The project schedule delay problem has received considerable attention for its significance
in impeding project performance. Compared to conventional projects, prefabricated …

Nearest Neighbors (k-NN) is a well-established algorithm for classification widely used in
various machine learning applications. Although-NN has many advantages, it suffers …

A rapid point-of-care method for the colorimetric detection of cisplatin was developed,
exploiting the efficient conversion of the chemotherapeutic drug into a high-performance …

k-NN, as one of the well-employed classification algorithms, severely suffers from a
computationally intensive nature. This paper exploits the parallelism and digit level …

The quest for efficient Tiny Machine Learning on Microcontroller Units is increasing rapidly
due to the vast application spectrum made possible with the advancement of Tiny ML. One …

Binarization is a machine learning optimization for limited resource devices that has
achieved significant results in edge applications. As microcontrollers are the mainstream …

Buildings and a lot of other such construction elements include steel as the main part. The
quality of the steel is often overlooked. This may lead to fatal consequences when prolonged …

Abstract k-Nearest Neighbors (k-NN) is one of the most widely used classification algorithms
in real-world machine learning applications such as computer vision, speech recognition …

Abstract The k-Nearest Neighbors (kNN) algorithm is a fundamental machine learning
classification technique with wide-ranging applications. Among various kNN implementation …

Shared memory heterogeneous systems are now mainstream, with nearly every mobile
phone and tablet containing integrated processing units. However, developing applications …