Sequentially Modified Gravitational Search Algorithm for Image Enhancement

Gravitational Search Algorithm (GSA) is based on the acceleration trend feature of objects with a mass towards each other and includes many interdependent parameters. The gravitational constant among these parameters influences the speeds and positions of the agents, meaning that the search capability depends on the largescale gravitational constant. The proposed new algorithm, which was obtained with the use of two operators at different times of the call and sequentially doing works, was named as Sequentially Modified ‎ Gravitational Search Algorithm (SMGSA). SMGSA is applied to 10 basic and 6 composite benchmark functions. Each function is run 30 times and the best, mean and median values are obtained. The achieved results are compared with the Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and GSA among the heuristic optimization algorithms. Between GSA and the operator for each function convergence speed, standard deviation and graphical comparisons are included. Beside this, by using the Wilcoxon signed rank test, the comparison of the averages of the data as two dependent groups of GSA and the new operators is performed. It is seen that the obtained results provided better results than the other methods. Additionally, in this study, SMGSA was applied to the transformation function among image enhancement techniques which are engineering applications. The success of this method has been increased by optimizing the parameters of the transformation function used. Effective improvement has been achieved in terms of both visual and information quality

MERMER KESME İŞLEMİNDE KESİM SÜRESİNİN YAPAY SİNİR AĞI TABANLI MODELLENMESİ

Doğrusal olmayan bir yapıya sahip olan mermer kesim süresi testere devir sayısına, vagon ilerleme hızına ve zamana karşılık kesim miktarına bağlı olarak değişmektedir. Bu değişkenlere bağlı olarak daha önce laboratuar ortamında yapılmış olan deneylerden elde edilen verilerin matematiksel olarak modellenmesi oldukça zordur. Bu çalışmada, mermer kesme işleminin bitiş süresine yönelik yapay sinir ağ (YSA) tabanlı bir modelleme işlemi gerçekleştirilmiştir. Eğitim esnasında deney verilerinin %90’ı verilmiş olup %10’u test amaçlı kullanılmıştır. Elde edilen sonuçlara göre, gerçekleştirilen modellemenin uygulanabilir olduğu görülmüştür

Sliding Mode Control Based Supercapacitor Modeling for Dynamic Stability in DFIG Based Wind Turbines

The supercapacitor is among the elements commonly used to store energy as an important component in sustainable energy systems. In doubly fed induction generators (DFIGs), the supercapacitor is used to compensate voltage dips and damping oscillations. In this study, a different supercapacitor model was developed for system stability in a DFIG-based wind turbine connected to an infinite bus. In the development of the mathematical supercapacitor model, the lookup table was realized with the voltage-capacity relationship and sliding mode control. DFIG modeling with/without the developed supercapacitor was performed for symmetrical and asymmetrical fault situations, and the findings were then compared and interpreted in detail. The simulation study analysis was conducted in a MATLAB/SIMULINK environment. The developed supercapacitor model yielded impressive results in symmetrical and asymmetrical faults

Snapshot evaluation of acute and chronic heart failure in real-life in Turkey: a follow-up data for mortality

Objective: Heart failure (HF) is a progressive clinical syndrome. SELFIE-TR is a registry illustrating the overall HF patient profile of Turkey. Herein, all-cause mortality (ACM) data during follow-up were provided. Methods: This is a prospective outcome analysis of SELFIE-TR. Patients were classified as acute HF (AHF) versus chronic HF (CHF) and HF with reduced ejection fraction (HFrEF), HF with mid-range ejection fraction, and HF with preserved ejection fraction and were followed up for ACM. Results: There were 1054 patients with a mean age of 63.3±13.3 years and with a median follow-up period of 16 (7–17) months. Survival data within 1 year were available in 1022 patients. Crude ACM was 19.9% for 1 year in the whole group. ACM within 1 year was 13.7% versus 32.6% in patients with CHF and AHF, respectively (p<0.001). Angiotensin-converting enzyme inhibitor/angiotensin receptor blocker, beta blocker, and mineralocorticoid receptor antagonist were present in 70.6%, 88.2%, and 50.7%, respectively. In the whole cohort, survival curves were graded according to guideline-directed medical therapy (GDMT) scores ?1 versus 2 versus 3 as 28% versus 20.2% versus 12.2%, respectively (p<0.001). Multivariate analysis of the whole cohort yielded age (p=0.009) and AHF (p=0.028) as independent predictors of mortality in 1 year. Conclusion: One-year mortality is high in Turkish patients with HF compared with contemporary cohorts with AHF and CHF. Of note, GDMT score is influential on 1-year mortality being the most striking one on chronic HFrEF. On the other hand, in the whole cohort, age and AHF were the only independent predictors of death in 1 yea

