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Institution Author: Turan, Mehmet

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    Citation - WoS: 4
    Citation - Scopus: 4
    On the Powers of the Kummer Distribution
    (Academic Publication Council, 2017) Ostrovska, Sofiya; Turan, Mehmet; Mathematics
    The Kummer distribution is a probability distribution, whose density is given by f (x) = cx (alpha-1)(1 + delta x)(-gamma) e(-beta x), X > 0, where alpha, beta, delta > 0, gamma is an element of R and C is a normalizing constant. In this paper, the distributions of random variable X-P, p > 0, where X has the Kummer distribution, are considered with the conditions being IFR/DFR, some properties of moments depending on the parameters and the moment-(in) determinacy. In the case of moment-indeterminacy, exemplary Stieltjes classes are constructed.
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    Article
    On Quasi-Weibull Distribution
    (Univ Miskolc inst Math, 2025) Ostrovska, Sofiya; Turan, Mehmet
    Exponential distribution together with a variety of its transformations is permanently used both in probability theory and related fields. The most popular one is the power transformation yielding the Weibull distribution. In this paper, the power distribution of exponential random variable is supplemented by a logarithmic factor leading to a new distribution called quasi-Weibull. This is a three-parameter distribution, where one parameter is inherited from the underlying exponential distribution, and the others originate from the transformation. The properties of the quasi-Weibull distribution are studied. Specifically, the impact of the parameters on the analyticity of characteristic function, the existence of the moment generating function, the moment-determinacy/indeterminacy and the behaviour of the hazard function are investigated.
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    Article
    Citation - WoS: 1
    Citation - Scopus: 1
    Evaluation and Optimization of Nonlinear Central Pattern Generators for Robotic Locomotion
    (Romanian Soc Control Tech informatics, 2018) Elbori, Abdalftah; Turan, Mehmet; Arikan, Kutluk Bilge; Department of Mechatronics Engineering; Mathematics
    With regard to the optimization of Central Pattern Generators (CPGs) for bipedal locomotion in robots, this paper investigates how the different cases of CPGs such as uncoupled, unidirectional, bidirectional two CPGs are used to produce rhythmic patterns for one leg with two degrees of freedom (DOF). This paper also discusses the stability analysis of CPGs and attempts to utilize genetic algorithms with the hybrid function and adapts the CPGs to robotic systems that perform one-leg movement, by utilizing the bidirectional two CPGs. The results show far greater improvement than in the other cases. CPGs not only enhance movement but also control locomotion without any sensory feedback.