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This book presents the fundamentals of discrete-time signals, systems, algorithms and applications for students in electrical engineering or computer science. It covers both time-domain and frequency- domain methods for ...

In several applications, the trajectory of an entity, a feature or an object has to be tracked over a sequence of image frames. When the processing is to be performed in real time, there are important constraints leading...

This work presents a systematic literature review on the application of Machine Learning algorithms in the development of effective movie recommender systems. With the increasing popularity of movie recommender systems i...

The book intends to address the important aspects of high-performance signal processing with a focus on the recent development of VLSI technology for signal processing. The editors collect much of all the research effor...

Forecasting vaccine demand and determining inventory policies are critical challenges in healthcare supply chains, where uncertainty poses significant operational risks. This study proposes a two-step data-driven framewo...

Abstract Background Optimization of biotechnological processes is traditionally limited by time-consuming trial-and-error approaches and the complexity of simultaneously optimizing multiple, often conflicting objectives....

Algorithms pose interesting challenges to competition law, particularly discussing which practices involving this fast-paced technologies may or should be caught under Article 101 of the Treaty on the Functioning of the ...

Abstract An increasing number of researchers have researched fixture layout optimization for thin-walled part assembly during the past decades. However, few papers systematically review these researches. By analyzing exi...

Abstract This study introduces two recently developed bio-inspired metaheuristic algorithms, Artificial Protozoa Optimizer (APO, 2024) and Dung Beetle Optimizer (DBO, 2023), into long short-term memory (LSTM) networks fo...

We present results from a data challenge posed to the radial velocity (RV) community: Namely, to quantify the Bayesian "evidence"for n = {0, 1, 2, 3} planets in a set of synthetically generated RV data sets containing a ...

Abstract The main purpose of this research is the survey of the development Block parallel numerical algorithms for solute stiff ordinary differential equations which are suitable for running on MIMD (Multiple instructi...

The clustering of small molecules implies the organization of a group of chemical structures into smaller subgroups with similar features. Clustering has important applications to sample chemical datasets or libraries in...

Deep learning offers a novel opportunity to achieve both high-quality and high-speed computer-generated holography (CGH). Current data-driven deep learning algorithms face the challenge that the labeled training datasets...

Three-phase pulse width modulation (PWM) rectifiers are crucial in industrial, civil, and transportation applications. Due to the diversity of grid loads, the three-phase input voltage may be unbalanced, which consequent...

Artificial pancreas (AP) algorithms can be divided into single-hormone (SH) and dual-hormone (DH). SH algorithms regulate glycemia using insulin as their control input. On the other hand, DH algorithms also use glucagon ...

Abstract Computational efficiency and accuracy always conflict with each other in molecular dynamics (MD) simulations. How to enhance the computational efficiency and keep accuracy at the same time is concerned by each c...

On-demand ride services or ride-sourcing services have been experiencing fast development and steadily reshaping the way people travel in the past decade. Various optimization algorithms, including reinforcement learning...

AimsUnderstanding atypical forms of diabetes (AD) may advance precision medicine, but methods to identify such patients are needed. We propose an electronic health record (EHR)-based algorithmic approach to identify pati...

ABSTRACT Background and Aims De novo drug design is the process of generating novel lead compounds that possess desirable pharmacological activities and optimal physicochemical properties for therapeutic development. In ...

With the arrival of big-data society, methods for classifying real-world problems have attracted much attention for researchers and developers in various fields. In recent years, much effort has been devoted for improvin...

This paper proposes beam training algorithms for robust line-of-sight (LoS) multi-input and multi-output (MIMO) systems with subarray-based beamforming functionality at both the transmitter (TX) and receiver (RX). In gen...

Abstract Achieving accurate speed prediction provides the most critical support parameter for high-level energy management of plug-in hybrid electric vehicles. Nowadays, people often drive a vehicle on fixed routes in th...

BDA is an adaptation of Dragonfly Algorithm (DA) that optimizes computation for single-objective, discrete, and multi-objective problems. Combining BDA optimization algorithm with KNN and SVM classification algorithms ai...

Abstract The last decade witnessed a great evolution on the fields of computer science, artificial intelligence, communication and data transmission. This evolution draw the attention of specialists to design a modern cr...