Static synchronous compensators (STATCOMs) are increasingly present in the power system scenario. The Delta-connected Cascaded H-bridge (Delta-CHB) is a widespread option for medium-and high-voltage STATCOM systems. H...
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In recent years, advances in automotive IoT technology have not only improved automated driving and driving convenience but have also led to a diminishing number of traffic accidents. Vehicle Ad-hoc Networks (VANETs) ...
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In this paper, The network with a faster detection speed than the original YOLOv5 nano model is proposed. The network defined as a bridge module reduced the number of channels and changed the speed quickly by applying...
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Binary Neural Networks (BNNs) are gaining popularity for solving real-world problems using Deep Neural Networks (DNNs), such as image recognition and natural language processing. BNNs use binary precision for weights ...
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As time progresses, the power capacity of the photovoltaic (PV) module grad.ally diminishes. Therefore, it is crucial to assess the PV module performance to ensure it aligns with the manufacturer specifications. One e...
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This work proposes a method for the stability analysis of aperiodic sampled-data control systems with sector and slope bounded input nonlinearities. The stability conditions are derived by using a hybrid system repres...
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This work proposes a method for the stability analysis of aperiodic sampled-data control systems with sector and slope bounded input nonlinearities. The stability conditions are derived by using a hybrid system representation and a timer-dependent Lur'e type Lyapunov function. Considering a polynomial timer-dependence, the stability conditions are cast in sum-of-squares optimization problems aiming at computing the largest range of sampling intervals or the largest sector bounds on the nonlinearity for which the origin of the closed-loop system is globally asymptotically stable.
In recent years, advances in automotive IoT technology have not only improved automated driving and driving convenience but have also led to a diminishing number of traffic accidents. Vehicle Ad-hoc Networks (VANETs) ...
In recent years, advances in automotive IoT technology have not only improved automated driving and driving convenience but have also led to a diminishing number of traffic accidents. Vehicle Ad-hoc Networks (VANETs) have attracted much attention because automotive IoT is based on wireless communications. Ad-hoc routing protocols that apply the characteristics of vehicle-to-vehicle (V2V) networks are needed. One of them is Greedy Perimeter Stateless Forwarding (GPSR), a routing protocol using geographic information. It uses Global Positioning System (GPS) information for routing. However, GPSR may increase the packet drop rate due to radio attenuation and fading. Therefore, C. Li et al. proposed to select the next hop by evaluating the link quality. However, due to the large moving speed of the node, the next hop may be out of the radio propagation range at the communication timing. Therefore, in this study, we propose a new routing method that combines the future location prediction proposed by Z.S. Houssaini et al. The effectiveness of the method is demonstrated by simulations using ns-3 with traffic data acquired by SUMO.
Static synchronous compensators (STATCOMs) are increasingly present in the power system scenario. The Delta-connected Cascaded H-bridge (Delta-CHB) is a widespread option for medium-and high-voltage STATCOM systems. H...
Static synchronous compensators (STATCOMs) are increasingly present in the power system scenario. The Delta-connected Cascaded H-bridge (Delta-CHB) is a widespread option for medium-and high-voltage STATCOM systems. However, the non-negligible second-harmonic ripple in the capacitor voltages directly affects the submodule voltages and, consequently, leads to an inherent third harmonic circulating current, which can increase power losses. This paper analytically describes this phenomenon and proposes a simple strategy based on a proportional resonant controller in the circulating current loop. So far, the strategy has been validated through both simulation and experimental results. The proposed model presents an error of 1.6% between the calculated and simulated circulating current amplitude. The proposed mitigation strategy provides a reduction in the circulating current ripple by 95.45% in the experiment, compared to the conventional control strategies found in the literature.
Binary Neural Networks (BNNs) are gaining popularity for solving real-world problems using Deep Neural Networks (DNNs), such as image recognition and natural language processing. BNNs use binary precision for weights ...
Binary Neural Networks (BNNs) are gaining popularity for solving real-world problems using Deep Neural Networks (DNNs), such as image recognition and natural language processing. BNNs use binary precision for weights and activations, reducing memory usage by 32 times compared to conventional networks using 32-bit floating-point precision. Among various types of BNNs, AQFP-based BNNs utilizing superconducting logic families are promising for energy-efficient computing, using magnetic flux quantization and quantum interference in Josephson-junction-based superconductor loops. This paper presents a performance assessment of a novel AQFP-based BNN architecture, highlighting scalability issues caused by increased inductance in the analog accumulation circuit. We also discuss potential optimization approaches to address these issues and improve scalability.
This paper proposes a Complex-Valued Neural Network (CVNN) for glucose sensing in milli-meter wave (mmWave). Based on the propagation characteristics of millimeter wave in glucose medium, we obtain the S21 parameter o...
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