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Abstract Unmanned Aerial Systems (UAS) have become increasingly integral to industries such as agriculture, surveillance, transportation, and entertainment, raising significant concerns about their vulnerability to cyber...

Abstract Feature selection is a critical step in machine learning, as it helps minimize redundant features, thereby enhancing model performance and interpretability. In practice, partially labeled datasets are common. Wh...

IntroductionThIntrusion Detection Systems (IDS) for Internet of Things (IoT) and edge environments require datasets with unambiguous labels, yet existing datasets often mix benign and malicious traffic within the same ca...

As Machine Learning Operations (MLOps) adoption accelerates, systematic integration of explainability is imperative for reliability, transparency, and continuous quality assurance. This paper presents a scoping review ex...

ABSTRACT As a government‐regulated public service, traffic signal control (TSC) requires reliable and transparent decision‐making. However, existing deep reinforcement learning (DRL) methods, despite improvements in ...

Abstract This study presents a Quantum-Enhanced Firefly Algorithm (QFA)-based multi-level image annotation framework that integrates advanced Otsu thresholding, region-based feature extraction, and Bayesian multi-label c...

BACKGROUND: There is a growing recognition of the value of synthesising qualitative research in the evidence base in order to facilitate effective and appropriate health care. In response to this, methods for undertaking...

W. R. Tobler, A Computer Movie Simulating Urban Growth in the Detroit Region, Economic Geography, Vol. 46, Supplement: Proceedings. International Geographical Union. Commission on Quantitative Methods (Jun., 1970), pp. 2...

A basic problem in computer vision is to understand the structure of a real world scene given several images of it. Techniques for solving this problem are taken from projective geometry and photogrammetry. Here, the aut...

Convolutional networks are at the core of most state of-the-art computer vision solutions for a wide variety of tasks. Since 2014 very deep convolutional networks started to become mainstream, yielding substantial gains ...

Computer vision applications have come to rely increasingly on superpixels in recent years, but it is not always clear what constitutes a good superpixel algorithm. In an effort to understand the benefits and drawbacks o...

This article provides researchers with a guide to properly construe and conduct analyses of conditional indirect effects, commonly known as moderated mediation effects. We disentangle conflicting definitions of moderated...

Non-biological experimental variation or "batch effects" are commonly observed across multiple batches of microarray experiments, often rendering the task of combining data from these batches difficult. The ability to co...

Business Research Methods contains new and revised chapters on quantitative methods and visual research, while cutting-edge material on inclusivity and bias in research, feminist perspectives, and decolonial and indigeno...

Collinearity refers to the non independence of predictor variables, usually in a regression‐type analysis. It is a common feature of any descriptive ecological data set and can be a problem for parameter estimation bec...

Preface 1. Background in linear algebra 2. Discretization of partial differential equations 3. Sparse matrices 4. Basic iterative methods 5. Projection methods 6. Krylov subspace methods Part I 7. Krylov subspace methods...

The purposes of this article are to position mixed methods research ( mixed research is a synonym) as the natural complement to traditional qualitative and quantitative research, to present pragmatism as offering an attr...

Prediction of species’ distributions is central to diverse applications in ecology, evolution and conservation science. There is increasing electronic access to vast sets of occurrence records in museums and herbaria, ...

This book is an applied introduction to the problems and solutions of modern computer vision. It offers a collection of selected, well-tested methods (theory and algorithms), aiming to balance difficulty and applicabilit...

"Brain Computer Interface (BCI) or Brain Machine Interfaces (BMI), has proved the feasibility of a distinct non-biological communication channel to transmit information from the Central Nervous System (CNS) to a computer...

The use of generic and generative methods for the development and application of interactive educational software is a relatively unexplored area in industry and education. Advantages of generic and generative techniques...

Phylogenies are extremely useful tools, not only for establishing genealogical relationships among a group of organisms or their parts (e.g. genes), but also for a variety of research once the phylogenies are estimated. ...

Fil: Brain, Robert M. Universidad de Columbia Británica; Canadá. El presente trabajo esboza una genealogía alternativa para dar cuenta del cambio epistemológico y técnico que supuso el pasaje de la energía a la inf...

SIR 97 is the integration of two programs, SIR 92 and CAOS , the first devoted to the solution of crystal structures by direct methods, the second to refinement via least-squares–Fourier procedures. Several new feature...