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An Improved Current Ripples Minimization Technique for Cascaded DC–DC Converter in DC Microgrid 直流微电网中级联直流-直流转换器的改进型电流纹波最小化技术
IF 0.9 Q3 Engineering Pub Date : 2024-05-20 DOI: 10.5152/electrica.2024.23177
Khadidja Khattab, Ahmed Safa, Abdelmadjid Gouichiche, Youcef Messlem, D. Abdeslam, Abdelilah Chibani
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引用次数: 0
Discretization of Stator Current of Induction Motor Using Predictive Control 利用预测控制实现感应电机定子电流的离散化
IF 0.9 Q3 Engineering Pub Date : 2024-05-17 DOI: 10.5152/electrica.2024.24042
Yasin Koçak, N. Bayhan
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引用次数: 0
Reduced-Order Fractionalized Controller for Disturbance Compensation Based on Direct Torque Control of DSIM With Less Harmonic 基于低谐波 DSIM 直接转矩控制的扰动补偿减阶分化控制器
IF 0.9 Q3 Engineering Pub Date : 2024-05-17 DOI: 10.5152/electrica.2024.23194
Sifelislam Guedida, B. tabbache, K. Nounou, Abdelhakim Idir
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引用次数: 0
Hazardous Zone Identification by Spectral Analysis of Ground Penetrating Radar Response 通过对探地雷达响应的频谱分析识别危险区
IF 0.9 Q3 Engineering Pub Date : 2024-05-17 DOI: 10.5152/electrica.2024.23186
Udbhav Joshi, Rahul Dev Garg, Neerav Sharma, Vinod Kumar Joshi, Kavita Sharma
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引用次数: 0
Design and Analysis of Time-Varying Derivative Fractional Order Proportional–Integral–Derivative Controller for Frequency Regulation of Shipboard Microgrid System 用于舰载微电网系统频率调节的时变微分阶比例-积分-微分控制器的设计与分析
IF 0.9 Q3 Engineering Pub Date : 2024-05-14 DOI: 10.5152/electrica.2024.23055
Sonalika Mishra, P. C. Nayak, R. Prusty, S. Panda
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引用次数: 0
Fractional Order PD(1+ PI) Controller for Frequency Control of Power System with Renewable Sources and Electric Vehicle 用于可再生能源和电动汽车电力系统频率控制的分数阶 PD(1+ PI)控制器
IF 0.9 Q3 Engineering Pub Date : 2024-05-14 DOI: 10.5152/electrica.2024.23143
Asini Kumar Baliarsingh, S. K. Mohapatra, P. Dash
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引用次数: 0
An Image Processing-Based Approach for Reading Needle-Type Instruments on Aircraft 基于图像处理的飞机针式仪器读取方法
IF 0.9 Q3 Engineering Pub Date : 2024-05-13 DOI: 10.5152/electrica.2024.23190
Fatma Gümüş, Can Eyüpoğlu
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引用次数: 0
Comparison of Time Series Forecasting for Intelligent Transportation Systems in Digital Twins 数字双胞胎中智能交通系统的时间序列预测比较
IF 0.9 Q3 Engineering Pub Date : 2024-05-13 DOI: 10.5152/electrica.2024.23200
Mehmet Ali Ertürk
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引用次数: 0
Estimation of Future Number of Passes and Optimization of Number of Trips Based on Istanbul Hourly Public Transportation Data 根据伊斯坦布尔每小时公共交通数据估算未来通行证数量并优化出行次数
IF 0.9 Q3 Engineering Pub Date : 2024-01-31 DOI: 10.5152/electrica.2024.23197
Emel Geçici, Zeynep Gürkaş Aydin
Considering the signi fi cance of transportation in everyday life, issues related to transportation are commonly encountered in developing and developed countries. The problems encountered in most countries are likewise evident in our country and manifest throughout several domains. Factors contributing to the issue include excessive passengers, inadequate trip availability to ful fi ll demand, ine ff ective line and route organization in addressing passenger requests, incomplete routes
考虑到交通在日常生活中的重要性,与交通有关的问题在发展中国家和发达国家都普遍存在。大多数国家遇到的问题在我国也同样明显,并体现在多个领域。造成这一问题的因素包括乘客过多、行程供应不足以满足需求、线路和路线组织在满足乘客要求方面效率低下、路线不完整等。
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引用次数: 0
Fluorescence Microscopy Denoizing via Neighbor Linear Embedding 通过邻域线性嵌入实现荧光显微镜去噪
IF 0.9 Q3 Engineering Pub Date : 2024-01-31 DOI: 10.5152/electrica.2024.23027
Cagatay Kirmiziay, Burhan Aydeniz, Mehmet Turkan
One of the di ffi culties in studying fl uorescence imaging of biological structures is the presence of noise corruption. Even though hardware-and software-related technologies have undergone continual improvement, the unavoidable e ff ect of Poisson–Gaussian mixture type is generally encountered in fl uorescence microscopy images. This noise should be mitigated to allow the extraction of valuable information from fl uorescence images for various types of biological analysis. Thus, this study introduces a new and e ffi cient learning-based denoizing approach for fl uorescence microscopy. The proposed approach is based mainly on linear transformations between noise-free and noisy submanifold structures of patch spaces, bene fi ting from linear neighbor embeddings of local image patches. According to visual and statistical results, the developed algorithm called "neighbor linear-embedding denoizing" algorithm has a highly competitive and generally superior performance in comparison with the other algorithms used for fl uorescence microscopy image denoizing in the literature
生物结构荧光成像研究的难题之一是存在噪声破坏。尽管软硬件相关技术在不断进步,但在荧光显微成像中仍不可避免地会出现泊松-高斯混合型噪声。要从荧光图像中提取有价值的信息用于各种生物分析,就必须降低这种噪声。因此,本研究为荧光显微镜引入了一种新的、基于高效学习的去噪方法。所提出的方法主要基于补丁空间的无噪声和噪声子曲面结构之间的线性变换,并从局部图像补丁的线性邻域嵌入中获益。根据视觉和统计结果,所开发的 "邻域线性嵌入去噪 "算法与文献中用于荧光显微图像去噪的其他算法相比,具有很强的竞争力和普遍优越的性能。
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引用次数: 0
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Electrica
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