Pattern representation and recognition with accelerated analog neuromorphic systems

Despite being originally inspired by the central nervous system, artificial neural networks have diverged from their biological archetypes as they have been remodeled to fit particular tasks. In this paper, we review several possibilites to reverse map these architectures to biologically more realistic spiking networks with the aim of emulating them on fast, low-power neuromorphic hardware. Since many of these devices employ analog components, which cannot be perfectly controlled, finding ways to compensate for the resulting effects represents a key challenge. Here, we discuss three different strategies to address this problem: the addition of auxiliary network components for stabilizing activity, the utilization of inherently robust architectures and a training method for hardware-emulated networks that functions without perfect knowledge of the system's dynamics and parameters. For all three scenarios, we corroborate our theoretical considerations with experimental results on accelerated analog neuromorphic platforms.Comment: accepted at ISCAS 201

The Theoretical and Statistical Ising Model: A Practical Guide in <i>R</i>

The “Ising model” refers to both the statistical and the theoretical use of the same equation. In this article, we introduce both uses and contrast their differences. We accompany the conceptual introduction with a survey of Ising-related software packages in R. Since the model’s different uses are best understood through simulations, we make this process easily accessible with fully reproducible examples. Using simulations, we show how the theoretical Ising model captures local-alignment dynamics. Subsequently, we present it statistically as a likelihood function for estimating empirical network models from binary data. In this process, we give recommendations on when to use traditional frequentist estimators as well as novel Bayesian options

Impact of RFID information-sharing coordination over a supply chain with reverse logistics

Companies have adopted environmental practices such as reverse logistics over the past few decades. However, studies show that aligning partners inside the green supply chain can be a substantial problem. This lack of coordination can increase overall supply chain cost. Information technology such as Radio Frequency Identification (RFID) has the potential to enable decentralized supply chain coordinate their information. Even though there are research that address RFID on traditional supply chain, few researches address how to coordinate RFID information sharing in a green supply chain. We study, through simulation experiments, two types of RFID information-sharing coordination under different configurations related with their inventory policies: basic and advanced. Statistical analyses show that better results can be presented in advanced RFID configuration given new coordination and inventory policy decisions presented. In addition, these findings shows what are the RFID information-sharing coordination that can provide better system improvement depending on the supply chain scenarios and factors

Inventory drivers in a pharmaceutical supply chain

In recent years, inventory reduction has been a key objective of pharmaceutical companies, especially within cost optimization initiatives. Pharmaceutical supply chains are characterized by volatile and unpredictable demands –especially in emergent markets-, high service levels, and complex, perishable finished-good portfolios, which makes keeping reasonable amounts of stock a true challenge. However, a one-way strategy towards zero-inventory is in reality inapplicable, due to the strategic nature and importance of the products being commercialised. Therefore, pharmaceutical supply chains are in need of new inventory strategies in order to remain competitive. Finished-goods inventory management in the pharmaceutical industry is closely related to the manufacturing systems and supply chain configurations that companies adopt. The factors considered in inventory management policies, however, do not always cover the full supply chain spectrum in which companies operate. This paper works under the pre-assumption that, in fact, there is a complex relationship between the inventory configurations that companies adopt and the factors behind them. The intention of this paper is to understand the factors driving high finished-goods inventory levels in pharmaceutical supply chains and assist supply chain managers in determining which of them can be influenced in order to reduce inventories to an optimal degree. Reasons for reducing inventory levels are found in high inventory holding and scrap related costs; in addition to lost sales for not being able to serve the customers with the adequate shelf life requirements. The thesis conducts a single case study research in a multi-national pharmaceutical company, which is used to examine typical inventory configurations and the factors affecting these configurations. This paper presents a framework that can assist supply chain managers in determining the most important inventory drivers in pharmaceutical supply chains. The findings in this study suggest that while external and downstream supply chain factors are recognized as being critical to pursue inventory optimization initiatives, pharmaceutical companies are oriented towards optimizing production processes and meeting regulatory requirements while still complying with high service levels, being internal factors the ones prevailing when making inventory management decisions. Furthermore, this paper investigates, through predictive modelling techniques, how various intrinsic and extrinsic factors influence the inventory configurations of the case study company. The study shows that inventory configurations are relatively unstable over time, especially in configurations that present high safety stock levels; and that production features and product characteristics are important explanatory factors behind high inventory levels. Regulatory requirements also play an important role in explaining the high strategic inventory levels that pharmaceutical companies hold