An EMO Algorithm Using the Hypervolume Measure as Selection Criterion

2005 ◽  
pp. 62-76 ◽  
Author(s):  
Michael Emmerich ◽  
Nicola Beume ◽  
Boris Naujoks
Keyword(s):  
Selection Criterion

Spacings and Intensities of Weak-Beam Dark Field Thickness Fringes

1981 ◽  
Vol 39 ◽  
pp. 222-223
Author(s):  
M. Avalos-Borja ◽  
K. Heinemann
Keyword(s):  
Selection Criterion ◽  
Dark Field ◽  
Dynamical Theory ◽  
Bragg Condition ◽  
Weak Beam ◽  
Kinematical Theory ◽  
Equal Thickness

Weak-beam dark field (WBDF) TEM produces narrowly spaced equal-thickness fringes in wedge-shaped crystals. Using non-systematic diffraction conditions, we have shown elsewhere that simple 2-beam kinematical theory (KT) calculations yield average fringe spacings that are for most practical purposes as satisfactorily accurate as the average spacings obtained from optimized multibeam dynamical theory (DT) calculations, As Fig. 1 shows, this result holds for deviations from the Bragg condition as low as 2x10-1 nm-1, and the differences between the results from the two calculational methods become increasingly insignificant for larger excitation errors. (Unless otherwise noted, all results reported here are for gold crystals, using the 200 beam at 100 KV; the DT calculations were made for 74 beams, using the selection criterion D as discussed in ref. [3]).

Mindfulness Training as Cognitive Training in High-Demand Cohorts: An Initial Study in Elite Military Servicemembers

2018 ◽  
Author(s):  
Anthony Paul Zanesco ◽  
Ekaterina Denkova ◽  
Scott L. Rogers ◽  
William K. MacNulty ◽  
Amishi P. Jha
Keyword(s):  
Working Memory ◽  
Cognitive Training ◽  
Short Form ◽  
Memory Performance ◽  
Memory Task ◽  
Selection Criterion ◽  
Initial Study ◽  
Mindfulness Training ◽  
Training Tool ◽  
Cognitive Failures

Cognitive ability is a key selection criterion for entry into many elite professions. Herein, we investigate whether mindfulness training (MT) can enhance cognitive performance in elite military forces. The cognitive effects of a short-form 8-hour MT program contextualized for military cohorts, referred to as Mindfulness-Based Attention Training (MBAT), were assessed. Servicemembers received either a 2-week (n = 40) or 4-week (n = 36) version of MBAT, or no training (NTC, n = 44). Sustained attention and working memory task performance along with self-reported cognitive failures were assessed at study onset (T1) and 8-weeks later (T2). In contrast to both the NTC and 2-week MT groups, the 4-week MT group significantly improved over time on attention and working memory outcome measures. Among the 4-week more so than the 2-week MBAT participants, working memory performance improvements were correlated with their amount of out-of-class MT practice. In addition to these group-wise effects, all participants receiving MBAT decreased in their self-reported cognitive failures from T1 to T2. Importantly, none of these improvements were related to self-reported task motivation. Together, these results suggest that short-form MT, when delivered over a 4-week delivery schedule, may be an effective cognitive training tool in elite military cohorts.

Gamma Knife surgery for metastatic brain tumors

2008 ◽  
Vol 109 (Supplement) ◽  
pp. 118-121 ◽  
Author(s):  
Toru Serizawa ◽  
Masaaki Yamamoto ◽  
Osamu Nagano ◽  
Yoshinori Higuchi ◽  
Shinji Matsuda ◽  
...  
Keyword(s):  
Brain Metastases ◽  
Gamma Knife ◽  
Patient Selection ◽  
Selection Criterion ◽  
Gamma Knife Surgery ◽  
Treatment Result ◽  
Karnofsky Performance Scale ◽  
Consecutive Series ◽  
Primary Tumors ◽  
Patient Selection Criterion

