Staffing & Scheduling

Machine-Learning-Based Analysis in Genome-Edited Cells Reveals the Efficiency of Clathrin-Mediated Endocytosis.

Cells internalize various molecules through clathrin-mediated endocytosis (CME). Previous live-cell imaging studies suggested that CME is inefficient, with about half of the events terminated. These CME efficiency estimates may have been confounded by overexpression of fluorescently tagged proteins and inability to filter out false CME sites. Here, we employed genome editing and machine learning t...

A Neurodynamic Approach for Real-Time Scheduling via Maximizing Piecewise Linear Utility.

In this paper, we study a set of real-time scheduling problems whose objectives can be expressed as piecewise linear utility functions. This model has very wide applications in scheduling-related problems, such as mixed criticality, response time minimization, and tardiness analysis. Approximation schemes and matrix vectorization techniques are applied to transform scheduling problems into linear ...

How to build up the actionable knowledge base: the role of 'best fit' framework synthesis for studies of improvement in healthcare.

Increasing recognition of the role and value of theory in improvement work in healthcare offers the prospect of capitalising upon, and consolidating, ...

An Effective and Novel Neural Network Ensemble for Shift Pattern Detection in Control Charts.

Pattern recognition in control charts is critical to make a balance between discovering faults as early as possible and reducing the number of false a...

Sample Selection for Training Cascade Detectors.

Automatic detection systems usually require large and representative training datasets in order to obtain good detection and false positive rates. Tra...

Near-Bayesian Support Vector Machines for imbalanced data classification with equal or unequal misclassification costs.

Support Vector Machines (SVMs) form a family of popular classifier algorithms originally developed to solve two-class classification problems. However...

Prediction of hydrogen and carbon chemical shifts from RNA using database mining and support vector regression.

The Biological Magnetic Resonance Data Bank (BMRB) contains NMR chemical shift depositions for over 200 RNAs and RNA-containing complexes. We have ana...

Once-per-step control of ankle-foot prosthesis push-off work reduces effort associated with balance during walking.

BACKGROUND: Individuals with below-knee amputation have more difficulty balancing during walking, yet few studies have explored balance enhancement th...

Effects of Innovative WALKBOT Robotic-Assisted Locomotor Training on Balance and Gait Recovery in Hemiparetic Stroke: A Prospective, Randomized, Experimenter Blinded Case Control Study With a Four-Week Follow-Up.

The present clinical investigation was to ascertain whether the effects of WALKBOT-assisted locomotor training (WLT) on balance, gait, and motor recov...

Artificial neural network modelling of pharmaceutical residue retention times in wastewater extracts using gradient liquid chromatography-high resolution mass spectrometry data.

The modelling and prediction of reversed-phase chromatographic retention time (tR) under gradient elution conditions for 166 pharmaceuticals in wastew...

An integrated Taguchi and response surface methodological approach for the optimization of an HPLC method to determine glimepiride in a supersaturatable self-nanoemulsifying formulation.

We studied the application of Taguchi orthogonal array (TOA) design during the development of an isocratic stability indicating HPLC method for glimep...

Robotic-assisted gait training in neurological patients: who may benefit?

Regaining one's ability to walk is of great importance for neurological patients and is a major goal of all rehabilitation programs. Gait training of ...

Effects of robotically modulating kinematic variability on motor skill learning and motivation.

It is unclear how the variability of kinematic errors experienced during motor training affects skill retention and motivation. We used force fields p...

Prediction of HPLC retention times of tebipenem pivoxyl and its degradation products in solid state by applying adaptive artificial neural network with recursive features elimination.

A sensitive and fast HPLC method using ultraviolet diode-array detector (DAD)/electrospray ionization tandem mass spectrometry (Q-TOF-MS/MS) was devel...

A novel tracking algorithm via feature points matching.

Visual target tracking is a primary task in many computer vision applications and has been widely studied in recent years. Among all the tracking meth...

Decomposition of surface EMG signals from cyclic dynamic contractions.

Over the past 3 decades, various algorithms used to decompose the electromyographic (EMG) signal into its constituent motor unit action potentials (MU...

Prediction and quantifying parameter importance in simultaneous anaerobic sulfide and nitrate removal process using artificial neural network.

The present investigation deals with the prediction of the performance of simultaneous anaerobic sulfide and nitrate removal in an upflow anaerobic sl...

Hyper-heuristic Evolution of Dispatching Rules: A Comparison of Rule Representations.

Dispatching rules are frequently used for real-time, online scheduling in complex manufacturing systems. Design of such rules is usually done by exper...

Design and control of the MINDWALKER exoskeleton.

Powered exoskeletons can empower paraplegics to stand and walk. Actively controlled hip ab/adduction (HAA) is needed for weight shift and for lateral ...

Assist-as-Needed Robot-Aided Gait Training Improves Walking Function in Individuals Following Stroke.

A novel robot-aided assist-as-needed gait training paradigm has been developed recently. This paradigm encourages subjects' active participation durin...