scholarly journals Comparison of an oblique single cut rotation osteotomy with a novel 3D computer-assisted oblique double cut alignment approach

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Johannes G. G. Dobbe ◽  
Peter Kloen ◽  
Simon D. Strackee ◽  
Geert J. Streekstra
Keyword(s):  
Optimization Algorithm ◽  
Transverse Direction ◽  
Preoperative Planning ◽  
Computer Assisted ◽  
Alignment Error ◽  
Bone Length ◽  
Translation Error ◽  
The Cost ◽  
Rotation Osteotomy ◽  
Better Than

AbstractAn oblique double-cut rotation osteotomy (ODCRO) enables correcting a complex bone deformation by aligning, in 3D, the distal, middle and proximal bone segments with a target bone, without intersegmental gaps. We propose virtual preoperative planning of an ODCRO. To minimize a residual translation error, we use an optimization algorithm and optimize towards bone length, alignment in the transverse direction, or a balanced reconstruction. We compare the residual alignment error with an oblique single-cut rotation osteotomy using 15 complex bone deformations. The single-cut approach was not feasible in 5 cases, whereas the ODCRO procedure was feasible in all cases. The residual alignment error was smaller for the ODCRO than for the single-cut approach except for one case. In a subset for length reconstruction, the length error of 7.3–21.3 mm was restored to 0.0 mm in 4 of 5 cases, although at the cost of an increased transverse translation. The proposed method renders planning an ODCRO feasible and helps restoring bone alignment and lengthening better than an oblique single-cut rotation osteotomy. Awareness of the challenges and possibilities in preoperative planning of an ODCRO will be of value for future alignment surgery and for patients.

scholarly journals Telecom Churn Prediction System Based on Ensemble Learning Using Feature Grouping

2021 ◽  
Vol 11 (11) ◽  
pp. 4742
Author(s):  
Tianpei Xu ◽  
Ying Ma ◽  
Kangchul Kim
Keyword(s):  
Ensemble Learning ◽  
Machine Learning Algorithms ◽  
Customer Relationship ◽  
Prediction System ◽  
Churn Prediction ◽  
Customer Churn ◽  
Feature Grouping ◽  
Recognition Systems ◽  
The Cost ◽  
Better Than

In recent years, the telecom market has been very competitive. The cost of retaining existing telecom customers is lower than attracting new customers. It is necessary for a telecom company to understand customer churn through customer relationship management (CRM). Therefore, CRM analyzers are required to predict which customers will churn. This study proposes a customer-churn prediction system that uses an ensemble-learning technique consisting of stacking models and soft voting. Xgboost, Logistic regression, Decision tree, and Naïve Bayes machine-learning algorithms are selected to build a stacking model with two levels, and the three outputs of the second level are used for soft voting. Feature construction of the churn dataset includes equidistant grouping of customer behavior features to expand the space of features and discover latent information from the churn dataset. The original and new churn datasets are analyzed in the stacking ensemble model with four evaluation metrics. The experimental results show that the proposed customer churn predictions have accuracies of 96.12% and 98.09% for the original and new churn datasets, respectively. These results are better than state-of-the-art churn recognition systems.

A Determinant Elimination Method for Bottleneck Assignment and Generalized Assignment Problems

2012 ◽  
Vol 239-240 ◽  
pp. 1522-1527
Author(s):  
Wen Bo Wu ◽  
Yu Fu Jia ◽  
Hong Xing Sun
Keyword(s):  
Computational Complexity ◽  
Optimization Algorithm ◽  
Assignment Problem ◽  
Numerical Experiments ◽  
High Efficiency ◽  
Synthesis Method ◽  
Assignment Problems ◽  
Generalized Assignment ◽  
The Cost ◽  
Time And Space Complexity

The bottleneck assignment (BA) and the generalized assignment (GA) problems and their exact solutions are explored in this paper. Firstly, a determinant elimination (DE) method is proposed based on the discussion of the time and space complexity of the enumeration method for both BA and GA problems. The optimization algorithm to the pre-assignment problem is then discussed and the adjusting and transformation to the cost matrix is adopted to reduce the computational complexity of the DE method. Finally, a synthesis method for both BA and GA problems is presented. The numerical experiments are carried out and the results indicate that the proposed method is feasible and of high efficiency.

scholarly journals Demonstration of an integrated nanophotonic chip-scale alkali vapor magnetometer using inverse design

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Yoel Sebbag ◽  
Eliran Talker ◽  
Alex Naiman ◽  
Yefim Barash ◽  
Uriel Levy
Keyword(s):  
Spatial Resolution ◽  
Near Field ◽  
Computer Assisted ◽  
Experimental Characterization ◽  
Optical Isolation ◽  
New Concepts ◽  
On Chip ◽  
The Cost ◽  
Micrometer Scale

