Equivalent Formulations of Inventory Control Problems

A general multi-item periodic-review inventory control problem is formulated in several ways, each reflecting a different point of view of the decision maker. These formulations are evaluated with respect to implementation criteria of: (i) technical difficulty in obtaining an optimal solution from the model, (ii) estimation effort required to find the values of the parameters in the model, (iii) effort needed to maintain the model continuously updated during the inventory management process. The most promising one is then compared with the conventional formulation, where the objective function is expressed as the sum of expected inventory holding and shortage costs. It is shown that both formulations lead to the same optimal solution under a certain budgetary constraint. This result offers an instrument for implementation improvements in inventory control systems.     

Multi-Item Inventory Management with Monetary Objective Function

This paper summarizes an actual multi-item periodic-review inventory control study where the “order-up-to-S” policy is employed. The objective function is expressed in monetary terms and is optimized subject to a budgetary limit on the maximum amount of money that can be tied up in inventories. The optimal solution is obtained by employing the generalized Lagrange multipliers method. Findings indicate that it is possible to decrease by at least 37.5% the amount of money currently invested in inventories while maintaining an 85-90% service level to customers. In this study a considerable amount of effort is also spent on the estimation of cost parameters, especially the shortage cost.     

Action research contextualizes DEA in a multi-organizational decision-making process

The theory of participatory action research (PAR) grew out of the practice of problem-solving in groups and organization by involving the participation of all pertinent stakeholders in decision-making process through empowerment. The ontological assumption is that “the world out there” is defined by the participating stakeholders as they understand and perceive it. The actionable knowledge thus produced is mostly used subjectively in the hope of a favorable organizational change or a transformation for betterment. On the other hand, Management Science/Operations Research (MS/OR) is more concerned with epistemological objectivity in identifying and defining managerial issues and finding solutions. In this paper we shall show that MS/OR can benefit from and contribute to PAR in complex decision making contexts. This kind of mutual benefit will be illustrated through a study reported in the area of R&D planning. It will be shown that PAR “contextualizes” problem structuring whereas MS/OR “optimizes” the consensual decision-making process in a multi-organizational context.     

Thresholds based outlier detection approach for mining class outliers: An empirical case study on software measurement datasets

Predicting the fault-proneness labels of software program modules is an emerging software quality assurance activity and the quality of datasets collected from previous software version affects the performance of fault prediction models. In this paper, we propose an outlier detection approach using metrics thresholds and class labels to identify class outliers. We evaluate our approach on public NASA datasets from PROMISE repository. Experiments reveal that this novel outlier detection method improves the performance of robust software fault prediction models based on Naive Bayes and Random Forests machine learning algorithms.     

Scanning hall probe microscopy (SHPM) using quartz crystal AFM feedback

Scanning Hall Probe Microscopy (SHPM) is a quantitative and non-invasive technique for imaging localized surface magnetic field fluctuations such as ferromagnetic domains with high spatial and magnetic field resolution of approximately 50 nm and 7 mG/Hz(1/2) at room temperature. In the SHPM technique, scanning tunneling microscope (STM) or atomic force microscope (AFM) feedback is used to keep the Hall sensor in close proximity of the sample surface. However, STM tracking SHPM requires conductive samples; therefore the insulating substrates have to be coated with a thin layer of gold. This constraint can be eliminated with the AFM feedback using sophisticated Hall probes that are integrated with AFM cantilevers. However it is very difficult to micro fabricate these sensors. In this work, we have eliminated the difficulty in the cantilever-Hall probe integration process, just by gluing a Hall Probe chip to a quartz crystal tuning fork force sensor. The Hall sensor chip is simply glued at the end of a 32.768 kHz or 100 kHz Quartz crystal, which is used as force sensor. An LT-SHPM system is used to scan the samples. The sensor assembly is dithered at the resonance frequency using a digital Phase Locked Loop circuit and frequency shifts are used for AFM tracking. SHPM electronics is modified to detect AFM topography and the frequency shift, along with the magnetic field image. Magnetic domains and topography of an Iron Garnet thin film crystal, NdFeB demagnetised magnet and hard disk samples are presented at room temperature. The performance is found to be comparable with the SHPM using STM feedback.     

Effect of different fillers on physical,mechanical, and optical properties of styrenic‐based thermoplastic elastomers

The effects of different fillers on physical, mechanical, and optical properties of styrenic‐based thermoplastic elastomers were investigated by experimental study. Poly[styrene‐b‐(ethylene‐co‐butylene)‐b‐styrene] block copolymer (SEBS)‐based thermoplastic elastomer composites were prepared in a co‐rotating intermeshing twin‐screw extruder, using silica and calcite as filler materials with three different particle sizes. The loading ratios in the composites were varied. Hardness, density, tensile strength, tear strength, compression set, wear resistance, transmittance, and haze measurements were performed. Thermal properties and morphological structure were investigated by differential scanning calorimeter (DSC) and scanning electron microscopy (SEM), respectively. The results show that, an interaction between silica and the polymer matrix exists, whereas calcite does not show any interaction with the polymer. Therefore, it is concluded that, calcium carbonate can be used in the composite as filler for cost efficiency, whereas silica can be used as reinforcing material in SEBS‐based thermoplastic elastomer composites, when optical properties are also concerned. POLYM. ENG. SCI., 2010. © 2009 Society of Plastics Engineers     

