The mean size and percentage of budded cells of a wild-type haploid strain of Saccharomyces cerevisiae grown in batch culture over a wide range of doubling times (tau) have been measured using microscopic measurements and a particle size analyzer. Mean size increased over a 2.5-fold range with increasing growth rate (from tau = 450 min to tau = 75 min). Mean size is principally a function of gr...

This paper presents a method to recognize polygonal-shaped particles (i.e. rectangles, regular/irregular prisms) among agglomerated crystals from in-situ images during a crystallization process. The aim is to measure the particle size distributions (PSD); a key measurement needed for monitoring and controlling industrial crystallization operations . The method is first based on detecting the ge...

A single-server queueing model with infinite buffer and batch arrival of customers is considered. In contrast to the standard batch arrival when a whole batch arrives into the system at one epoch, we assume that the customers of an accepted batch arrive one by one in exponentially distributed times. Service time is exponentially distributed. Flow of batches is the stationary Poisson arrival pro...

The capability index Cpk for a process, that produces parts with normally distributed characteristic X , is defined as Cpk = min(U −μ, μ−L)/(3σ) = (T − |μ− ν|)/(3σ), where U and L are upper and lower specification limits for X , μ and σ are process mean and standard deviation, and ν = (U + L)/2, T = (U − L)/2. Using a sample X1, . . . , Xn of independent observations from N (μ, σ) Chou et al. (...

Processes of a real world manufacturer involve a number of batch-processing operations. Generally, these operations require the decision on batch sizes of products and there is no specific rule to set batch sizes of all products simultaneously so that the sum of the weighted expected cycle times of all products is minimized. The weights represent different levels of importance for products. In ...

We propose Batch-Expansion Training (BET), a framework for running a batch optimizer on a gradually expanding dataset. As opposed to stochastic approaches, batches do not need to be resampled i.i.d. at every iteration, thus making BET more resource efficient in a distributed setting, and when disk-access is constrained. Moreover, BET can be easily paired with most batch optimizers, does not req...

The overhead of processing fine-grain tasks on a grid induces the need for batch processing or task group deployment in order to minimise overall application turnaround time. When deciding the granularity of a batch, the processing requirements of each task should be considered as well as the utilisation constraints of the interconnecting network and the designated resources. However, the dynam...

The use of batch means is a well known technique for estimating the variance of point estimators computed from simulation experiments. The batch means variance estimator is simply the (appropriately scaled) sample variance of the estimator computed on subsets of consecutive observations. For the method to be practical, a good choice of batch length is necessary. We propose a method to estimate ...

It is common practice to decay the learning rate. Here we show one can usually obtain the same learning curve on both training and test sets by instead increasing the batch size during training. This procedure is successful for stochastic gradient descent (SGD), SGD with momentum, Nesterov momentum, and Adam. It reaches equivalent test accuracies after the same number of training epochs, but wi...