scholarly journals Near-Optimal A-B Testing

2020 ◽  
Vol 66 (10) ◽  
pp. 4477-4495
Author(s):  
Nikhil Bhat ◽  
Vivek F. Farias ◽  
Ciamac C. Moallemi ◽  
Deeksha Sinha
Keyword(s):  
Selection Bias ◽  
Dynamic Optimization ◽  
State Of The Art ◽  
Stopping Times ◽  
Elliptical Distribution ◽  
Statistical Efficiency ◽  
Optimization Framework ◽  
Online Setting ◽  
Operational Constraints ◽  
The Impact

We consider the problem of A-B testing when the impact of the treatment is marred by a large number of covariates. Randomization can be highly inefficient in such settings, and thus we consider the problem of optimally allocating test subjects to either treatment with a view to maximizing the precision of our estimate of the treatment effect. Our main contribution is a tractable algorithm for this problem in the online setting, where subjects arrive, and must be assigned, sequentially, with covariates drawn from an elliptical distribution with finite second moment. We further characterize the gain in precision afforded by optimized allocations relative to randomized allocations, and show that this gain grows large as the number of covariates grows. Our dynamic optimization framework admits several generalizations that incorporate important operational constraints such as the consideration of selection bias, budgets on allocations, and endogenous stopping times. In a set of numerical experiments, we demonstrate that our method simultaneously offers better statistical efficiency and less selection bias than state-of-the-art competing biased coin designs. This paper was accepted by Noah Gans, stochastic models and simulation.

scholarly journals Does Delayed Retirement Crowd Out Workforce Welfare? Evidence in China

SAGE Open ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 215824402110544
Author(s):  
Zhen Hu ◽  
James Yang
Keyword(s):  
Dynamic Optimization ◽  
Working Population ◽  
Replacement Rate ◽  
Elderly Individuals ◽  
The Public ◽  
Optimization Framework ◽  
Retirement Plan ◽  
Crowd Out ◽  
The Impact ◽  
Over Time

Does delayed retirement crowd out the welfare of the workforce? To answer this question, a dynamic optimization framework is established to simulate the impact of delayed retirement on the welfare of the working population over time. Simulations are conducted based on practical and feasible parameters. Delayed retirement was found to improve the welfare of the working population rather than crowding it out. Furthermore, the results are robust against changes in parameters and modes of supporting elderly individuals. In terms of policymaking, it is suggested that such facts be shared with the public and that a delayed retirement plan be introduced as soon as possible to manage the pension and retirement wave caused by post-1960s baby boomers. However, to ensure that the delayed retirement plan does not lead to a reduction in the welfare of the working population, increases in fertility costs and the pension replacement rate should be appropriately controlled.

scholarly journals Comparison of Industrial Quenching Oils

Metals ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 250
Author(s):  
Jiří Hájek ◽  
Zaneta Dlouha ◽  
Vojtěch Průcha
Keyword(s):  
State Of The Art ◽  
Cooling Capacity ◽  
Steel Grade ◽  
Cooling Curves ◽  
Cooling Process ◽  
Industrial Practice ◽  
Product Size ◽  
Cct Curve ◽  
Hardening Power ◽  
The Impact

This article is a response to the state of the art in monitoring the cooling capacity of quenching oils in industrial practice. Very often, a hardening shop requires a report with data on the cooling process for a particular quenching oil. However, the interpretation of the data can be rather difficult. The main goal of our work was to compare various criteria used for evaluating quenching oils. Those of which prove essential for operation in tempering plants would then be introduced into practice. Furthermore, the article describes monitoring the changes in the properties of a quenching oil used in a hardening shop, the effects of quenching oil temperature on its cooling capacity and the impact of the water content on certain cooling parameters of selected oils. Cooling curves were measured (including cooling rates and the time to reach relevant temperatures) according to ISO 9950. The hardening power of the oil and the area below the cooling rate curve as a function of temperature (amount of heat removed in the nose region of the Continuous cooling transformation - CCT curve) were calculated. V-values based on the work of Tamura, reflecting the steel type and its CCT curve, were calculated as well. All the data were compared against the hardness and microstructure on a section through a cylinder made of EN C35 steel cooled in the particular oil. Based on the results, criteria are recommended for assessing the suitability of a quenching oil for a specific steel grade and product size. The quenching oils used in the experiment were Houghto Quench C120, Paramo TK 22, Paramo TK 46, CS Noro MO 46 and Durixol W72.

scholarly journals Smoothing additive manufactured parts using ns-pulsed laser radiation

2021 ◽  
Author(s):  
Florian Kuisat ◽  
Fernando Lasagni ◽  
Andrés Fabián Lasagni
Keyword(s):  
Surface Roughness ◽  
Mechanical Performance ◽  
State Of The Art ◽  
Pulsed Laser ◽  
Industrial Applications ◽  
Laser Source ◽  
Pulsed Laser Radiation ◽  
Current State ◽  
The Impact

