SIMULATION STUDIES OF TRIGGER DECISION CRITERION FOR THE ALICE/PHOS

2007 ◽  
Vol 16 (07n08) ◽  
pp. 2407-2412
Author(s):  
YAPING WANG ◽  
XU CAI
Keyword(s):  
Decision Criterion ◽  
Simulation Studies ◽  
Energy Reconstruction ◽  
Trigger Rate ◽  
Reconstruction Performance ◽  
Event Trigger ◽  
Trigger Efficiency ◽  
Photon Event ◽  
Trigger Decision ◽  
Selection Of

This paper gives some results about trigger decision criterion of the ALICE PHOton Spectrometer (PHOS) by Monte Carlo simulations, including four parts: (1) an overview of trigger decision criterion of PHOS; (2) the energy reconstruction performance of PHOS; (3) the selection of trigger threshold and the event trigger efficiency distribution; (4) the photon event trigger rate of PHOS in p – p interactions and Pb – Pb collisions.

Numerical simulation studies of Cs3Bi2I9 perovskite solar device with optimal selection of electron and hole transport layers

Optik ◽  
2021 ◽  
Vol 231 ◽  
pp. 166417 ◽  
Author(s):  
Md Tohidul Islam ◽  
Md Rafsun Jani ◽  
Kazi Md Shorowordi ◽  
Zameer Hoque ◽  
Ali Mucteba Gokcek ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Hole Transport ◽  
Optimal Selection ◽  
Simulation Studies ◽  
Hole Transport Layers ◽  
Selection Of

scholarly journals Selection of X-chromosome Inactivation Model

2017 ◽  
Vol 16 ◽  
pp. 117693511774727 ◽  
Author(s):  
Jian Wang ◽  
Rajesh Talluri ◽  
Sanjay Shete
Keyword(s):  
X Chromosome ◽  
X Chromosome Inactivation ◽  
Association Test ◽  
Chromosome Inactivation ◽  
Simulation Studies ◽  
Nucleotide Polymorphisms ◽  
Unified Approach ◽  
Cancer Genetic ◽  
Single Nucleotide ◽  
Selection Of

To address the complexity of the X-chromosome inactivation (XCI) process, we previously developed a unified approach for the association test for X-chromosomal single-nucleotide polymorphisms (SNPs) and the disease of interest, accounting for different biological possibilities of XCI: random, skewed, and escaping XCI. In the original study, we focused on the SNP-disease association test but did not provide knowledge regarding the underlying XCI models. One can use the highest likelihood ratio (LLR) to select XCI models (max-LLR approach). However, that approach does not formally compare the LLRs corresponding to different XCI models to assess whether the models are distinguishable. Therefore, we propose an LLR comparison procedure (comp-LLR approach), inspired by the Cox test, to formally compare the LLRs of different XCI models to select the most likely XCI model that describes the underlying XCI process. We conduct simulation studies to investigate the max-LLR and comp-LLR approaches. The simulation results show that compared with the max-LLR, the comp-LLR approach has higher probability of identifying the correct underlying XCI model for the scenarios when the underlying XCI process is random XCI, escaping XCI, or skewed XCI to the deleterious allele. We applied both approaches to a head and neck cancer genetic study to investigate the underlying XCI processes for the X-chromosomal genetic variants.

scholarly journals FUZZY MULTI-CRITERIA DECISION MAKING MODEL FOR SUBCONTRACTOR SELECTION IN INTERNATIONAL CONSTRUCTION PROJECTS

2015 ◽  
Vol 22 (2) ◽  
pp. 210-234 ◽  
Author(s):  
Serdar ULUBEYLI ◽  
Aynur KAZAZ
Keyword(s):  
Construction Projects ◽  
Decision Criterion ◽  
Practical Application ◽  
Human Judgment ◽  
Qualitative And Quantitative ◽  
International Construction ◽  
Weak Points ◽  
Initial Idea ◽  
Decision Making Model ◽  
Selection Of

