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Molecular simulation is an extremely useful, but computationally very expensive tool for studies of chemical and biomolecular systems. Here, we present a new implementation of our molecular simulation toolkit GROMACS whi...

From the Publisher: The updated new edition of the classic Introduction to Algorithms is intended primarily for use in undergraduate or graduate courses in algorithms or data structures. Like the first edition,this text ...

There are now a wide variety of packages for electronic structure calculations, each of which differs in the algorithms implemented and the output format. Many computational chemistry algorithms are only available to use...

Now in its second edition, Nursing Facts Made Incredibly Quick! is the point-of-care reference that every nurse in every specialty needs. This pocket-sized book of clinical tools provides instant access to information th...

Operations Research, Management Science or Business Analytics is a technology that helps improve business decision making. This book is focused on linear, integer, nonlinear and multiobjective programming, as well as mul...

Globalization and new technologies with their breakneck competitiveness and speed of doing business have driven the development of e-commerce, changing the way products are sold and bought today. The new digital era in w...

What is the predictive accuracy and effectiveness of algorithms designed for crime prevention purposes? Are they sufficiently transparent? Are there any inherent biases? This report presents an analysis of three algorith...

Social networking sites have enabled a high connectedness leading to unprecedented interactive dynamics. Social workers are using these digital means and are generating communities of practice through which they cooperat...

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 ...

Direction of arrival (DoA) estimation is a key research focus in array signal processing, and numerous progressive direction-finding algorithms have already been developed. In terms of the development of algorithms, meta...

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....

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...

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...

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...

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...

The ripening stage of a fruit is a crucial determinant of its quality. Traditional assessment methods for fruit ripeness are often subjective, error-prone, and time-consuming. Therefore, numerous attempts are being made ...

In this paper, the three-stage two-dimensional rectangular strip packing problem is tackled using genetic algorithms. A new problem dependent recombination operator, called best inherited levels recombination (BIL), is i...

Our interest is to define evolutionary algorithms to solve Constraint Satisfaction Problems (CSP), which indlude benefits of taditional resolution methods of CSPs as well as inherent characteristics of these kind of prob...

This paper presents a neuro-fuzzy network where all its parameters can be tuned simultaneously using Genetic Algorithms. The approach combines the merits of fuzzy logic theory, neural networks and genetic algorithms. The...

Metaheuristics are used as very good optimization methods and they imitate natural, biologic, social and cultural process. In this work, we evaluate and compare three different metaheuristics which are population-based: ...

Historically Functional Programming FP for short has been associated with a small scope of applications mainly academic The computer science community did not pay enough attention to its potential perhaps due t...

Recently, novel learning algorithms such as Support Vector Regression (SVR) and Neural Networks (NN) have received increasing attention in forecasting and time series prediction, offering attractive theoretical propertie...