AbstractIt is well known that the surface topography of a part can affect its mechanical performance, which is typical in additive manufacturing. In this context, we report about the surface modification of additive manufactured components made of Titanium 64 (Ti64) and Scalmalloy®, using a pulsed laser, with the aim of reducing their surface roughness. In our experiments, a nanosecond-pulsed infrared laser source with variable pulse durations between 8 and 200 ns was applied. The impact of varying a large number of parameters on the surface quality of the smoothed areas was investigated. The results demonstrated a reduction of surface roughness Sa by more than 80% for Titanium 64 and by 65% for Scalmalloy® samples. This allows to extend the applicability of additive manufactured components beyond the current state of the art and break new ground for the application in various industrial applications such as in aerospace.

scholarly journals Cash Flow Bullwhip—Literature Review and Research Perspectives

Logistics ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 8
Author(s):  
Hicham Lamzaouek ◽  
Hicham Drissi ◽  
Naima El Haoud
Keyword(s):  
Literature Review ◽  
Customer Service ◽  
Cash Flow ◽  
State Of The Art ◽  
Research Work ◽  
Bullwhip Effect ◽  
Research Perspectives ◽  
Financial Perspective ◽  
The Impact ◽  
Exhaustive List

The bullwhip effect is a pervasive phenomenon in all supply chains causing excessive inventory, delivery delays, deterioration of customer service, and high costs. Some researchers have studied this phenomenon from a financial perspective by shedding light on the phenomenon of cash flow bullwhip (CFB). The objective of this article is to provide the state of the art in relation to research work on CFB. Our ambition is not to make an exhaustive list, but to synthesize the main contributions, to enable us to identify other interesting research perspectives. In this regard, certain lines of research remain insufficiently explored, such as the role that supply chain digitization could play in controlling CFB, the impact of CFB on the profitability of companies, or the impacts of the omnichannel commerce on CFB.

scholarly journals Assessing the Impact of the Loss Function, Architecture and Image Type for Deep Learning-Based Wildfire Segmentation

2021 ◽  
Vol 11 (15) ◽  
pp. 7046
Author(s):  
Jorge Francisco Ciprián-Sánchez ◽  
Gilberto Ochoa-Ruiz ◽  
Lucile Rossi ◽  
Frédéric Morandini
Keyword(s):  
Deep Learning ◽  
Loss Function ◽  
State Of The Art ◽  
Fire Detection ◽  
Loss Functions ◽  
Wildfire Spread ◽  
Combine Information ◽  
The Impact ◽  
Image Type ◽  
Segmentation Models

Wildfires stand as one of the most relevant natural disasters worldwide, particularly more so due to the effect of climate change and its impact on various societal and environmental levels. In this regard, a significant amount of research has been done in order to address this issue, deploying a wide variety of technologies and following a multi-disciplinary approach. Notably, computer vision has played a fundamental role in this regard. It can be used to extract and combine information from several imaging modalities in regard to fire detection, characterization and wildfire spread forecasting. In recent years, there has been work pertaining to Deep Learning (DL)-based fire segmentation, showing very promising results. However, it is currently unclear whether the architecture of a model, its loss function, or the image type employed (visible, infrared, or fused) has the most impact on the fire segmentation results. In the present work, we evaluate different combinations of state-of-the-art (SOTA) DL architectures, loss functions, and types of images to identify the parameters most relevant to improve the segmentation results. We benchmark them to identify the top-performing ones and compare them to traditional fire segmentation techniques. Finally, we evaluate if the addition of attention modules on the best performing architecture can further improve the segmentation results. To the best of our knowledge, this is the first work that evaluates the impact of the architecture, loss function, and image type in the performance of DL-based wildfire segmentation models.

Patients Who Attend Alone at a First Memory Consultation: Are They a Specific Population,or Is It an Instance of Confounding Bias?

2019 ◽  
Vol 81 (1-2) ◽  
pp. 81-86
Author(s):  
Pierre Koskas ◽  
Mouna Romdhani ◽  
Olivier Drunat
Keyword(s):  
Selection Bias ◽  
Confounding Bias ◽  
Significant Difference ◽  
Comparison Groups ◽  
Methodological Problems ◽  
Group 2 ◽  
The Impact ◽  
First Time ◽  
State Examination ◽  
Group 1

