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Elektrik - Elektronik Mühendisliği Bölümü Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/202

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Start date: 2020Language: search.filters.language.eng

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  • Review
    Aerial Swarms: Recent Applications and Challenges
    (Springer, 2021) Mohamed Abdelkader; Samet Güler
    Purpose of review: Currently, there is a large body of research on multi-agent systems addressing their different system theoretic aspects. Aerial swarms as one type of multi-agent robotic systems have recently gained huge interest due to their potential applications. However, aerial robot groups are complex multi-disciplinary systems and usually research works focus on specific system aspects for particular applications. The purpose of this review is to provide an overview of the main motivating applications that drive the majority of research works in this field, and summarize fundamental and common algorithmic components required for their development._x000D_ _x000D_ Recent findings: Most system demonstrations of current aerial swarms are based on simulations, some have shown experiments using few 10 s of robots in controlled indoor environment, and limited number of works have reported outdoor experiments with small number of autonomous aerial vehicles. This indicates scalability issues of current swarm systems in real world environments. This is mainly due to the limited confidence on the individual robot's localization, swarm-level relative localization, and the rate of exchanged information between the robots that is required for planning safe coordinated motions._x000D_ _x000D_ Summary: This paper summarizes the main motivating aerial swarm applications and the associated research works. In addition, the main research findings of the core elements of any aerial swarm system, state estimation and mission planning, are also presented. Finally, this paper presents a proposed abstraction of an aerial swarm system architecture that can help developers understand the main required modules of such systems.
  • Conference Object
    Machine Learning Assisted Particle Size and Type Classification Using Wavelength-Dependent Scattering Patterns
    (Wroclaw University of Science and Technology (WUST), 2021) Sinan Genc; Kutay Icoz; Talha Erdem
    The presence of microplastics in oceans and water supplies have increased to critical levels within the last decade [1]. In addition to the huge mass of plastics in the seas, additional contribution to water pollution comes from our chemical wastes including toothpaste, detergents, cosmetics etc. All these pollutants end up in seas or clean water sources, which eventually affects the sea life but also the human health via the water consumption and the food chain [2]. Slowing down the microparticle pollution in water first relies on identifying and tracking these particles in a cost-effective manner so that the microparticles can be easily detected before they accumulate. To address this challenge, in this study, we investigated the scattering patterns of different microplastic samples at different concentrations in aqueous samples. By analyzing these scattering patterns obtained using blue, green, and red low-power lasers, we show that it is possible to classify the microparticles particles in terms of their size, concentration, and first time for the material type in a liquid sample thanks to random forest algorithm that accomplish the limited theoretical calculations. Figure 1: (a) Scattering behavior of 8 um Me samples under green laser with increasing concentration (b) scattering behavior of three different microplastics under red laser with 1.50 fM concentration. The aim of all these experiments was to show that the scattering patterns change for different type and size of the microplastics in liquid samples. As presented in Fig. 1(a), for the same excitation wavelength and material at the same size (green laser operating at 520 nm and 8 um-sized Melamine microparticles) the distance of the observed peaks and valleys from the center does not have any concentration dependence; nevertheless, the scattering intensity increases very strongly as the particle concentration increases. Especially the average intensities of the pixels, farthest away from the center turn out to be clear indicators of the microparticle concentration in water. In Fig. 1(b), we employed a red laser operating at 650 nm to record the scattering patterns of these particles all at 1.50 fM. The comparison between the melamine and polystyrene particles having the same size reveals peaks at different distances from the center and at different intensities originating from the different refractive indices of these particles.
  • Article
    Ergotropy of Quantum Battery Controlled via Target Attractor Feedback
    (IOSR Journal Of Applied Physics (IOSR-JAP), 2020) Sergey Borisenok
    Model: Quantum battery (QB) is a device that is capable to be charged efficiently and store the energy for a long period of time to be transferred to consumption centers. There are many different physical types of such devices and different charging schemes. Here we discuss the single-qubit based QB in the form of quantum oscillator in a Markovian bath environment. The charging of QB is performed via so-called 'coherent' control u(t) in the Hamiltonian and time dependent spectral density n(t) as an 'incoherent' control (number of excitations in the bath). Our goal is to drive the ergotropy of the stored qubit via the certain control algorithm. Methods: For the effective control we apply here Kolesnikov’s ‘target attractor’ (TA) feedback algorithm. In the frame of this approach we form an attractor set targeting the evolution of the basic characteristics of quantum battery. TA method makes the effective design of the control fields charging the battery; the corresponding control signals could be restored explicitly from the dynamical equations. Interestingly, the proposed algorithm applied to our single qubit model of QB has an analytical solution. Results and Discussion: As a result for the control goal, we obtain an exponentially converting behavior for driving the quantum battery ergotopic characteristics. Our algorithm can be extended to the multi-qubit model of QB (for the parallel or collective charging scheme). It could be applied also for different physical realizations of QBs: Dicke QB, spin QB, harmoniс oscillator QB; and for all working stages of the QB (charging, long time storage and the energy transfer to a consumption center or engine). Conclusion: Feedback algorithms, particularly in the form of target attractor approach, can be applied efficiently to control the set of fundamental characteristics of quantum batteries, including the ergotropy, charging power and others. The analytical study of the proposed model and its numerical simulations demonstrate the possibility to imply the developed mathematical algorithm experimentally for a single qubit system and the set of few qubits as well.