ADAPTIVE IMAGE FILTER DESIGN

Görüntü işleme yöntemleri sayısal ve analog kamera, röntgen, bilgisayarlı tomografi, manyetik rezonans, nükleer tıp ve ultrasound gibi tıbbi görüntüleme cihazlarından elde edilen görüntülerin yorumlanmasında kullanılmaktadır. Ancak elde edilen görüntüler, oluşumunda ve iletim sırasında meydana gelen bozulmalardan ve gürültülerden dolayı doğrudan kullanılabilecek durumda değildir. Bundan dolayı görüntü işleme analizlerinin yapılabilmesi için filtre işlemlerine tabi tutulması gerekmektedir. 1980'li yıllardan itibaren görüntü filtrelemede kısmi diferansiyel denklemler temelli teknikler kullanılmaktadır. Ancak kullanılan bu filtreleme teknikleri görüntüdeki gürültüyü yok ederken orijinal görüntünün kenarlarında kalınlaşma ve bozulmalar meydana getirmektedir. Bu tezde renkli ve gri görüntülerin filtrelenmesi için yeni bir algoritma geliştirilmiştir. Yayınım katsayıları için piksellerin benzerlik oran değerleri kullanılmıştır. Bunun için üç farklı matematiksel yaklaşım daha sonra bulanık mantık tabanlı bir yaklaşım kullanılmıştır. Yapılan test ve uygulamalarda, geliştirilen yaklaşımlardan elde edilen sonuçların, görüntülerin gürültülerini yok ederken kenar bilgilerin korunmasını diğer yaklaşımlardan daha iyi sonuç verdiği görülmüştür.Image processing methods are used to interpret images which are obtained from digital and analog cameras, and medical images which are obtained from medical equipments such as x-ray, computerized tomography, magnetic resonance, nuclear medicine, ultrason etc. Nevertheless, the obtained images are not directly used because of noises and corruptions occurred during acquation. Therefore they need filtering process in order to perform image analysis. The differential equation based image filtering techniques have been used since 1980. However these methods destroy edge in image while denoising. In this study, a novel algorithm was developed to filter gray scale and color images. Similarity measurements of pixels are used as diffusion coefficients. Moreover, three different mathematical approaches for similarity calculations are proposed initially and flowingly fuzzy logic based method was employed. It has been observed in simulations and applications that the edge preserving capabilities of the proposed algorithm are better than conventional approaches during filtering process

Combined economic emission dispatch solution using genetic algorithm based on similarity crossover

GUVENC, Ugur/0000-0002-5193-7990WOS: 000282704100015Combined economic emission dispatch (CEED) problem is to schedule the committed generating units outputs to meet the required load demand at minimum operating cost with minimum emission simultaneously. This multi-objective CEED problem is converted into a single objective function using a price penalty factor. In this paper, a novel Genetic Algorithm method based on similarity crossover for solving CEED problem in power systems is proposed. In the proposed method, children created by using similarity measurement between mother and father chromosomes relationship. The feasibility of the proposed approach is demonstrated for two different power systems, and it is compared in the recent literature. The study results show that the proposed approach is more efficient in finding higher quality solutions in CEED problems

Economic Dispatch Integrated Wind Power Using Coyote Optimization Algorithm

7th International Istanbul Smart Grids and Cities Congress and Fair (ICSG) -- APR 25-26, 2019 -- Istanbul, TURKEYguvenc, ugur/0000-0002-5193-7990WOS: 000518924200031Fossil fuels used in power system cause air pollution and global warming because of releasing greenhouse gases. Nowadays, renewable energy especially wind power has more widespread in power generation due to ecological concerns and increasing fuel prices. Therefore, it is presented the Economic Dispatch integrated wind power approach in this paper. However, wind power is stochastic because wind speed is uncertain in nature. Therefore Weibull Probability Density Function ( PDF) and Incomplete Gamma Function (IGF) are used to estimating and modelling wind power. To solve the problem effectively, Coyote Optimization Algorithm (COA) is implemented to the problem and it was tested on various power system consisting thermal generator and wind power generator. Simulation results generated by COA are compared with other heuristic algorithm such as GA and PSO. It can be clearly seen that COA produces better results than GA and PSO.IEEE, IEEE, Power & Energy Soc, Republ Turkey, Minist Energy & Nat Resources, Republ Turkey, Minist Environm & Urbanisat, Republ Turkey, Minist Ind & Technol, Republ Turkey, Minist Trade, Elder, HHB Exp

