We present the Distributed Batch Controller (DBC}, a system built to support batch processing of large scienti$c datasets. The DBC implements a federation of autonomous workstation pools, which may be widely distributed. Individual batch ,jobs are executed using idle workstations in these pools. Input data are staged to the pool before processing begins. We describe the architecture and impleme...

This paper describes our submission to the WMT 2017 Neural MT Training Task. We modified the provided NMT system in order to allow for interrupting and continuing the training of models. This allowed mid-training batch size decrementation and incrementation at variable rates. In addition to the models with variable batch size, we tried different setups with pre-trained word2vec embeddings. Asid...

A crucial step for batch process improvement and optimization is to develop information structures that streamline data gathering and, above all, are capable of integrating transactional data into a system using the analytical tools that are developed. Current trends in electronics, computer science, artificial intelligence and control system technology are providing technical capability that g...

In this article, an imperfect vendor–buyer inventory system with stochastic demand, process quality control and learning in production is investigated. It is assumed that there are learning in production and investment for process quality improvement at the vendor’s end, and lot-size dependent lead-time at the buyer’s end. The lead-time for the first batch and those for the rest of the batches ...

In the past, many researchers have analysed queueing models with batch service. In such models, the server typically postpones service until the number of present customers reaches a service threshold, whereupon service is initiated of a batch consisting of several customers. In addition, correlation in the customer arrival process has been studied for many different queueing models. However, c...

Based on the proportional-integral (PI) closed-loop control widely used in industrial engineering practice, a robust iterative learning control (ILC) method is proposed for industrial batch processes subject to time-varying uncertainties and load disturbance. An important merit is that the proposed ILC design is independent of the PI tuning which maintains the closed-loop system stability, owin...

This paper analyzes a finite-buffer queueing system, where customers arrive in batches and the accepted are served by single server. The service is assumed to be dependent on batch-size follows general bulk rule. inter-arrival times of correlated they represented through batch Markovian arrival process (BMAP). Computation procedure queue-length distributions at post-batch-service completion, an...

the main objective of this study was to investigate the effi ciency of biological treatmentof azo dye-containing wastewater with a sequencing batch reactor system, followed by ultrafi ltration.the performance of the system was quantifi ed by measuring the chemical oxygen demand and azo dyeconcentration. the biodegradation was carried out under combined alternating anaerobic and aerobiccondition...