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Area Computation by the Alternative Coordinate Method

Area Computation by the Alternative Coordinate Method

The alternative coordinate method, also known as the Shoelace Formula, is a technique for determining the area of a traverse using Cartesian coordinates. This method relies on the sequential arrangement of x and y coordinates for each point of the shape, ensuring accuracy and ease of application.In this approach, each corner's x and y coordinates are listed as fractions, with the x-coordinate as the numerator and the y-coordinate as the denominator. These coordinates are arranged sequentially...

Design Example: Capacitance Multiplier Circuit

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In integrated circuit technology, a capacitance multiplier is often utilized to produce a larger capacitance value when a small physical capacitance falls short. This is achieved by a circuit that multiplies capacitance values by a factor of up to 1000, such that a 10-pF capacitor can replicate the performance of a 100-nF capacitor.
The circuit illustrated in Figure 1 below incorporates two op-amps, with the first operating as a voltage follower and the second acting as an inverting amplifier.

In Vitro Drug Dissolution: Alternative Methods

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Alternative drug dissolution methods include the rotating bottle, intrinsic dissolution test, peristalsis, and the Franz diffusion cell method. The rotating bottle method involves meticulously rotating tightly capped controlled-release beads in a temperature-controlled bath. Periodic decanting of samples allows for residue assay, followed by refilling with fresh medium and testing at various pH levels to emulate the gastrointestinal tract conditions.In contrast, the intrinsic dissolution test...

Linear Circuits

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A linear circuit is characterized by its output having a direct proportionality to its input, adhering to the linearity property, which encompasses the principles of homogeneity (scaling) and additivity. Homogeneity dictates that when the input, also referred to as the excitation, is multiplied by a constant factor, the output, known as the response, is correspondingly scaled by the same constant factor. For instance, if the current is multiplied by a constant 'k,' the voltage likewise...

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一种线性交替方向乘法方法用于联邦矩阵完成问题.

Patrick Hytla, Tran T A Nghia, Duy Nhat Phan

IEEE transactions on neural networks and learning systems

|January 21, 2026

概括

此摘要是机器生成的。

本研究介绍了FedMC-ADMM,这是一个新的联邦矩阵完成 (MC) 方法,用于隐私保护数据预测. 它有效地处理复杂的数据,而不损害用户隐私,优于现有的方法.

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Stereo-Imaging System DLT Calibration to Capture 3D In Situ Displacements of Stretched Peripheral Nerves

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Matrix-assisted Laser Desorption/Ionization Time of Flight MALDI-TOF Mass Spectrometric Analysis of Intact Proteins Larger than 100 kDa

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科学领域:

计算机科学计算机科学
机器学习机器学习
数据科学数据科学数据科学

背景情况:

矩阵完成 (MC) 对于预测各个领域缺失的数据至关重要.
传统的MC方法面临着集中数据存储的挑战,包括隐私,可扩展性和效率.
联合学习 (FL) 提供了一个解决方案,可以在分布式数据集上进行协作学习,而无需共享原始数据.

研究的目的:

为了应对隐私敏感应用程序中联合矩阵完成 (MC) 的挑战.
提出一个新的算法框架,FedMC-ADMM,用于解决联合MC问题.
为具有多块变量的联合MC提供理论保证.

主要方法:

开发了FedMC-ADMM,它结合了乘数的交替方向方法 (ADMM) 与随机区块坐标和近接梯度策略.
设计用于处理联合MC固有的多块非凸和非光滑优化问题.
分析了理论的收性质,确定了后续收率和O(K^{-1/2}) 的收率.

主要成果:

FedMC-ADMM证明了后续的融合,通信复杂度为O{\displaystyle O{\sqrt {-2} } .
该算法有效地处理多块非凸和非光滑的优化问题.
在MovieLens和Netflix数据集上的广泛实验表明,FedMC-ADMM在融合速度和准确性方面超过了现有的方法.

结论:

FedMC-ADMM为联邦矩阵完成提供了一个高效和私有解决方案.
这项工作为具有多块变量的联合MC提供了第一个理论保证.
拟议的方法显示了对现实应用的性能显著改善.