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The growth of photovoltaic power plants is continuously rising, this growth would not be possible without safety, monitoring, and fault detection systems. In this paper, the common faults of a typical photovoltaic power plant that may occur in a photovoltaic module are discussed. Also, the paper studies the electrical characteristics of a photovoltaic module operating under several faults’ conditions applied on a specially designed module that measures the output current of each substring by utilizing sensitive Hall Effect sensors. After obtaining the electrical characteristics under faults, using machine learning, two decision trees classifier models are trained, the first classifier is trained to detect and recognize faults. However, this classifier may confuse the partial shading case with several other faults. Hence, the second decision tree classifier is trained to distinguish the exact fault type when the module is operating under partial shading condition by applying a short-circuit test on the photovoltaic module. This design can be achieved by connecting current sensors in the junction box of a typical photovoltaic module.

In this paper, a waypoint-based path tracking approach is suggested for the swarm robots to follow the desired path in an organized way. In the study, the applicability of the waypoint-based path tracking on the swarm robots that show flexible and scalable behavior has been demonstrated. To evaluate the proposed path planing approach with regard to scalability and flexibility, simulations have been applied in with/without obstacle arenas with different numbers of robots and according to different lookahead distances. With the proposed approach, each swarm robots exhibit swarm behavior in an organized manner depending on the distance of the lookahead to the path to track in the with / without obstacle arenas.

Solar power prediction is an important problem that has gained significant attention in recent years due to the increasing demand for renewable energy sources. In this paper, we present the results of using four different regression models for solar power prediction: linear regression, logistic regression, Lasso regression, and elastic regression. Our results show that all four models are able to accurately predict solar power, but Lasso regression and elastic regression outperform linear and logistic regression in terms of predicting the maximum solar power output. We also discuss the advantages and disadvantages of each model in the context of solar power prediction.

The paper investigates the better possible combined initial conditions of leader-follower formations of nonholonomic mobile robots for Input/Output Linearization Technique. Initial conditions are applied to two followers and one leader robot. The first follower tries to maintain desired distance and angle towards the leader while the second follower tries to maintain desired distances to the first follower and the leader. In simulations, it is observed that, changing initial relative positions and velocities as well as angles can cause robots act differently throughout the whole leader- follower trajectory. At the end, optimum initial conditions are proposed for the best trajectory., Bu çalışmada, Giriş/Çıkış Doğrusallaştırma Tekniği ile, holonomik olmayan mobil robotlara Lider-Takipçi Formasyon Kontrolü uygulandığında, daha iyi sonuçlar veren başlangıç koşulları araştırılmıştır. Başlangıç koşulları bir lider ve iki takipçi robotta denenmiştir. Kontrol kuralı, ilk takipçinin lidere göre istenilen mesafe ve açıyı; ikinci takipçinin lidere göre ve ilk takipçiye göre istenilen mesafeyi koruması şeklindedir. Simülasyonlarda başlangıç koordinatları, hızları ve açılarının değiştirilmesinin robotların tüm lider-takipçi yolculuğunda farklı davranmasına sebep olduğu gözlemlenmiştir. Makalenin sonunda, en iyi takip için optimal başlangıç koşulları önerilmiştir.

Various neuron models have been developed to understand the working principles of nerve cells and their physiological properties and behavior, some of such models are Hodgkin-Huxley (HH), FitzHugh-Nagumo, Morris-Lecar, Hindmarsh-Rose, Izhikevich, Integrate & Fire and Adaptive Exponential Integrate-Fire models. Especially in recent years, research studies on neuron structure, behavior and inter-neuronal phenomenas have become an important research area. HH neuron model has been simulated a number of times by numerical methods in order to better understand the physiology and behavior of the neurons. However, when the literature is looked at, it could easily be observed that the electrical equivalent circuit of the HH neuron model had not been simulated. In this paper, equivalent circuit of HH neuron model is simulated using the range of parameter values of numerical simulation methods, via MATLAB / Simulink and electronic circuit elements such as resistor, capacitor and voltage sources. And it is observed that the expected all stages of the action potential were not formed. But, it has been shown that resting, depolarization and repolarization phases of the action potential were obtained provided that the excitation current applied to the circuit and the change of capacitor values of the circuit but the hyperpolarization state was not fully formed. Therefore, it has been verified that the expected membrane voltages generated by electrical equivalent circuits are directly related to the excitation currents and capacitive values of variable capacitance., Sinir hücrelerinin çalışmasını anlamak, fizyolojik özelliklerini ve davranışlarını incelemek için geliştirilen Hodgkin-Huxley, FitzHugh-Nagumo, Morris-Lecar, Hindmarsh-Rose, Izhikevich, Integrate & Fire ve Adaptive Exponential Integrate-Fire gibi birçok modelleme mevcuttur. Bu nedenle özellikle son yıllarda nöron yapısı, davranışı ve nöronlar arası fenomenler üzerine yapılan çalışmalar önemli bir alan haline gelmiştir. Nöron fizyolojisinin ve davranışlarının daha iyi anlaşılması için Hodgkin-Huxley (HH) nöron modeli, nümerik metotlar ile birçok kez simüle edilmiştir. Fakat literatür incelendiğinde Hodgkin-Huxley nöron modelinin elektriksel eş devresinin simüle edilmediği görülmüştür. Bu çalışmada, Hodgkin-Huxley nöron modeli eşdeğer devresi temel alınmış ve MATLAB/Simulink ortamında temel elektronik devre elemanları kullanılarak, nümerik metot benzetimlerinde kullanılan parametre değer aralıkları ile simüle edilmiş ve aksiyon potansiyelinin sadece dinlenme aşamasının oluştuğu diğer aşamaların oluşmadığı gözlemlenmiştir. Ancak devreye uygulanan uyarı akımı ve devrenin kapasite parametreleri değiştirildiğinde aksiyon potansiyelinin dinlenme, depolarizasyon ve repolarizasyon aşamalarının oluştuğu fakat hiperpolarizasyon durumunun tam olarak oluşmadığı gözlemlenmiştir. Böylece, nöron elektriksel eş devresinin oluşturduğu membran geriliminin, uyarı akımlarıyla ve kapasitans değerleriyle doğrudan ilişkili olduğu anlaşılmıştır.