Object The authors compared results of Gamma Knife surgery (GKS) for brain metastases obtained at 2 institutions in Japan. Methods They analyzed a consecutive series of 2390 patients with brain metastases who underwent GKS from 1998 through 2005 in 2 institutes (1181 patients in Chiba; 1209 in Mito). In the 2 facilities, 1 neurosurgeon each was responsible for diagnosis, patient selection, GKS procedures, and follow-up (T.S. in Chiba, M.Y. in Mito). Even if tumor numbers exceeded 4, all visible lesions were irradiated with a total skull integral dose (TSID) of ≤ 10–12 J. No prophylactic whole-brain radiotherapy (WBRT) was applied. If new distant lesions were detected, salvage GKS was appropriately performed. Results The distributions of patient and treatment factors did not differ between institutes. The most common primary tumors were lung cancer (1572 patients), followed by gastrointestinal tract (316), breast (211), kidney (113), and other cancers (159). The median survival periods were 7.7 months in Chiba and 7.0 months in Mito (p = 0.0635). The significant poor prognostic factors for overall survival were active extracranial disease status, male sex, and low initial Karnofsky Performance Scale score on multivariate analysis (all p < 0.0001). The neurological survival rates at 1 year were 86.6% in Chiba and 84.2% in Mito (p = 0.3310). Conclusions This 2-institute study demonstrated no significant institutional differences in any of the treatment result items. Gamma Knife surgery for brain metastases without prophylactic WBRT prevents neurological death and allows a patient to maintain good brain condition. However, there is 1 important patient selection criterion: regardless of how many tumors there are, all lesions can be irradiated with a TSID of ≤12 J.

scholarly journals An Ad Hoc Random Initialization Deep Neural Network Architecture for Discriminating Malignant Breast Cancer Lesions in Mammographic Images

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Andrea Duggento ◽  
Marco Aiello ◽  
Carlo Cavaliere ◽  
Giuseppe L. Cascella ◽  
Davide Cascella ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Network Architecture ◽  
Ad Hoc ◽  
False Negative ◽  
Selection Criterion ◽  
Current Status ◽  
Clinical Image ◽  
Imaging Data ◽  
Breast Cancer Death ◽  
Random Initialization

Breast cancer is one of the most common cancers in women, with more than 1,300,000 cases and 450,000 deaths each year worldwide. In this context, recent studies showed that early breast cancer detection, along with suitable treatment, could significantly reduce breast cancer death rates in the long term. X-ray mammography is still the instrument of choice in breast cancer screening. In this context, the false-positive and false-negative rates commonly achieved by radiologists are extremely arduous to estimate and control although some authors have estimated figures of up to 20% of total diagnoses or more. The introduction of novel artificial intelligence (AI) technologies applied to the diagnosis and, possibly, prognosis of breast cancer could revolutionize the current status of the management of the breast cancer patient by assisting the radiologist in clinical image interpretation. Lately, a breakthrough in the AI field has been brought about by the introduction of deep learning techniques in general and of convolutional neural networks in particular. Such techniques require no a priori feature space definition from the operator and are able to achieve classification performances which can even surpass human experts. In this paper, we design and validate an ad hoc CNN architecture specialized in breast lesion classification from imaging data only. We explore a total of 260 model architectures in a train-validation-test split in order to propose a model selection criterion which can pose the emphasis on reducing false negatives while still retaining acceptable accuracy. We achieve an area under the receiver operatic characteristics curve of 0.785 (accuracy 71.19%) on the test set, demonstrating how an ad hoc random initialization architecture can and should be fine tuned to a specific problem, especially in biomedical applications.

scholarly journals Embodied Carbon as a Material Selection Criterion: Insights from Sri Lankan Construction Sector

2021 ◽  
Vol 13 (4) ◽  
pp. 2202
Author(s):  
Amalka Nawarathna ◽  
Muditha Siriwardana ◽  
Zaid Alwan
Keyword(s):  
Sri Lanka ◽  
Construction Projects ◽  
Material Selection ◽  
Selection Criterion ◽  
Green Building ◽  
Vital Role ◽  
Low Carbon ◽  
Rating Systems ◽  
Embodied Carbon ◽  
The Government

The choice of materials is crucial in responding to the increasing embodied carbon (EC) impacts of buildings. Building professionals involved in material selection for construction projects have a vital role to play in this regard. This paper aimed to explore the extent to which building professionals in Sri Lanka considered EC as a material selection criterion. A questionnaire survey was conducted among a sample of building professionals in Sri Lanka. The results indicated that the consideration of EC as a material selection criterion remained low among key professionals, such as architects, engineers, and sustainability managers, despite their reasonable influencing powers and knowledge of EC. Those respondents who had considered EC as a selection criterion said they had been primarily driven by green building rating systems and previous experience. Those respondents who had not considered EC during material selection commonly reported that they had been prevented from doing so by the lack of regulations and the lack of alternative low carbon materials. Respondents believed that the involvement of actors, such as the government, professional bodies, environmental organizations, activist groups, and the public, may be significant in promoting the greater consideration of EC during material selection.

