Atılım Academic Archive (Atılım University)
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Enhancing Classification Modeling Through Feature Selection and Smoothness: a Conic-Fused Lasso Approach Integrated With Mean Shift Outlier Modelling
No full textOutlier detection and variable selection are among main objectives of statistical analysis. In our study, we address the outlier problem for classification by using the Mean Shift Outlier Model (CLMSOM). Since the MSOM has more coefficients than the linear regression model, the complexity of the model MSOM is high. Therefore, we consider feature selection for MSOM by using fused Lasso (FLasso), which is beneficial and helpful in the cases where the number of explanatory variables or features is greater than the sample size. FLasso is penalizing both the coefficients and their successive differences by the L-1-norm, and it allows sparsity for both of them, while Lasso only allows the coefficients by considering a nonsmooth optimization problem. In this study, we take into account Iterated Ridge approximation which enables us to use a smooth optimization for FLasso problem. Generated smooth optimization problem is solved by using one of continuous optimization techniques called Conic Quadratic Programming (CQP), which is enabling the utilization of interior point methods. The newly developed method is called Conic FLasso for classification by MSOM (C-FLasso-CLMSOM) and is applied to real world data set to show its performance.Emerging Sources Citation Inde
Gerçek Zamanlı Polip Tespiti: YOLOv5 ve YOLOv6'nın Hız ve Performans Analizi
No full textKolorektal kanser, kolonoskopi sırasında gözden kaçan poliplerin bilgisayar destekli teşhis sistemi ile tespit edilmesiyle potansiyel olarak önlenebilir. Bu nedenle, endoskopi uzmanlarına yardımcı olmak amacıyla, polipleri gerçek zamanlı olarak tespit eden bir teşhis algoritması geliştirildi. Polip tespiti için you look only once v5 (yolov5) ve you look only once v6 (yolov6) modelleri kullanıldı. Açık kaynaklı verilere ek olarak, nesne tespiti modellerini eğitmek için yeni bir özel veri seti de kullanıldı. Sonuçlara göre, yolov5x ve yolov6l sırasıyla 0.896 ve 0.913 mean average precision 50 (mAP50) oranlarına ulaştı. Yolov5x ve yolov6l karşılaştırıldığında, yolov5x'in hassasiyet açısından daha iyi olduğu, yolov6l'nin ise duyarlılık açısından daha iyi olduğu sonucuna varıldı. Modeller diğer çalışmalardaki sonuçlarla karşılaştırıldığında, yolov5x 0.876 f1-skoru oranıyla diğer çalışmalardan daha iyi performans sergilerken, yolov6l 0.893 duyarlılık oranıyla diğer çalışmaları geride bıraktı
The Evaluation of P-Wave Parameters in Patients With Percutaneous Closure of Atrial Septal Defect
No full textBackground: Atrial septal defect (ASD) can lead to volume overload and related changes in P-wave parameters in surface electrocardiograms of these patients. In this study, we aimed to evaluate the effect of volume overload on P-wave parameters in patients with ASD. Materials and methods: This study is a retrospective cohort analysis. A total of 142 patients with secundum ASD who underwent percutaneous closure were evaluated. P-wave duration (Pmax) and P-wave dispersion (PWD) were measured on the surface ECG before and 1 h after the closure procedure. We evaluated P-wave parameters in terms of defect size, duration of the volume overload, and closure device sizes. Results: Pmax and PWD were significantly decreased after the procedure compared with the values before the procedure (p = 20 mm) both before and after the procedure. Pmax values were significantly higher in patients older than 30 years of age (119.6 +/- 19.5 vs. 102.7 +/- 17.1 ms, respectively; p = 0.039). A significantly positive correlation was found between pre- and post-procedural Pmax and defect sizes (r = 0.474, p = 0.019 and r = 0.4233, p = 0.04, respectively). However, no positive correlation between PWD and defect age and size was present. Conclusion: Percutaneous closure of ASD is associated with an immediate decrease in both Pd and Pmax that seems to be related to the acute volume overload cessation in cardiac chambers.Science Citation Index Expande
Modeling, Dynamic Characterization, and Performance Analysis of a 2.2 kW BLDC Motor Under Fixed Load Torque Levels and Variable Speed Inputs: An Experimental Study