Hydroxyapatite/Bioactive Glass Films Produced by a Sol–Gel Method: In Vitro Behavior

Hydroxyapatite (HA) and HA/bioactive glass (49S) films were deposited on Si(100) substrates by a sol–gel dip‐coating method. The microstructure and in vitro bioactivity of the films were investigated by scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), and X‐ray photoelectron spectroscopy (XPS). Polycrystalline HA and amorphous bioactive glass films were obtained after annealing at 600 and 400 °C, respectively. The crystallization temperature of HA was determined to be around 568 °C. The surfaces of the HA films were covered with an apatite layer consists of spherulites formed by nanosized needle‐like aggregates after the soaking in simulated body fluid (SBF) for 10 days, while amorphous HA/bioactive glass surface was covered with larger spherical crystallites. Both XPS and EDS results obtained from HA/bioactive glass film, after soaking in SBF, showed increasing P amounts on the surface at the expense of Si. The higher density of the newly formed layer on HA/bioactive glass surface than that of the HA surface after 10 days of soaking was evidence of increased reaction rate and apatite forming ability when bioactive glass layer is present on the HA films.     

Physical properties and cure characteristics of natural rubber/nanoclay composites with two different compatibilizers

The effects of epoxidized natural rubber (ENR) and maleic anhydride‐grafted polybutadiene (PB‐g‐MA) as compatibilizers to rubber formulations with and without organo‐modified layered silicates are investigated. The physical properties and curing characteristics of composites are studied by moving die rheometer, rubber process analyzer, tensile, tear, and hardness testing. The state of organoclay intercalation was determined by X‐ray diffraction method. The addition of compatibilizers, especially ENR 50, results in further intercalation or exfoliation of the organoclay that increased the clay dispersion in the rubber matrix. ENR 50 with organo‐modified clay improves the physical properties and changes the curing profile. The addition of PB‐g‐MA without organoclay increases the tensile strength (σ_max) by increasing the stock viscosity of the rubber compound. Interestingly, simultaneous increase in hardness and σ_max is achieved in the presence of both compatibilizers, a characteristic that is difficult to achieve and sometimes required in rubber processing. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2011     

p(AAm/TA)‐based IPN hydrogel films with antimicrobial and antioxidant properties for biomedical applications

Interpenetrating polymer networks (IPN), either semi‐IPN (s‐IPN) or full IPN, based on a natural polymer tannic acid (TA) and synthetic poly(acrylamide) (p(AAm)) were prepared by incorporation of TA during p(AAm) hydrogel film preparation with and without crosslinking of TA simultaneously. The synthesis of p(AAm/TA) s‐IPN and IPN hydrogels with different amounts of TA were prepared by concurrent use of redox polymerization and epoxy crosslinking. The p(AAm)‐based hydrogels were completely degraded at 37.5°C within 9 and 2 days at pHs 7.4 and 9, respectively. Biocompatibility of p(AAm), s‐IPN, and IPN were tested with WST assay and double staining, they had 75% cell viability up to almost 20 μg mL^?1 concentration against L929 fibroblast cell. Antioxidant properties of IPN and s‐IPN hydrogels were investigated with FC and ABTS^? methods. Antimicrobial properties of TA‐containing s‐IPN, and IPN hydrogels were determined against three common bacterial strains, Escherichia coli ATCC 8739, Staphylococcus aureus ATCC 6538, and Bacillus subtilis ATCC 6633, and it was found that p(AAm/TA)‐based s‐IPN and IPN hydrogels are effective antimicrobial and antioxidant materials. Moreover, almost up to day‐long linear TA release profiles were obtained from IPN and s‐IPN hydrogels in phosphate buffer solution at pH 7.4 at 37.5°C. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 41876.     

Collaborative duty cycling strategies in energy harvesting sensor networks

Energy harvesting wireless sensor networks are a promising solution for low cost, long lasting civil monitoring applications. But management of energy consumption is a critical concern to ensure these systems provide maximal utility. Many common civil applications of these networks are fundamentally concerned with detecting and analyzing infrequently occurring events. To conserve energy in these situations, a subset of nodes in the network can assume active duty, listening for events of interest, while the remaining nodes enter low power sleep mode to conserve battery. However, judicious planning of the sequence of active node assignments is needed to ensure that as many nodes as possible can be reached upon the detection of an event, and that the system maintains capability in times of low energy harvesting capabilities. In this article, we propose a novel reinforcement learning (RL) agent, which acts as a centralized power manager for this system. We develop a comprehensive simulation environment to emulate the behavior of an energy harvesting sensor network, with consideration of spatially varying energy harvesting capabilities, and wireless connectivity. We then train the proposed RL agent to learn optimal node selection strategies through interaction with the simulation environment. The behavior and performance of these strategies are tested on real unseen solar energy data, to demonstrate the efficacy of the method. The deep RL agent is shown to outperform baseline approaches on both seen and unseen data.