  • Article
    Suppressing Epileptiform Dynamics in Small Hodgkin-Huxley Neuron Clusters via Target Repeller-Attractor Feedback
    (IOSR Journal of Mathematics (IOSR-JM), 2020) Sergey Borisenok
    Model: Quantum battery (QB) is a device that is capable to be charged efficiently and store the energy for a long period of time to be transferred to consumption centers. There are many different physical types of such devices and different charging schemes. Here we discuss the single-qubit based QB in the form of quantum oscillator in a Markovian bath environment. The charging of QB is performed via so-called 'coherent' control u(t) in the Hamiltonian and time dependent spectral density n(t) as an 'incoherent' control (number of excitations in the bath). Our goal is to drive the ergotropy of the stored qubit via the certain control algorithm. Methods: For the effective control we apply here Kolesnikov’s ‘target attractor’ (TA) feedback algorithm. In the frame of this approach we form an attractor set targeting the evolution of the basic characteristics of quantum battery. TA method makes the effective design of the control fields charging the battery; the corresponding control signals could be restored explicitly from the dynamical equations. Interestingly, the proposed algorithm applied to our single qubit model of QB has an analytical solution. Results and Discussion: As a result for the control goal, we obtain an exponentially converting behavior for driving the quantum battery ergotopic characteristics. Our algorithm can be extended to the multi-qubit model of QB (for the parallel or collective charging scheme). It could be applied also for different physical realizations of QBs: Dicke QB, spin QB, harmoniс oscillator QB; and for all working stages of the QB (charging, long time storage and the energy transfer to a consumption center or engine). Conclusion: Feedback algorithms, particularly in the form of target attractor approach, can be applied efficiently to control the set of fundamental characteristics of quantum batteries, including the ergotropy, charging power and others. The analytical study of the proposed model and its numerical simulations demonstrate the possibility to imply the developed mathematical algorithm experimentally for a single qubit system and the set of few qubits as well.
  • Article
    Control over Cavity Assisted Charging for Dicke Quantum Battery
    (ResearchGate, 2020) Sergey Borisenok
    We study feed forward (open-loop) control approach for driving the cavity assisted charging process in the Dicke quantum battery, in which the coupling between the cavity and quantum twolevel subsystem(s) plays a role of control parameter.The dynamics of the system is described with the Tavis - Cummings Hamiltonian. The analytical result is supported with the corresponding numerical simulations to demonst
  • Article
    Design and analysis of low profile and low SAR full-textile UWB wearable antenna with metamaterial for WBAN applications
    (ELSEVIER SCIENCE BV, PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS, 2020) Husnu Yalduz; Timucin EmreTabaru; Veli Tayfun Kilic; Mustafa Turkmen
    In this paper, a low-profile wearable antenna with metamaterial (MM) for wireless body area network (WBAN) applications is presented. The designed antenna with MM operates in the ultra-wideband (UWB) between 4.55 and 13 GHz and it has a thickness of 4.68 mm. To the best of our knowledge, it is the lowest thickness reported in the literature for UWB antennas with MM. The proposed is designed and manufactured using fully flexible textiles. The designed antenna was simulated in free space and on the human body model. Simulation results show that gain, directionality, and front-to-back ratio of the antenna increase considerably with the placement of the MM. Also, in simulations, it is found that the specific absorption rate (SAR) values for the designed antenna reduce by 98.3% when MM is used. These SAR values calculated for the designed antenna with MM are well below the limits defined in European standards. The designed antenna and metamaterials were manufactured, too, and scattering parameters were measured. Measurement results are in good agreement with the results found in the simulations. It shows that the proposed antenna is very suitable for use in WBAN applications due to its low thickness, having low SAR, and UWB operation.