No full textAccurate modeling and performance analysis of brushless DC (BLDC) motors are essential for high-efficiency control in modern drive systems. In this article, a BLDC motor was modeled using system identification techniques. In addition, experimental data were collected from the BLDC motor, including its speed response to various input signals. Using system identification tools, particularly those provided by MATLAB/Simulink R2024b, an approximation model of the BLDC motor was constructed to represent the motor's dynamic behavior. The identified model was experimentally validated using various input signals, demonstrating its accuracy and generalizability under different operating conditions. Additionally, a series of mechanical load tests was conducted using the AVL eddy-current dynamometer to evaluate performance under practical operating conditions. Fixed load torques were applied across a range of motor speeds, and multiple torque levels were tested to assess the motor's dynamic response. Electrical power, mechanical power, and efficiency of the entire system were computed for each case to assess overall system performance. Moreover, the real-time state of charge (SOC) of Lithium-ion (Li-ion) battery was estimated using the Coulomb counting method to analyze the impact of Li-ion battery energy level on the BLDC motor efficiency. The study offers valuable insights into the motor's dynamic and energetic behavior, forming a foundation for robust control design and real-time application development
Recognition and Misclassification Patterns of Basic Emotional Facial Expressions: An Eye-Tracking Study in Young Healthy Adults
No full textEffects of Tailored Nutritional Counseling in Patients With Idiopathic Pulmonary Fibrosis: a Clinical Trial
No full textScience Citation Index Expande
Biosorption of Reactive Dyes by Novel Bacterium Leclercia Adecarboxylata: Complete Removal of Reactive Black 5 and Molecular Insights Into the Adsorption Mechanism
Full text linkKocberber Kilic, Nur/0000-0003-2668-3789Leclercia adecarboxylata isolated from the D & uuml;den Waterfall (Turkey) was utilized as a biosorbent for the removal of Reactive Black 5 (RB5), Setazol Blue BRF-X (BRF-X), Setazol Navy Blue SBG (SNB), and Setazol Turquoise Blue G (STBG). Of the dyes, RB5 was removed with the highest efficiency, 97.4% after 60 min. The effect of parameters such as pH (3-9), initial biosorbent dose (0.1-2.0 g/L), and initial dye concentration (25-1200 mg/L) on the biosorption of RB5 was investigated. Increasing the biosorbent dosage from 0.1 to 2.0 g/L enhanced the RB5 removal from 55.3% to 100% within 10 min. The complete removal (100%) of RB5 was achieved in media with 2.0 g/L biosorbent and 25 mg/L RB5 at pH 3 after 10 min. Additionally, the soluble extracellular polymeric substances (EPS) of L. adecarboxylata were found to consist of proteins, lipids, nucleic acids, and polysaccharides according to Fourier transform infrared spectroscopy (FTIR) analysis. The EPS was found to play a crucial role in dye removal, forming chemical interactions with dye molecules. Zeta potential analysis was used to evaluate the charge distribution on the biosorbent surface (-12.6 +/- 1.1 mV) and its interactions in the biosorption process. Kinetic and isotherm models suggested a complex interaction mechanism between the biomass and the dye. Adsorption isotherm data were analyzed via nine isotherm models. Among them, the Hill model was found to be the best fit for describing the equilibrium adsorption process of the RB5 (R2 = 0.9993). Overall, the applied models elucidated the influence of both physical and chemical interactions on the mechanism. Kinetic studies revealed that the adsorption of RB5 fit a pseudo-second-order kinetic model. The unique biochemical composition of the indigenous L. adecarboxylata biosorbent provided a high affinity for RB5, offering a sustainable, rapid, and economical solution for the treatment of dye-polluted water.Turkiye Bilimsel ve Teknolojik Arastirma Kurumu [1919B012317853]; Ankara UniversityThis study was supported by the Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (1919B012317853) and the Ankara University.Science Citation Index Expande
Recognition and Misclassification Patterns of Basic Emotional Facial Expressions: An Eye-Tracking Study in Young Healthy Adults
