A stochastic optimization model for real-time ambulance redeployment

When ambulances are engaged in responding to emergency calls, the ability to respond quickly to future calls is considerably compromised. The available ambulances are typically relocated to reestablish maximal coverage. We present a two-stage stochastic optimization model for the ambulance redeployment problem that minimizes the number of relocations over a planning horizon while maintaining an acceptable service level. We conduct computational testing based on the real historical data from the Region of Waterloo Emergency Medical Services. The results show that the optimal relocation strategies can be computed within 40 s of computational time for a desired service level of 90%.     

Precision design aspects for friction actuation with error compensation

Some key aspects in the design of actuators for ultra precision systems will require particular attention as actuators have to comply with ultra precision positioning and related tight specifications. The actuation is an important sub-group within the overall system to be designed. Any design failure in this sub-group will degrade drastically the machine performance. An interface analysis with immediate surrounding sub-groups is important to secure better generation of motion. In this paper, a design procedure for an actuator dedicated to generate high precision motion is presented with a discussion of some important aspects encountered when designing a friction drive. The procedure encompasses design concepts, axis stiffness, control, system dynamics, and, error compensation using a dedicated control strategy compensating for errors. A case study is discussed.     

Self-tuning dynamic models of HVAC system components

A great majority of modern buildings are equipped with Energy Management and Control Systems (EMCS) which monitor and collect operating data from different components of heating ventilating and air conditioning (HVAC) systems. Models derived and tuned by using the collected data can be incorporated into the EMCS for online prediction of the system performance. To that end, HVAC component models with self-tuning parameters were developed and validated in this paper. The model parameters were tuned online by using a genetic algorithm which minimizes the error between measured and estimated performance data. The developed models included: a zone temperature model, return air enthalpy/humidity and CO₂ concentration models, a cooling and heating coil model, and a fan model. The study also includes tools for estimating the thermal and ventilation loads. The models were validated against real data gathered from an existing HVAC system. The validation results show that the component models augmented with an online parameter tuner, significantly improved the accuracy of predicted outputs. The use of such models offers several advantages such as designing better real-time control, optimization of overall system performance, and online fault detection.     

Design of survivable WDM networks using pre-configured protection structures with unrestricted shapes

We propose a novel protection approach for the design of link-protection schemes in survivable Wavelength Division Multiplexing mesh networks by merging the well-known p-cycle- and p-tree-protection structures. So doing, we aim at gathering the advantages of p-cycles in terms of protection capabilities, and of p-trees in terms of protection flexibilities (local re-routing, scalability) in a single protection scheme. As opposed to existing protection schemes based on protection structures with a pre-defined shape, the building blocks of the new scheme are protection structures with unrestricted shapes. Thus, they allow more flexibility in provisioning spare capacity, and provide higher capacity efficiency when compared to the shaped-protection schemes that have been proposed so far. In order to cope with the size of the solution space which includes all the possible protection structures, we propose an efficient and scalable optimization technique in large-scale systems named column generation (CG). In our CG-based optimization approach, the shape of a candidate protection structure is dynamically decided during the optimization process according to a link spare capacity budget. Experimental results on different network instances show that the protection plan resulting from the merging of p-cycle and p-tree structures is, on average, ~15% less capacity redundant and ~15% more reliable than the pure p-cycle one. It also requires, on average, ~30% less protection structures. In addition, those structures provide backup paths ~30% smaller than those of the p-cycle-based scheme.     

An Expeditious Copper‐Catalyzed Access to 3‐Aminoquinolinones, 3‐Aminocoumarins and Anilines using Sodium Azide

An efficient copper‐catalyzed in situ C(sp²) NH₂ bond formation to provide a range of 3‐aminoquinolin‐2(1H)‐ones and 3‐aminocoumarins from 3‐bromoquinolinones and 3‐bromocoumarins, respectively, has been achieved. The reaction conditions involve the use of copper powder as the catalyst, eco‐friendly ethanol as the solvent in the presence of pipecolinic acid as the ligand and ascorbic acid as the additive. The efficiency of this practical method was demonstrated in the synthesis of various anilines.     

