A survey on the applications of variable neighborhood search algorithm in healthcare management

Annals of Mathematics and Artificial Intelligence - This paper reviews the papers on the applications of VNS in the health care area by analyzing the characteristics of VNS in different problems....     

Integrated inventory and production policy for manufacturing with perishable raw materials

Annals of Mathematics and Artificial Intelligence - This research investigates an integrated inventory and production scheduling problem (IIPSP) in a manufacturer that deals with the perishable...     

Surgical Tool Datasets for Machine Learning Research: A Survey

International Journal of Computer Vision - This paper is a comprehensive survey of datasets for surgical tool detection and related surgical data science and machine learning techniques and...     

Recent Progress in Photonic Processing of Metal‐Oxide Transistors

Over the past few decades, significant progress has been made in the field of photonic processing of electronic materials using a variety of light sources. Several of these technologies have now been exploited in conjunction with emerging electronic materials as alternatives to conventional high‐temperature thermal annealing, offering rapid manufacturing times and compatibility with temperature‐sensitive substrate materials among other potential advantages. Herein, recent advances in photonic processing paradigms of metal‐oxide thin‐film transistors (TFTs) are presented with particular emphasis on the use of various light source technologies for the photochemical and thermochemical conversion of precursor materials or postdeposition treatment of metal oxides and their application in thin‐film electronics. The pros and cons of the different technologies are discussed in light of recent developments and prospective research in the field of modern large‐area electronics is highlighted.     

Digital Image Processing Applied to Scintillation Images from Biomedical Systems

Several nonlinear filtering methods have been developed for two-dimensional image signals obtained from an Anger Scintillation camera. The first method termed "pruning" is implemented in the frequency domain and filters out certain components of the two-dimensional amplitude spectrum. The other methods called "E-filtering" and "P-filtering" utilize a nonlinear transformation of the spatial coordinates which is proportional to the two-dimensional signal amplitude and energy spectrum, respectively. These nonlinear filtering techniques have been applied to phantom scintigrams as well as brain and heart scans of normal and abnormal patients. In addition, the detection of boundaries using the hexagonal Golay transform on filtered and unfiltered images is included. Finally, these filtering and edge detection techniques were for the first time applied to a new technique for the detection of acute myocardial infarcts.     

Exploring the Leidenfrost Effect for the Deposition of High‐Quality In2O3 Layers via Spray Pyrolysis at Low Temperatures and Their Application in High Electron Mobility Transistors

The growth mechanism of indium oxide (In₂O₃) layers processed via spray pyrolysis of an aqueous precursor solution in the temperature range of 100–300 °C and the impact on their electron transporting properties are studied. Analysis of the droplet impingement sites on the substrate's surface as a function of its temperature reveals that Leidenfrost effect dominated boiling plays a crucial role in the growth of smooth, continuous, and highly crystalline In₂O₃ layers via a vapor phase‐like process. By careful optimization of the precursor formulation, deposition conditions, and choice of substrate, this effect is exploited and ultrathin and exceptionally smooth layers of In₂O₃ are grown over large area substrates at temperatures as low as 252 °C. Thin‐film transistors (TFTs) fabricated using these optimized In₂O₃ layers exhibit superior electron transport characteristics with the electron mobility reaching up to 40 cm² V^?1 s^?1, a value amongst the highest reported to date for solution‐processed In₂O₃ TFTs. The present work contributes enormously to the basic understanding of spray pyrolysis and highlights its tremendous potential for large‐volume manufacturing of high‐performance metal oxide thin‐film transistor electronics.     

Subspace based blind identification of LTI FIR MIMO systems and equalization of finite memory SIMO Volterra systems

In this paper a novel algorithm based on subspace projections is developed for the blind kernel identification of LTI FIR multiple input multiple output (MIMO) systems, as well as blind equalization of finite memory SIMO Volterra systems. In addition, for Volterra systems, the algorithm computes the memory lengths of the nonlinearities involved. Simulations in the context of blind channel equalization and identification demonstrate good performance in comparison to existing schemes.     

Head Up Games: combining the best of both worlds by merging traditional and digital play

Current pervasive games are mostly location-aware applications, played on handheld computing devices. Considering pervasive games for children, it is argued that the interaction paradigm existing games support limits essential aspects of outdoor play like spontaneous social interaction, physical movement, and rich face-to-face communication. We present a new genre of pervasive games conceived to address this problem, that we call “Head Up Games” (HUGs) to underline that they liberate players from facing down to attend to screen-based interactions. The article discusses characteristics of HUG and relates them to existing genres of pervasive games. We present lessons learned during the design and evaluation of three HUG and chart future challenges.     

Modelling and explicit model predictive control for PEM fuel cell systems

We present an analytical dynamic model and a general framework for the optima control design of a PEM fuel cell system. The mathematical model consists of a detailed model for the PEM fuel cell stack and simplified models for the compressor, humidifier and cooling system. The framework features (i) a detailed dynamic process model, (ii) a reduced order approximating model obtained by performing dynamic simulations of the system and (iii) the design of an explicit/multi-parametric model predictive controller. The derived explicit/multi-parametric controller is tested and validated off-line on several operating conditions.     

Optimal storage design for a multi-product plant: A non-convex MINLP formulation

We discuss a tank design problem for a multi product plant, in which the optimal cycle time and the optimal campaign size are unknown. A mixed-integer nonlinear programming (MINLP) formulation is presented, where non-convexities are due to the tank investment cost, storage cost, campaign setup cost and variable production rates. The objective of the optimization model is to minimize the sum of the production cost per ton per product produced. A continuous-time mathematical programming formulation is proposed and several extensions are discussed. The model is implemented in GAMS and computational results are reported for the two global MINLP solver BARON and LINDOGlobal as well as several nonlinear solvers available in GAMS.