No full textAccurate recognition of basic facial emotions is well documented, yet the mechanisms of misclassification and their relation to gaze allocation remain under-reported. The present study utilized a within-subjects eye-tracking design to examine both accurate and inaccurate recognition of five basic emotions (anger, disgust, fear, happiness, and sadness) in healthy young adults. Fifty participants (twenty-four women) completed a forced-choice categorization task with 10 stimuli (female/male poser x emotion). A remote eye tracker (60 Hz) recorded fixations mapped to eyes, nose, and mouth areas of interest (AOIs). The analyses combined accuracy and decision-time statistics with heatmap comparisons of misclassified versus accurate trials within the same image. Overall accuracy was 87.8% (439/500). Misclassification patterns depended on the target emotion, but not on participant gender. Fear male was most often misclassified (typically as disgust), and sadness female was frequently labeled as fear or disgust; disgust was the most incorrectly attributed response. For accurate trials, decision time showed main effects of emotion (p < 0.001) and participant gender (p = 0.033): happiness was categorized fastest and anger slowest, and women responded faster overall, with particularly fast response times for sadness. The AOI results revealed strong main effects and an AOI x emotion interaction (p < 0.001): eyes received the most fixations, but fear drew relatively more mouth sampling and sadness more nose sampling. Crucially, heatmaps showed an upper-face bias (eye AOI) in inaccurate trials, whereas accurate trials retained eye sampling and added nose and mouth AOI coverage, which aligned with diagnostic cues. These findings indicate that the scanpath strategy, in addition to information availability, underpins success and failure in basic-emotion recognition, with implications for theory, targeted training, and affective technologies
Elektrikli Otomobil ve Otonom Otomobil Satın Alma Niyetlerini Etkileyen Faktörlerin İncelenmesi: Bir Alan Çalışması
No full textArtan rekabet ortamında otomobil şirketleri yeni teknolojiler geliştirerek günümüz ve geleceğin otomobillerini tasarlamak ve üretmek için yoğun çaba sarf etmektedir. Özellikle sürüş konforu ve araç içi deneyimi geliştirmeye yönelik çabaların yanı sıra, enerji tasarrufu ve çevre koruma hedefleri doğrultusunda otomobil üreticilerine rekabet avantajı sağlayan iki teknoloji öne çıkmaktadır: elektrikli araçlar ve otonom araçlar. Elektrikli araçlar tamamen yeni bir teknoloji olmamakla birlikte, günümüzde çevresel kaygıların artması bu araçların daha iyi performans, fiyat ve ulaşılabilirlik ile yeniden popülerlik kazanmasına yol açmıştır. Bu çalışmada, yeni sayılabilecek bu iki araç türü için tüketicilerin satın alma niyetleri ve bu niyetleri etkileyebilecek faktörler belirlenmeye çalışılmıştır. Araştırma, Ankara ilinde yaşayan 18 yaş ve üzeri 384 kişi üzerinde çevrimiçi anket uygulanarak gerçekleştirilmiştir. Çalışma sonucunda katılımcıların %85,7'sinin halihazırda otomobile sahip olduğu, ancak sadece %1'inin elektrikli araca sahip olduğu, %51'inin elektrikli araçlar hakkında, %34,3'ünün ise otonom araçlar hakkında orta ve iyi düzeyde bilgi sahibi olduğu tespit edilmiştir. Araç tercihinde en fazla önem verdikleri konuların başında aracın güvenliği gelirken, bunu aracın fiyatı ve yakıt tüketimi izlemektedir. Katılımcıların büyük çoğunluğu gelecekte elektrikli araç satın almayı düşündüğünü ifade etmiştir. Elektrikli araçlarda en dezavantajlı konu olarak menzillerinin sınırlı olması, otonom araçlarda ise aracın olumsuz hava koşullarından etkilenme endişesi belirtilmiştir
Ann-Based Maximum Power Tracking for a Grid-Synchronized Wind Turbine-Driven Doubly Fed Induction Generator Fed by Matrix Converter
No full textThe integration of renewable energy sources, such as wind power, into the electrical grid is essential for the development of sustainable energy systems. Doubly fed induction generators (DFIGs) have been significantly utilized in wind energy conversion systems (WECSs) because of their efficient power generation and variable speed operation. However, optimizing wind power extraction at variable wind speeds remains a major challenge. To address this, an artificial neural network (ANN) is adopted to predict the optimal shaft speed, ensuring maximum power point tracking (MPPT) for a wind energy-driven DFIG connected to a matrix converter (MC). The DFIG is controlled via field-oriented control (FOC), which allows independent power output regulation and separately controls the stator active and reactive power components. Through its compact design, bidirectional power flow, and enhanced harmonic performance, the MC, which is controlled by the simplified Venturini modulation technique, improves the efficiency and dependability of the system. Simulation outcomes confirm that the ANN-based MPPT enhances the power extraction efficiency and improves the system performance. This study shows how wind energy systems can be optimized for smart grids by integrating advanced control techniques like FOC and simplified Venturini modulation with intelligent algorithms like ANN. © 2025 by the authors.Science Citation Index Expande