Search results for "Computer Science Application"
showing 10 items of 3998 documents
Development of an Inductive NIS Thermometer
2012
We have studied an inductive readout for normal metal-insulator-superconductor (NIS) tunnel junctions by using on-chip planar inductors and a DC SQUID (superconducting quantum interference device) to develop a sensitive and fast thermometer for studies of nanoscale heat conduction and bolometry. Our initial results show the feasibility of the concept, with a good sensitivity for temperatures below 1 K for aluminum as the superconductor when voltage biased close to the superconductor energy gap. peerReviewed
Method for finding the critical temperature of the island in a SET structure
2008
We present a method to measure the critical temperature of the island of a superconducting single electron transistor. The method is based on a sharp change in the slope of the zero-bias conductance as a function of temperature. We have used this method to determine the superconducting phase transition temperature of the Nb island of an superconducting single electron transistor with Al leads. We obtain $T_\mathrm{c}^\mathrm{Nb}$ as high as 8.5 K and gap energies up to $\Delta_\mathrm{Nb}\simeq 1.45$ meV. By looking at the zero bias conductance as a function of magnetic field instead of temperature, also the critical field of the island can be determined. Using the orthodox theory, we have …
First acceleration of heavy ion beams with a superconducting continuous wave HIM/GSI CW-linac
2020
Heavy Ion Accelerator Technology 2018, Lanzhou, China, 22 Oct 2018 - 26 Oct 2018; Journal of physics / Conference series 1401, 012012 (2020). doi:10.1088/1742-6596/1401/1/012012
Status and recent developments at the polarized-electron injector of the superconducting Darmstadt electron linear accelerator S-DALINAC
2011
At the superconducting Darmstadt electron linac a 100 keV source of polarized electrons has been installed. Major components had been tested prior to installation at an offline teststand. Commissioning of the new source at the S-DALINAC will take place early in 2011. We report on the performance of the teststand, simulations, developments on the laser systems, new radio-frequency components for the S-DALINAC injector, and the status of the implementation of the source.
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.
Anomalous magnetic hysteresis in the microwave surface resistance of MgB2 superconductor
2007
We report experimental results of the field-induced variations of the microwave surface resistance in samples of MgB2, produced by different methods. By sweeping the DC magnetic field at increasing and decreasing values, we have detected a magnetic hysteresis that can be ascribed to the different magnetic induction, due to the critical state of the fluxon lattice. The hysteresis observed in the bulk samples has an unusual shape, which cannot be justified in the framework of the critical-state models.
Capacity constrained supply chains: a simulation study
2008
This paper explores the relationship between constrained capacity and supply chain performance. Six capacity constraint levels are studied under different inventory policies and information sharing strategies. The results suggest that an increment of production capacity, used in industry as local approach to manage increasing incoming orders, does not necessarily imply an improvement in customer service. In presence of information distortions, the strategy of augmenting production capacity can lead to satisfy at a higher cost an over-estimated market demand. The collaborative practices provide bullwhip effect dampening and inventory stability, and increase the ability of the structure to av…
Multi-criteria risk classification to enhance complex supply networks performance
2021
[EN] Management of complex supply networks is a fundamental business topic today. Especially in the presence of many and diverse stakeholders, identifying and assessing those risks having a potential negative impact on the performance of supply processes is of utmost importance and, as a result, implementing focused risk management actions is a current lively field of research. The possibility of supporting Supply Chain Risks Management (SCRM) is herein explored from a Multi-Criteria Decision-Making (MCDM)-based perspective. The sorting method ELimination Et Choix Traduisant la REalite (ELECTRE) TRI is proposed as a structural procedure to classify Supply Chain Risks (SCRs) into proper risk…
Simulation analysis of cold chain performance based on time–temperature data
2011
Perishable goods are a fundamental source of revenue for the retail sector; their management, however, constitutes a severe challenge for retailers and supply chain partners. A significant cost in particular is the fraction of products perished through the supply chain, which also constitutes an ethical and environmental concern. Supply chain organisation and operative characteristics have a significant influence on this matter, as in fact ensuring suitable temperature conditions for the stock-keeping units throughout the supply chain is mandatory for perishable products. Recent developments in sensing and communication technologies allow detailed monitoring and control of cold chain; howev…
Deep learning approach for prediction of impact peak appearance at ground reaction force signal of running activity
2020
Protruding impact peak is one of the features of vertical ground reaction force (GRF) that is related to injury risk while running. The present research is dedicated to predicting GRF impact peak appearance by setting a binary classification problem. Kinematic data, namely a number of raw signals in the sagittal plane, collected by the Vicon motion capture system (Oxford Metrics Group, UK) were employed as predictors. Therefore, the input data for the predictive model are presented as a multi-channel time series. Deep learning techniques, namely five convolutional neural network (CNN) models were applied to the binary classification analysis, based on a Multi-Layer Perceptron (MLP) classifi…