A two-phase mathematical-programming heuristic for flexible assignment of activities and tasks to work shifts

In the service industry, workers perform work shifts and are assigned to interruptible activities and uninterruptible tasks during their shifts. The work shifts of regular employees are often established several weeks in advance of the operations when the activity and task demands are still uncertain. Just a few days before the operations when these demands are unveiled with more certainty, the planned schedules can be slightly modified and on-call temporary employees can be scheduled to satisfy the demands as best as possible. As acceptable modifications, extending the planned shifts and moving workers’ meal breaks are considered. In this paper, we are interested in the scheduling problem encountered in this second step, which also involves assigning activities and tasks to the scheduled work shifts. To produce good-quality solutions in fast computational times for large-sized instances, we develop a two-phase heuristic. In the first phase, an approximate mixed-integer programming model is used to suggest temporary shifts and extensions to regular shifts and to schedule and assign tasks. In the second phase, a column-generation heuristic embedded in a rolling horizon procedure determines the final shifts and assigns activities to them. Computational results obtained on randomly generated instances are reported to evaluate the validity of the proposed solution method.     

A constrained optimization approach for an adaptive generalized subspace tracking algorithm

In this paper, we present an orthonormal version of the generalized signal subspace tracking. It is based on an interpretation of the generalized signal subspace as the solution of a constrained minimization task. This algorithm, referred to as the CGST algorithm, guarantees the C_x-orthonormality of the estimated generalized signal subspace basis at each iteration which C_x denotes the correlation matrix of the sequence x(t). An efficient implementation of the proposed algorithm enhances applicability of it in real time applications.     

A learning-based visual saliency prediction model for stereoscopic 3D video (LBVS-3D)

Saliency prediction models provide a probabilistic map of relative likelihood of an image or video region to attract the attention of the human visual system. Over the past decade, many computational saliency prediction models have been proposed for 2D images and videos. Considering that the human visual system has evolved in a natural 3D environment, it is only natural to want to design visual attention models for 3D content. Existing monocular saliency models are not able to accurately predict the attentive regions when applied to 3D image/video content, as they do not incorporate depth information. This paper explores stereoscopic video saliency prediction by exploiting both low-level attributes such as brightness, color, texture, orientation, motion, and depth, as well as high-level cues such as face, person, vehicle, animal, text, and horizon. Our model starts with a rough segmentation and quantifies several intuitive observations such as the effects of visual discomfort level, depth abruptness, motion acceleration, elements of surprise, size and compactness of the salient regions, and emphasizing only a few salient objects in a scene. A new fovea-based model of spatial distance between the image regions is adopted for considering local and global feature calculations. To efficiently fuse the conspicuity maps generated by our method to one single saliency map that is highly correlated with the eye-fixation data, a random forest based algorithm is utilized. The performance of the proposed saliency model is evaluated against the results of an eye-tracking experiment, which involved 24 subjects and an in-house database of 61 captured stereoscopic videos. Our stereo video database as well as the eye-tracking data are publicly available along with this paper. Experiment results show that the proposed saliency prediction method achieves competitive performance compared to the state-of-the-art approaches.

     

Physicochemical properties of cross-linked-annealed wheat starch

Starch in its native form, may not be able to provide functional properties such as high or low temperatures and shear forces bearings expected in modern industries. Therefore, it is usually modified to make it compatible for different applications. The main aim of this research was to study the effects of dual modification using cross-linking and annealing on physicochemical properties of wheat starch. Therefore, starch was first cross-linked using different levels of POCl₃ (0, 0.1, 0.2, 0.4?%, w/w, starch basis) and then annealed at 40?°C for 72?h. Scanning electron micrographs showed the presence of some spots on the granules of the dual-modified samples. The results of differential scanning calorimetry showed that the onset, peak and conclusion temperatures and enthalpy increased upon dual modification. The X-ray diffraction pattern of the modified samples remained unchanged while water solubility and swelling decreased. The results of rapid visco analyzing showed lower peak, setback, breakdown and final viscosities for the dual-modified samples. These samples produced stronger gels as determined using a texture analyzer. In total, annealing of the cross-linked starch could enhance some of its functional properties for further applications.     