AbstractRecently, there has been growing interest in the miniaturization and integration of atomic-based quantum technologies. In addition to the obvious advantages brought by such integration in facilitating mass production, reducing the footprint, and reducing the cost, the flexibility offered by on-chip integration enables the development of new concepts and capabilities. In particular, recent advanced techniques based on computer-assisted optimization algorithms enable the development of newly engineered photonic structures with unconventional functionalities. Taking this concept further, we hereby demonstrate the design, fabrication, and experimental characterization of an integrated nanophotonic-atomic chip magnetometer based on alkali vapor with a micrometer-scale spatial resolution and a magnetic sensitivity of 700 pT/√Hz. The presented platform paves the way for future applications using integrated photonic–atomic chips, including high-spatial-resolution magnetometry, near-field vectorial imaging, magnetically induced switching, and optical isolation.

The Race for Online Reputation: Implications for Platforms, Firms, and Consumers

2021 ◽  
Author(s):  
Mingwen Yang ◽  
Zhiqiang (Eric) Zheng ◽  
Vijay Mookerjee
Keyword(s):  
Adverse Event ◽  
Marketing Mix ◽  
Digital Economy ◽  
The Other ◽  
The Mean ◽  
The Absolute ◽  
The Cost ◽  
Online Reputation ◽  
Better Than

Online reputation has become a key marketing-mix variable in the digital economy. Our study helps managers decide on the effort they should use to manage online reputation. We consider an online reputation race in which it is important not just to manage the absolute reputation, but also the relative rating. That is, to stay ahead, a firm should try to have ratings that are better than those of its competitors. Our findings are particularly significant for platform owners (such as Expedia or Yelp) to strategically grow their base of participating firms: growing the middle of the market (firms with average ratings) is the best option considering the goals of the platform and the other stakeholders, namely incumbents and consumers. For firms, we find that they should increase their effort when the mean market rating increases. Another key insight for firms is that, sometimes, adversity can come disguised as an opportunity. When an adverse event strikes the industry (such as a reduction in sales margin or an increase in the cost of effort), a firm’s profit can increase if it can manage this event better than its competitors.

scholarly journals Datasets and Their Influence on the Development of Computer Assisted Synthesis Planning Tools in the Pharmaceutical Domain

2019 ◽  
Author(s):  
Amol Thakkar ◽  
Thierry Kogej ◽  
Jean-Louis Reymond ◽  
Ola Engkvist ◽  
Esben Jannik Bjerrum
Keyword(s):  
Model Performance ◽  
Computer Assisted ◽  
Patent Office ◽  
United States Patent ◽  
Planning Tool ◽  
Virtual Libraries ◽  
Synthesis Planning ◽  
Synthetic Routes ◽  
The Cost ◽  
States Patent

<p>Computer Assisted Synthesis Planning (CASP) has gained considerable interest as of late. Herein we investigate a template-based retrosynthetic planning tool, trained on a variety of datasets consisting of up to 17.5 million reactions. We demonstrate that models trained on datasets such as internal Electronic Laboratory Notebooks (ELN), and the publicly available United States Patent Office (USPTO) extracts, are sufficient for the prediction of full synthetic routes to compounds of interest in medicinal chemistry. As such we have assessed the models on 1,731 compounds from 41 virtual libraries for which experimental results were known. Furthermore, we show that accuracy is a misleading metric for assessment of the ‘filter network’, and propose that the number of successfully applied templates, in conjunction with the overall ability to generate full synthetic routes be examined instead. To this end we found that the specificity of the templates comes at the cost of generalizability, and overall model performance. This is supplemented by a comparison of the underlying datasets and their corresponding models.</p>

A vibration-based identification of elastic properties of stitched sandwich panels

2018 ◽  
Vol 53 (5) ◽  
pp. 579-592 ◽  
Author(s):  
Nan Li ◽  
Mabrouk Ben Tahar ◽  
Zoheir Aboura ◽  
Kamel Khellil
Keyword(s):  
Elastic Properties ◽  
Transverse Direction ◽  
Sandwich Panel ◽  
Low Cost ◽  
Element Model ◽  
Vibration Test ◽  
Structural Application ◽  
Sensibility Analysis ◽  
The Cost ◽  
Non Destructive

Stitched sandwich becomes popular in structural application owing to its better performance in the transverse direction with respect to classical sandwich structure and relatively low-cost additional stitching process. The identification of its elastic properties is essential for offering a tailored structure for specific applications. A non-destructive identification method based on vibration test is proposed to obtain these parameters. The number of parameters is firstly reduced by a sensibility analysis. The retained parameters are identified by minimizing the cost function which indicates the gap between measured frequencies from vibration test and calculated frequencies from a finite element model. This method is applied to a stitched sandwich panel and its elastic properties are successfully identified.

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