As commonly happens in epidemiological research, none of the reported studies were totally free of methodological problems. Studies have considered the influence of social relationships on dementia, but the mechanisms underlying these associations are not perfectly understood. We look at the possible impact of selection bias. For their first memory consultation, patients may come alone or accompanied by a relative. Our objective is to better understand the impact of this factor by retrospective follow-up of geriatric memory outpatients over several years. All patients over 70 who were referred to Bretonneau Memory Clinic for the first time, between January 2006 and 2018, were included in the study. The patients who came alone formed group 1, the others, whatever type of relative accompanied them, formed group 2. We compared the Mini-Mental State Examination (MMSE) scores of patients; and for all patients who came twice for consultation with at least a 60-day interval, we compared their first MMSE with the MMSE performed at the second consultation. In total, 2,935 patients were included, aged 79.7 ± 8.4 years. Six hundred and twenty-five formed group 1 and 2,310 group 2. We found a significant difference in MMSE scores between the 2 groups of patients; and upon second consultation in group 2, but that difference was minor in group 1. Our finding of a possible confounding factor underlines the complexity of choosing comparison groups in order to minimize selection bias while maintaining clinical relevance.

scholarly journals Investigating the Impact of the Bit Depth of Fluorescence-Stained Images on the Performance of Deep Learning-Based Nuclei Instance Segmentation

Diagnostics ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 967
Author(s):  
Amirreza Mahbod ◽  
Gerald Schaefer ◽  
Christine Löw ◽  
Georg Dorffner ◽  
Rupert Ecker ◽  
...  
Keyword(s):  
Deep Learning ◽  
State Of The Art ◽  
Computer Assisted ◽  
Important Criterion ◽  
Histological Image ◽  
Computer Mediated ◽  
Image Patches ◽  
Processing Techniques ◽  
The Impact ◽  
Instance Segmentation

Nuclei instance segmentation can be considered as a key point in the computer-mediated analysis of histological fluorescence-stained (FS) images. Many computer-assisted approaches have been proposed for this task, and among them, supervised deep learning (DL) methods deliver the best performances. An important criterion that can affect the DL-based nuclei instance segmentation performance of FS images is the utilised image bit depth, but to our knowledge, no study has been conducted so far to investigate this impact. In this work, we released a fully annotated FS histological image dataset of nuclei at different image magnifications and from five different mouse organs. Moreover, by different pre-processing techniques and using one of the state-of-the-art DL-based methods, we investigated the impact of image bit depth (i.e., eight bits vs. sixteen bits) on the nuclei instance segmentation performance. The results obtained from our dataset and another publicly available dataset showed very competitive nuclei instance segmentation performances for the models trained with 8 bit and 16 bit images. This suggested that processing 8 bit images is sufficient for nuclei instance segmentation of FS images in most cases. The dataset including the raw image patches, as well as the corresponding segmentation masks is publicly available in the published GitHub repository.

scholarly journals Intracytoplasmic sperm injection: state of the art in humans

Reproduction ◽  
2017 ◽  
Vol 154 (6) ◽  
pp. F93-F110 ◽  
Author(s):  
G D Palermo ◽  
C L O’Neill ◽  
S Chow ◽  
S Cheung ◽  
A Parrella ◽  
...  
Keyword(s):  
Intracytoplasmic Sperm Injection ◽  
Poor Prognosis ◽  
State Of The Art ◽  
Semen Analysis ◽  
Reproductive Technology ◽  
Male Factor Infertility ◽  
Male Factor ◽  
Current Application ◽  
Infertile Couples ◽  
The Impact

Among infertile couples, 25% involve both male and female factors, while male factor alone accounts for another 25% due to oligo-, astheno-, teratozoospermia, a combination of the three, or even a complete absence of sperm cells in the ejaculate and can lead to a poor prognosis even with the help of assisted reproductive technology (ART). Intracytoplasmic sperm injection (ICSI) has been with us now for a quarter of a century and in spite of the controversy generated since its inception, it remains in the forefront of the techniques utilized in ART. The development of ICSI in 1992 has drastically decreased the impact of male factor, resulting in millions of pregnancies worldwide for couples who, without ICSI, would have had little chance of having their own biological child. This review focuses on the state of the art of ICSI regarding utility of bioassays that evaluate male factor infertility beyond the standard semen analysis and describes the current application and advances in regard to ICSI, particularly the genetic and epigenetic characteristics of spermatozoa and their impact on reproductive outcome.

The Impact Assessment of the Managed Motorway on M25 Junction 5 to 7

2011 ◽  
Vol 66-68 ◽  
pp. 692-696
Author(s):  
Sui Chao ◽  
Ling Tao Wu ◽  
Jian Yun Chen
Keyword(s):  
Impact Assessment ◽  
State Of The Art ◽  
Technical State ◽  
Current Implementation ◽  
The Impact

This study introduces the transport situation and polices of the highway agency for the M25. Then the current implementation of the Managed Motorway on M25 between junction 5 and junction 7 is reviewed, and some examples are given in this paper. Then a technical state-of-the-art of application is also reviewed. After that, the requirements for integration with complementary systems and polices are presented. Finally, this paper discusses the arguments for and against taking this application forward.

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