A general contractor’s ability to select proper subcontractors in foreign projects is a key competitive advantage. Toward this aim, a subcontractor selection model (CoSMo) was developed in this study. As a computational approach, the fuzzy sets method was employed because it can model human judgment by means of linguistic values, combining qualitative and quantitative decision criteria into an aggregate measure. Although the algorithm may be complex for easy acceptance by industrial practitioners, this disadvantage was minimized through a computer-supported system. In order to gain a better understanding of the current practice of CoSMo, a real world construction project was conducted. As a result, it was observed that CoSMo has high practical application and can be used as an advisory system by satisfying principal contractor’s requirements to reduce the risk involved in the selection of a subcontractor. Moreover, it gives an initial idea of how subcontractors perform on each decision criterion and allows the main contractor to understand the picture on the strong and weak points of each bidder and thereby to take conscious decisions.

scholarly journals Improving reliability of river flow forecasting using neural networks, wavelets and self-organising maps

2012 ◽  
Vol 15 (2) ◽  
pp. 486-502 ◽  
Author(s):  
Mukesh K. Tiwari ◽  
Ki-Young Song ◽  
Chandranath Chatterjee ◽  
Madan M. Gupta
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Lead Time ◽  
River Flow ◽  
Simulation Studies ◽  
River Flow Forecasting ◽  
Testing Dataset ◽  
Crucial Problem ◽  
Daily Discharge ◽  
Selection Of

Neural network (NN) models have gained much attention for river flow forecasting because of their ability to map complex non-linearities. However, the selection of appropriate length of training datasets is crucial and the uncertainty in predictions of the trained NNs with new datasets is a crucial problem. In this study, self-organising maps (SOM) are used to classify the datasets homogeneously and the performance of four types of NN models developed for daily discharge predictions – namely traditional NN, wavelet-based NN (WNN), bootstrap-based NN (BNN) and wavelet-bootstrap-based NN (WBNN) – is analysed for their applicability cluster-wise. SOM classified the training datasets into three clusters (i.e. cluster I, II and III) and the trained SOM is then used to assign testing datasets into these three clusters. Simulation studies show that the WBNN model performs better for the entire testing dataset as well as for values in clusters I and III; for cluster II the performance of BNN model is better compared with others for a 1-day lead time forecasting. Overall, it is found that the proposed methodology can enhance the accuracy and reliability of river flow forecasting.

Lightweight Design in Architecture – Forming of Stainless Steel Composites for Modern Facades

2015 ◽  
Vol 639 ◽  
pp. 77-82
Author(s):  
Marc Tulke ◽  
Jennifer Watzke ◽  
Alexander Brosius ◽  
Michael Schomäcker
Keyword(s):  
Stainless Steel ◽  
Composite Material ◽  
Lightweight Design ◽  
Mechanical Stretch ◽  
Simulation Studies ◽  
Stretch Forming ◽  
Forming Process ◽  
Extensive Simulation ◽  
Selection Of

This paper shows the characterisation of a new composite material for architectural applications. The stainless steel and polyethylene laminate offers new possibilities in forming optically pleasing facade shapes. A selection of possible structures is presented as a result of extensive simulation studies. The presented structures are generated with a new pneumo-mechanical stretch forming process.

scholarly journals Iterative Image Reconstruction for Limited-Angle CT Using Optimized Initial Image

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Jingyu Guo ◽  
Hongliang Qi ◽  
Yuan Xu ◽  
Zijia Chen ◽  
Shulong Li ◽  
...  
Keyword(s):  
Iterative Reconstruction ◽  
Simulated Data ◽  
Real Data ◽  
Clinical Applications ◽  
Data Reconstruction ◽  
Reconstruction Algorithms ◽  
Initial Image ◽  
Reconstruction Performance ◽  
Selection Of ◽  
Limited Angle