Comparison of Canola and Soy Flour with Added Isocyanate as Wood Adhesives

Canola is widely grown in the northern latitudes for its vegetable oil, generating large quantities of residual, low value canola flour used as animal feed. The common wood adhesive poly(diphenylmethylene diisocyanate) (pMDI) should react with the wide variety of functional groups in proteins. Therefore, it would seem that canola flour with added pMDI could be an effective adhesive. Two main questions are addressed in this study: How do the wood adhesive properties of canola flour compare to the better-studied soy flour? How well do proteins, which contain an abundance of functional groups, cure with the very reactive pMDI? These questions were addressed using the small-scale adhesive strength test ASTM D-7998, with various adhesive formulations and bonding conditions for canola flour plus pMDI compared to soy adhesives. The more challenging wet cohesive bond strength was emphasized because the dry strengths were usually very good. Generally, soy adhesives were better than canola ones, as was the polyamidoamine-epichlorohydrin cross-linker compared to pMDI, but these generalizations can be altered by the conditions selected. Three-ply plywood tests supported the small-scale test results.     

Fabrication of oriented electrospun cellulose nanocrystals–polystyrene composite fibers on a rotating drum

Nitrobenzene (CNC-1), trifluoromethyl benzene (CNC-2) modified and polystyrene-grafted (CNC-g) cellulose nanocrystals in polystyrene (PS)-N,N dimethylformamide (DMF) solutions were electrospun and collected as stretched and aligned fibers on a rotating drum. Scanning electron microscope pictures showed significant alignment in the case of unmodified and nitrobenzene-modified CNC-1/PS nanocomposite fibers once the linear speed of rotor reached to 15 m s⁻¹. Fiber diameter decrease was more strong with rotor speed increase in the case of trifluoromethyl benzene modified (CNC-2) and polystyrene-grafted (CNC-g) cellulose nanocrystals/PS systems. Dynamic mechanical analysis including storage and elastic modulus of electrospun-oriented fibers were performed on surface-modified and polymer-grafted CNC/PS samples. According to α transition peak, the increase in the glass-transition temperature with filler concentration was the highest in polymer-grafted CNC-g/PS composite fibers. It was due to the interpenetration of grafted polymer brushes and free polymer chains in continuous phase and resulted in restrictions of motions of polymer chains in the PS matrix. The elastic moduli of nitrobenzene (CNC-1) and trifluoromethyl benzene (CNC-2)-modified CNC-filled PS composite fibers agreed well with percolation model, which indicates the CNC–CNC interactions and network formation with an increase in concentration. Magnitude of the elastic modulus of polymer grafted CNC-g at 0.33 vol % in PS was significantly higher than the prediction from percolation theory. It was due the immobilized polymer chains around CNC-g particles. However, grafted polymer chains, at higher CNC concentrations acted like stickers among CNC particles and caused CNC agglomerates with entrapped free polystyrene from the matrix, thus caused a decrease in the elastic modulus. © 2020 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2020 , 137, 48942.     

Nafion/histidine functionalized carbon nanotube: High-performance fuel cell membranes

Here we show preparation and characterization of a new type of composite membrane based on Nafion^®/histidine modified carbon nanotube by imidazole groups (Im-CNT), for direct methanol fuel cell (DMFC) applications. Due to the presence of this imidazole-based amino acid on the surface of CNT, new electrostatic interactions can be formed in the interface of Nafion^® and Im-CNT. Physical characteristics of these nanocomposite membranes are investigated by water uptake, methanol permeability, ion exchange capacity, proton conductivity, as well as fuel cell performance results.     

Decision support in pre-hospital stroke care operations: A case of using simulation to improve eligibility of acute stroke patients for thrombolysis treatment

Stroke is the third most common cause of death and the sixth most common cause of disability worldwide. Treating acute ischemic stroke with thrombolytic therapy within 4.5 hours from symptom onset is effective in improving patient outcomes. The time from stroke onset to arrival to hospital has been identified as the single most important issue in determining patients' eligibility for stroke thrombolysis. There is a need for simultaneous systemic evaluation of multi-factorial interventions in pre-hospital acute care systems, aimed at increasing patients' eligibility for stroke thrombolysis. In this paper an OR solution is proposed in the form of a simulation model that provides clear measure of the relative benefit of alternative potential interventions, demonstrating how OR modeling can be used for providing decision support in pre-hospital stroke care operations and contributing to health OR literature.