (NN) models, including various ML models and comparison of optimization studies of these applied models are examined in this article. In addition, a wide range of studies was carried out to compare ML models, including comparison metrics such as Accuracy, Precision, Recall, Mean Squared Error (MSE), F1 Score, $R^{2}$ and Training Time. In line with these results, the highest score was obtained in the $\mathrm{R}^{2}$ comparison metric (97%) in the Neural Network (NN). Compared to the others, the results of Neural Network (NN) were more successful, but the Training Time (245 sec) in the Neural Network (NN) method is by far more than the other ML methods, which shows us that the NN method requires a very high computing process. As a result of the comparison, another outstanding Ensemble-based ML method is Decision Tree. This is because besides the very low Training Time $(5\sec)$, it has managed to be the 2nd ML algorithm with the highest $\mathrm{R}^{2}$ score (96%). Apart from these, among other ML methods, SVM performed slightly less well $(\mathrm{R}^{2}$ 91%) in solving this complex problem. The advanced Gradient Method (95%) and XGBoost (96%), which also have the Ensemble structure, showed a head-to-head performance regarding $\mathrm{R}^{2}$ scores. However, XGBoost (30 sec) has a very short Training Time compared to Gradient Boosting (180 sec). As a result, the approach of each ML method to solving the complex problem differed from each other, and the success rates and Training Time also differed equally. The most important work to be done here is to choose which ML method you want to achieve according to the limited system in hand and the performance-accuracy dilemma. © 2023 IEEE.
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    Investigation of Electrical Discharge Drilling (EDD) Performance of Ti-6Al4V Super Alloy
    (2018) Erdem, Oğuz; Çoğun, Can; Uslan, İbrahim
    Ti-6Al-4V super alloy (Ti64) is widely used in many engineering applications such as automotive, aviation and aerospace owing to its low density and high strength properties. Because of its high toughness and high melting temperature, Ti64 is regarded as a difficult-to-machine material in conventional machining. Furthermore, it is also difficult to machine in Electrical Discharge Drilling (EDD) due to its high electrical resistance and low thermal conductivity. The EDD performance is quantified by material removal rate (MRR), electrode wear rate (EWR), relative wear (RW), surface roughness (SR) and surface characteristic of drilled workpiece. The main goal of this study is to experimentally investigate the performance outputs (MRR, EWR, RW and SR) of Ti64 super alloy in EDD operation.
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    Image-Based Remote Control Using FPGA
    (2014) Bingöl, Hilal; Kısa Işık, Gizay; Başayar, Tuğba; Genç, Fatih; Yengel, Emre
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    Elektrolitik ve alaşım bakır elektrotların elektro-erozyon ile işleme performansına etkisi
    (2014) Çoğun, Can; Şimşek, Ülke
    Elektro erozyon ile işlemenin (EEİ) en önemli maliyet unsuru elektrotun üretilmesidir. EEİ’de en yaygın kullanılan elektrot malzemeleri bakır ve alaşımlarıdır. Maliyeti arttırmadan EEİ yapmanın yolu, hammadde maliyeti düşük, işlemesi kolay ve elektriksel aşınma direnci yüksek bakır alaşımlarını tespit etmektir. Bu çalışmada, EEİ’de elektrot olarak kullanılan elektrolitik bakır, CuCr1Zr ve CuCo2Be bakır alaşımları için işleme hızı, elektrot aşınma hızı, bağıl aşınma ve işparçası yüzey pürüzlülüğü gibi performans çıktıları deneysel olarak incelenmiştir. Ayrıca, CuCr1Zr alaşımına uygulanan yaşlandırma işlemi sonrası artan elektriksel iletkenliğin EEİ performans çıktılarına etkileri incelenmiştir. Performans çıktılarının alaşım türünden ve uygulanan yaşlandırma işleminden etkilendiği görülmüştür.
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    Electro discharge machining performance of chromium copper powder metal electrodes
    (2014) Gülcan, Orhan; Uslan, İbrahim; Usta, Yusuf; Çoğun, Can
    In electro discharge machining used frequently in tool production, copper and graphite is commonly used as electrode material. The reason of this is high melting temperatures and excellent electrical and thermal conductivity of these materials. But, the low wear resistance of these materials makes it necessary to investigate different materials that have more wear resistance. Up to now, apart from copper, materials like brass, chromium, tungsten, steel, titanium have been used in electrode production. Apart from different materials, different production techniques have been investigated to increase production time. Powder metallurgy is one of these techniques. Electrode production with powder metallurgy becomes more advantageous than other production techniques due to the possibility of different powder combinations and controlling of thermal, electrical, mechanical and micro structure properties of produced electrodes with pressing pressure and sintering temperature. In the present study, chromium-copper composite electrodes produced with powder metallurgy will be used for electro discharge machining of SAE 1040 steel and material removal rate, electrode wear rate and surface roughness values will be compared with values from machining with electrolytic copper.