Limited-angle computed tomography (CT) has great impact in some clinical applications. Existing iterative reconstruction algorithms could not reconstruct high-quality images, leading to severe artifacts nearby edges. Optimal selection of initial image would influence the iterative reconstruction performance but has not been studied deeply yet. In this work, we proposed to generate optimized initial image followed by total variation (TV) based iterative reconstruction considering the feature of image symmetry. The simulated data and real data reconstruction results indicate that the proposed method effectively removes the artifacts nearby edges.

scholarly journals Selection of Filter And Reduction of Ripple in The Output of Boost-Converter for Four Bus Micro Grid System

2019 ◽  
Vol 8 (6) ◽  
pp. 263-268
Keyword(s):  
Boost Converter ◽  
Simulation Studies ◽  
Grid System ◽  
Voltage Ripple ◽  
Micro Grid ◽  
Cascade Filter ◽  
Selection Of

Boost converter finds a way amidst RES and inverter. This work investigates selection of filter and reduction of ripple in the output of boost-converter for four bus Micro- Grid- System. The objective of the proposed micro grid system was to improve the performance of four bus Micro Grid System (FB-MGS). Simulation studies were performed with C, L-C, Pi and cascade filters and the outcome shows an enhanced -performance by employing cascade-filter for FB- MGS. The outcomes specify that MGS with cascade-filter has diminished-voltage ripple.

scholarly journals Selection of Filtration Methods in the Analysis of Motion of Automated Guided Vehicle

2016 ◽  
Vol 16 (4) ◽  
pp. 183-189 ◽  
Author(s):  
Magdalena Dobrzańska ◽  
Paweł Dobrzański ◽  
Mirosław Śmieszek ◽  
Paweł Pawlus
Keyword(s):  
Error Correction ◽  
Experimental Studies ◽  
Digital Filtering ◽  
Automated Guided Vehicle ◽  
Simulation Studies ◽  
Data Set ◽  
Real Movement ◽  
Selection Of ◽  
Analysis Of Motion

AbstractIn this article the issues related to mapping the route and error correction in automated guided vehicle (AGV) movement have been discussed. The nature and size of disruption have been determined using the registered runs in experimental studies. On the basis of the analysis a number of numerical runs have been generated, which mapped possible to obtain runs in a real movement of the vehicle. The obtained data set has been used for further research. The aim of this paper was to test the selected methods of digital filtering on the same data set and determine their effectiveness. The results of simulation studies have been presented in the article. The effectiveness of various methods has been determined and on this basis the conclusions have been drawn.

Selection of an EOR technique for the matured EOR 33 reservoir in Southern Trinidad using adsorption and simulation studies

2021 ◽  
Vol 14 (23) ◽  
Author(s):  
Sanyah Ramkissoon ◽  
Rean Maharaj ◽  
David Alexander ◽  
Mohammad Soroush
Keyword(s):  
Simulation Studies ◽  
Selection Of

Variable selection in rank regression for analyzing longitudinal data

2016 ◽  
Vol 27 (8) ◽  
pp. 2447-2458 ◽  
Author(s):  
Liya Fu ◽  
You-Gan Wang
Keyword(s):  
Variable Selection ◽  
Longitudinal Data ◽  
Adaptive Lasso ◽  
New Method ◽  
Dispersion Function ◽  
Simulation Studies ◽  
Rank Regression ◽  
Oracle Properties ◽  
Effective Selection ◽  
Selection Of

In this paper, we consider variable selection in rank regression models for longitudinal data. To obtain both robustness and effective selection of important covariates, we propose incorporating shrinkage by adaptive lasso or SCAD in the Wilcoxon dispersion function and establishing the oracle properties of the new method. The new method can be conveniently implemented with the statistical software R. The performance of the proposed method is demonstrated via simulation studies. Finally, two datasets are analyzed for illustration. Some interesting findings are reported and discussed.

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