Escape velocity: a new operator for gravitational search algorithm

GUVENC, Ugur/0000-0002-5193-7990WOS: 000457458000003Gravitational search algorithm (GSA) is based on the feature of reciprocal acceleration tendency of objects with masses. The total force, which is formed as an influence of other agents, is an important variable in the calculation of agent velocity. It has been determined that the total force and, thus, the velocity of the agents that are located far away, is low due to the distance. In this case, they continue their search in bad areas, as their velocity is low, which means a decrease in their contribution to optimization result. In this paper, a new operator called escape velocity has been proposed which is inspired by the real nature of GSA. It has been suggested that adding the escape velocity negatively will enable the agents that remain far away or outside of group behavior to be included in the group or to be increased in velocity. Thus, the study of perfecting the herd or group approach within the search scope has been carried out. To evaluate the performance of our algorithm, we applied it to 23 standard benchmark functions and six composite test functions. Escape velocity gravitational search algorithm (EVGSA) has been compared with some well-known heuristic search algorithms such as GSA, genetic algorithm (GA), particle swarm optimization (PSO), and recently the new algorithm dragonfly algorithm (DA). Wilcoxon signed-rank tests were also utilized to execute statistical analysis of the results obtained by GSA and EVGSA. Standard and composite benchmark tables and Wilcoxon signed-rank test and visual results show that EVGSA is more powerful than other algorithms

Coyote optimization algorithm to solve energy hub economic dispatch problem

Regardless of energy type that we need today, it is important to use it efficiently and economically in the production, transmission and distribution stages. In line with the developing technology and needs, a new energy concept has emerged in which different energy types managed together in the past were managed independently. In this concept, energy infrastructures of more than one energy carrier such as electricity, gas and heat are met as Energy Hub (EH) to supply the demands such as electricity, gas, heating, cooling and compressed air by means of energy conversion, distribution and storage devices. EHs are expected to meet the demands energy with low operating costs. Energy hub economic dispatch problem (EHEDP) is a non-linear, non-convex, uniform and non-differential multidimensional optimization problem. In this study, the energy cost of the system is minimized by using the Coyote Optimization Algorithm (COA) for the solution of the EHEDP. The results obtained with COA have been compared with the results of heuristic algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Moth Swarm Algorithm (MSA) and Symbiotic Organisms Search Algorithm (SOS) in the literature. The compared results showed that COA performed better than other algorithms in solving EHED problem

Kademeli İleri Geri Yayılım ve Gauss Fonksiyon Modelleri ile Pomza ve Diatomit İçeren Çimento Harçlarının Basınç Dayanımlarının Tahmini

Bu çalışmada, yapay sinir ağı (YSA) ve uyarlamalı ağ tabanlı bulanık çıkarım sistemi (ANFIS) ile pomza ve diyatomit içerikli çimento harçlarının basınç dayanımlarının tahmini yapılmıştır. YSA için kademeli ileri geri yayılım algoritması, ANFIS için ise Gauss üyelik fonksiyonu tercih edilmiştir. Modellerin oluşturulmasında toplam 7 tip çimento ile üretilen harçların 2., 7., 28. ve 90. hidratasyon günlerinde belirlenen basınç dayanım sonuçları kullanılmıştır. Modellerin eğitim ve test süreçlerinde; 5 giriş (hidratasyon günü, Portland çimento, pomza, diatomit, su) ve 1 çıkış (basınç dayanımı) parametresi kullanılmıştır. Deney sonuçlarıyla modelden elde edilen sonuçların karşılaştırılması R2, MAPE ve RMSE gibi istatistiksel yöntemlerle gerçekleştirilmiştir. Elde edilen veriler, YSA modeli ile elde edilen sonuçların tüm hidratasyon günleri için hemen hemen gerçek değerlere ulaşıldığını ve bu modelin başarılı bir tahmin modeli olduğunu göstermektedir