Search results for "NETWORK"

Electromagnetic behaviour of superconductive amorphous metals

2005

The penetration depth of the magnetic field into an amorphous superconductor is calculated. The ratio of the London penetration depth δL to the electron free path le under zero temperature is above unity for almost all amorphous metals. That is why pure metals, in a superconducting state, change from type I superconductors to type II superconductors during the crystalline–amorphous transition.

Quantum Monte Carlo Simulations of Models Related to High-Tc Superconductivity on a Transputer Network

1991

Much of the insight into the low temperature behaviour of two-dimensional quantum antiferromagnets has been recently obtained by extensive Monte Carlo. These models are relevant in the study of the magnetic behaviour of high Tc compounds containing copper-oxide layers. While of little technical importance, the physical properties of these models are certainly important for the understanding of the new type of behaviour that leads to superconductivity under certain conditions.

A journey into the information Typhoon: Typhoon Haiyan DRL Field Report Findings and Research Insights:

2013

A Decisional Multi-Agent Framework for Automatic Supply Chain Arrangement

2013

In this work, a multi-agent system (MAS) for supply chain dynamic configuration is proposed. The brain of each agent is composed of a Bayesian Decision Network (BDN); this choice allows the agent for taking the best decisions estimating benefits and potential risks of different strategies, analyzing and managing uncertain information about the collaborating companies. Each agent collects information about customer's orders and current market prices, and analyzes previous experiences of collaborations with trading partners. The agent therefore performs a probabilistic inferential reasoning to filter information modeled in its knowledge base in order to achieve the best performance in the sup…

An Innovative Shelf Life Model Based on Smart Logistic Unit for an Efficient Management of the Perishable Food Supply Chain

2015

Despite the recent interest towards food safety and control, it is generally difficult to ensure full products traceability through industrial food chains, due to the lack of efficient information and communication systems. Consequently, nowadays, the protection of food products often ends at the gates of the producer without any investigation about the status of their quality at the consumer's location. The aim of this paper was the development of a supply chain monitoring system based on a smart logistic unit (SLU) to support the integrated management of the food supply chain from “farm to fork” in order to guarantee and control food safety and shelf life (SL) of products in agreement wit…

R&D supply chain and innovation performance: the contingent role of the firm’s position in the network

2013

This paper conceptualizes the supply chain of innovation as a sub-set of the whole innovation network. We focus on the relationship between the activities of purchasing/selling R&D and the firm’s innovation performance. Specifically, we examine how the position of the firm within its innovation network moderates this relationship. Our empirical setting consists in cross-sectional data about 1772 agreements signed by biotech companies between 2006-2010. We find, first, anecdotal evidence of both the existence of the innovation supply chain and the phenomenon of firms’ positioning along it. Second, we find that information richness positively moderates the effect of purchasing R&D services on…

The modes of supply net management: a capability view

2007

Purpose – The purpose of this paper is to identify the key capabilities required in supply net management.Design/methodology/approach – Uses the Management Capability Framework to break down supply net management into different modes and identify capabilities required in them.Findings – Reveals that the supply activity of companies increasingly takes place in intentionally developed strategic networks called supply nets. These networks pose distinctive challenges for supply chain management. Identifies four diverse but simultaneously extant modes of management in the supply net context, and discusses the key managerial capabilities in each mode.Originality/value – Provides a conceptual fram…

Management dilemmas in innovative supplier networks

2016

This paper focuses on the challenges in managing innovation within supply networks. We present an empirical study on innovation collaboration between a focal company and its supply network of small and medium sized enterprises. By analysing the case from the viewpoints of the focal company, the suppliers and investors we point out three controversial issues in innovation management within the supply network: intellectual property rights, partnering versus competition, and commitment versus independency. Furthermore, we analyse the suppliers' positions with a purchasing portfolio model and present implications for innovation management practices in supply chains. peerReviewed

Effectively Predicting the Presence of Coronary Heart Disease Using Machine Learning Classifiers

2022

Coronary heart disease is one of the major causes of deaths around the globe. Predicating a heart disease is one of the most challenging tasks in the field of clinical data analysis. Machine learning (ML) is useful in diagnostic assistance in terms of decision making and prediction on the basis of the data produced by healthcare sector globally. We have also perceived ML techniques employed in the medical field of disease prediction. In this regard, numerous research studies have been shown on heart disease prediction using an ML classifier. In this paper, we used eleven ML classifiers to identify key features, which improved the predictability of heart disease. To introduce the prediction …

Machine learning for a combined electroencephalographic anesthesia index to detect awareness under anesthesia

2020

Spontaneous electroencephalogram (EEG) and auditory evoked potentials (AEP) have been suggested to monitor the level of consciousness during anesthesia. As both signals reflect different neuronal pathways, a combination of parameters from both signals may provide broader information about the brain status during anesthesia. Appropriate parameter selection and combination to a single index is crucial to take advantage of this potential. The field of machine learning offers algorithms for both parameter selection and combination. In this study, several established machine learning approaches including a method for the selection of suitable signal parameters and classification algorithms are a…