As an indispensable component, Batch Normalization (BN) has successfully improved the training of deep neural networks (DNNs) with mini-batches, by normalizing the distribution of the internal representation for each hidden layer. However, the effectiveness of BN would diminish with scenario of micro-batch (e.g. less than 10 samples in a mini-batch), since the estimated statistics in a mini-bat...

Clinoptilolite was investigated for the removal of Cu(II) ions from industrial leachate. Adaptive neural fuzzy interface system (ANFIS) was used for modeling the batch experimental system and predicting the optimal input values, that is, initial pH, adsorbent dosage, and contact time. Experiments were studied under laboratory batch and fixed bed conditions. The outcomes of suggested ANFIS model...

We consider a problem of minimizing the number of batches of a fixed capacity processing the orders of various sizes on a finite set of items. This batch consolidation problem is motivated by the production system typical in raw material industries in which multiple items can be processed in the same batch if they share sufficiently close production parameters. If the number of items processed ...

While sophisticated systems for both process control and production planning enjoy a wide industrial acceptance, tools for batch process scheduling represent a serious gap in the fully automated batch plant. Despite over fifteen years of academic research in batch scheduling algorithms and Moore’s law increases in computing power, spreadsheets and calculators remain the state-of-the-art means f...

Most research concerning batch-service queueing systems has focussed on some specific aspect of the buffer content. Further, the customer delay has only been examined in the case of single arrivals. In this paper, we examine three facets of a threshold-based batch-service system with batch arrivals and general service times. First, we compute a fundamental formula from which an entire gamut of ...

counts; Second, the tunable transmitters not only generate downstream data traffic but also provide ONUs with optical Continuous Wave (CW) bursts for upstream transmissions. To provide efficient bidirectional transmissions between OLT and ONUs, we propose a batch scheduling algorithm based on the sequential scheduling algorithm previously studied. The key idea is to provide room for optimizatio...

We consider a problem of minimizing the number of batches of a fixed capacity processing the orders of various sizes on a finite set of items. This batch consolidation problem is motivated by the production system typical in raw material industries in which multiple items can be processed in the same batch in case they share sufficiently close production parameters. If the number of items proce...

In this paper we introduce vFlow A framework for rapid designing of batch processing applications for Cloud Computing environment. vFlow batch processing system extracts tasks from the vPlans diagrams, systematically captures the dynamics in batch application management tasks, and translates them to Cloud environment API, named vDocuments, that can be used to execute batch processing applicatio...

We consider an online scheduling problem in a parallel batch processing system with jobs in a batch being allowed to restart. Online means that jobs arrive over time, and all jobs’ characteristics are unknown before their arrival times. A parallel batch processing machine can handle up to several jobs simultaneously. All jobs in a batch start and complete at the same time. The processing time o...

—Driven by recent advances in batch Reinforcement Learning (RL), this paper contributes to the application of batch RL to demand response. In contrast to conventional model-based approaches, batch RL techniques do not require a system identification step, which makes them more suitable for a large-scale implementation. This paper extends fitted Q-iteration, a standard batch RL technique, to the...