Bayesian prediction for business mortality analysis

Summary This paper is concerned with business mortality analysis in a Bayesian setting. We assume that a businessman startsN businesses at different points of time and at a certain epoch referred to as the ‘present’, the failure times of the failed businesses and the survival times of the still surviving businesses are recorded. Bayesian prediction for business mortality or survival up to a future time pointt ₀ is made under the assumptions of a Weibull business survival distribution (WBSD) and the squared error loss function (SELF). The results are extended to the situation where one of the observed times of business failure may possibly be an outlier.     

Lactic acid fermentation of anthocyanin-rich sweet potato (Ipomoea batatas L.) into lacto-juice

Sweet potato (SP) is an important root crop grown all over the world and consumed as a vegetable, boiled, baked or often fermented into food and beverages. The grated SP roots [non- boiled and fully boiled (boiled in water at 100 °C for 15 min) were treated with 0.05% of commercial pectinase enzyme (Pectinex, Novoenzyme) in order to extract the juice. The fresh juice was inoculated with Lactobacillus plantarum MTCC 1407 culture at 28 ± 2 °C for 48 h to produce lacto-juice (LJ). The anova analysis of analytical data revealed that there was significant effect of boiling conditions (fully boiled and non-boiled) on pH [ F (1, 4) = 220.5, P  < 0.001), TA [ F (1, 4) = 78.89, P  < 0.01], starch [ F (1, 4) = 26.63, P  < 0.01), total sugar [ F (1, 4) = 61.36, P  < 0.01) and anthocyanin [ F (1, 4) = 32.86, P  < 0.01) but not on reducing sugar [ F (1, 4) = 2.48, P  = 0.19). Sensory evaluation rated the SP LJ acceptable based on texture, taste, aroma, flavour and after taste. LJ prepared from fully boiled roots with 10% cane sugar was most preferred by a consumer's panelist based on Linear Discriminant Analysis. Principal component analyses (PCA) reduced the seven original analytical variables to three independent components (factors), which accounted for 99.9% of the total variations. Similarly, six original sensory variables were reduced to two independent components, which accounted for 65.7% of the total variations.     

Principles for microwave moisture and density measurement in grain and seed.

The importance of cereal grain moisture content in determining time of harvest and in preserving grain quality is described. Techniques for moisture measurement, including electronic moisture meters, are also discussed briefly, and the need for better moisture sensing techniques for modern agricultural on-line moisture monitoring is described. Principles of microwave free-space measurements involving attenuation and phase-shift determination are explained, and density-independent functions of the grain permittivity are presented that permit reliable moisture sensing applicable to moving grain in which bulk density variation occurs. Three different approaches are discussed for determining moisture content and bulk density of grain from microwave measurement of the dielectric properties. A new moisture calibration function, based on complex-plane plots of dielectric constant and loss factor, each divided by bulk density, is described, which promises a universal calibration for different types of grain and seed. This important advantage should encourage commercial development for practical use.     

Cellulose nanocrystals reinforced poly(oxyethylene)

Nanocomposite materials were prepared from poly(oxyethylene) (POE) as the matrix and a stable aqueous suspension of cellulose nanocrystals extracted from tunicate as the reinforcing phase. After dissolving POE in water and mixing with the cellulose nanocrystals suspension, solid films were obtained by casting and evaporating the preparations. Resulting films were characterized using scanning electron microscopy, differential scanning calorimetry, thermogravimetric analysis and dynamic mechanical analysis. Favorable interactions between cellulose and POE were evidenced and assumed to be partially responsible for a decrease of the crystallinity of the matrix. A thermal stabilization of the nanocomposites for temperatures higher than the melting temperature of POE was reported and ascribed to the formation of a rigid cellulosic network within the matrix assumed to be governed by a percolation effect. The formation of this percolating network was not altered by the matrix crystallization process and filler/POE interactions.