scholarly journals Serum alpha-fetoprotein and clinical outcomes in patients with advanced hepatocellular carcinoma treated with ramucirumab

2021 ◽  
Author(s):  
Andrew X. Zhu ◽  
Richard S. Finn ◽  
Yoon-Koo Kang ◽  
Chia-Jui Yen ◽  
Peter R. Galle ◽  
...  
Keyword(s):  
Prognostic Factor ◽  
Clinical Outcomes ◽  
Predictive Value ◽  
Survival Benefit ◽  
Radiographic Progression ◽  
Cox Regression ◽  
Selection Criterion ◽  
Alpha Fetoprotein ◽  
Advanced Hepatocellular Carcinoma ◽  
Clinical Trial Registration

Abstract Background Post hoc analyses assessed the prognostic and predictive value of baseline alpha-fetoprotein (AFP), as well as clinical outcomes by AFP response or progression, during treatment in two placebo-controlled trials (REACH, REACH-2). Methods Serum AFP was measured at baseline and every three cycles. The prognostic and predictive value of baseline AFP was assessed by Cox regression models and Subpopulation Treatment Effect Pattern Plot method. Associations between AFP (≥ 20% increase) and radiographic progression and efficacy were assessed. Results Baseline AFP was confirmed as a continuous (REACH, REACH-2; p < 0.0001) and dichotomous (≥400 vs. <400 ng/ml; REACH, p < 0.01) prognostic factor, and was predictive for ramucirumab survival benefit in REACH (p = 0.0042 continuous; p < 0.0001 dichotomous). Time to AFP (hazard ratio [HR] 0.513; p < 0.0001) and radiographic (HR 0.549; p < 0.0001) progression favoured ramucirumab. Association between AFP and radiographic progression was shown for up to 6 (odds ratio [OR] 5.1; p < 0.0001) and 6–12 weeks (OR 1.8; p = 0.0065). AFP response was higher with ramucirumab vs. placebo (p < 0.0001). Survival was longer in patients with an AFP response than patients without (13.6 vs. 5.6 months, HR 0.451; 95% confidence interval, 0.354–0.574; p < 0.0001). Conclusions AFP is an important prognostic factor and a predictive biomarker for ramucirumab survival benefit. AFP ≥ 400 ng/ml is an appropriate selection criterion for ramucirumab. Clinical Trial Registration ClinicalTrials.gov, REACH (NCT01140347) and REACH-2 (NCT02435433).

scholarly journals Effects of User Interfaces on Take-Over Performance: A Review of the Empirical Evidence

Information ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 162
Author(s):  
Soyeon Kim ◽  
René van Egmond ◽  
Riender Happee
Keyword(s):  
User Interface ◽  
Situation Awareness ◽  
User Interfaces ◽  
Situational Awareness ◽  
Selection Criterion ◽  
Auditory Modality ◽  
Automated Driving ◽  
Automated Vehicle ◽  
Positive Effects ◽  
High Urgency

In automated driving, the user interface plays an essential role in guiding transitions between automated and manual driving. This literature review identified 25 studies that explicitly studied the effectiveness of user interfaces in automated driving. Our main selection criterion was how the user interface (UI) affected take-over performance in higher automation levels allowing drivers to take their eyes off the road (SAE3 and SAE4). We categorized user interface (UI) factors from an automated vehicle-related information perspective. Short take-over times are consistently associated with take-over requests (TORs) initiated by the auditory modality with high urgency levels. On the other hand, take-over requests directly displayed on non-driving-related task devices and augmented reality do not affect take-over time. Additional explanations of take-over situation, surrounding and vehicle information while driving, and take-over guiding information were found to improve situational awareness. Hence, we conclude that advanced user interfaces can enhance the safety and acceptance of automated driving. Most studies showed positive effects of advanced UI, but a number of studies showed no significant benefits, and a few studies showed negative effects of advanced UI, which may be associated with information overload. The occurrence of positive and negative results of similar UI concepts in different studies highlights the need for systematic UI testing across driving conditions and driver characteristics. Our findings propose future UI studies of automated vehicle focusing on trust calibration and enhancing situation awareness in various scenarios.

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