Initial Placement and Analyst Performance

2010 ◽  
Author(s):  
Jess Cornaggia ◽  
Lin Zou
Keyword(s):  
Initial Placement

A Hybrid GSA-K-Mean Classifier Algorithm to Predict Diabetes Mellitus

2017 ◽  
Vol 8 (4) ◽  
pp. 99-112 ◽  
Author(s):  
Rojalina Priyadarshini ◽  
Rabindra Kumar Barik ◽  
Nilamadhab Dash ◽  
Brojo Kishore Mishra ◽  
Rachita Misra
Keyword(s):  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Cluster Head ◽  
Training Data ◽  
Learning Classifier ◽  
Initial Cluster ◽  
Positive Class ◽  
Initial Placement ◽  
Negative Class ◽  
Inherent Problem

Lots of research has been carried out globally to design a machine classifier which could predict it from some physical and bio-medical parameters. In this work a hybrid machine learning classifier has been proposed to design an artificial predictor to correctly classify diabetic and non-diabetic people. The classifier is an amalgamation of the widely used K-means algorithm and Gravitational search algorithm (GSA). GSA has been used as an optimization tool which will compute the best centroids from the two classes of training data; the positive class (who are diabetic) and negative class (who are non-diabetic). In K-means algorithm instead of using random samples as initial cluster head, the optimized centroids from GSA are used as the cluster centers. The inherent problem associated with k-means algorithm is the initial placement of cluster centers, which may cause convergence delay thereby degrading the overall performance. This problem is tried to overcome by using a combined GSA and K-means.

An Effective Cell Spreading Method for Force-Directed Global Placement

2014 ◽  
Vol 519-520 ◽  
pp. 911-918
Author(s):  
Xin Min Ma ◽  
Xu Qian ◽  
Wen Chao Gao
Keyword(s):  
Large Scale ◽  
Decisive Role ◽  
Cell Spreading ◽  
Fast Method ◽  
Wire Length ◽  
Additional Force ◽  
Large Scale Integration ◽  
Initial Placement ◽  
Scale Integration ◽  
Global Placement

Force-directed placement method for large scale integration physical design is a very effective and fast method to spread the cell uniformly in the placement region. But this kind of method also create large amount of cell overlap in initial placement. In this paper, we present an effective method to cope with cell spreading and add additional force without damaging the wire length. It mainly takes the following method: Firstly, in the prior period of iteration n we keep limit the cell moving distance using a rectangle structure .Because the prior iteration play a decisive role in the final placement quality. Secondly, after the cell relative order determined we can use a new method to compute the weight of additional force to accelerate converge. Thirdly, a strategy called iterative local refinement is added in the well-distributed placement to further reduce the total wire length.

scholarly journals 2452

2017 ◽  
Vol 1 (S1) ◽  
pp. 79-79
Author(s):  
Arnav Srivastava ◽  
Gregory Joice ◽  
Madeline Manka ◽  
Nikolai Sopko ◽  
Edward Jamie Wright
Keyword(s):  
Median Time ◽  
Cox Regression ◽  
Incidence Rates ◽  
Artificial Urinary Sphincter ◽  
Surgical Revision ◽  
Time To Failure ◽  
Surgical Morbidity ◽  
Urethral Erosion ◽  
Pump Failure ◽  
Initial Placement

OBJECTIVES/SPECIFIC AIMS: Stress urinary incontinence (SUI) significantly affects quality of life and occurs in 60% of men after radical prostatectomy, with 5% requiring surgical treatment. The artificial urinary sphincter (AUS) offers these patients excellent control of their post-prostatectomy SUI. The device contains 3 parts: the pump, urethral cuff, and pressure regulating balloon. Despite the effectiveness of AUS, up to 50% of patients require surgical revision after initial placement due to recurring SUI. Thus far, literature is heterogeneous regarding the causes of mechanical AUS failure and appropriate surgical management. Our study aims to characterize the most common reasons of AUS failure requiring surgical revision and the survival of each AUS component. METHODS/STUDY POPULATION: We report a series of 48 patients who received AUS placement and/or revision by 1 surgeon from 2010 to 2013. Upon presenting for revision, intraoperatively, the surgeon systematically evaluated the device for failure of the balloon, cuff and pump as well as urethral erosion and atrophy. In patients not requiring revision all device components were presumed functional. We conducted retrospective chart review to collect baseline characteristics, intraoperative findings, and postoperative outcomes. Using Kaplan-Meier estimates, we calculated incidence rates of component failure for the cuff, pump, and balloon. To identify risk factors for AUS failure, Cox regression was performed for univariate and multivariable testing. Multivariable modeling included those variables considered biologically plausible and significant in univariate testing. RESULTS/ANTICIPATED RESULTS: In total, 48 patients were studied with median follow up of 4.25 years. All patients received an AMS 800 device with a 61–70 mL balloon filled with 27 cc of isotonic contrast. Cuff sizes ranged from 3.5 to 5.5 cm, with 4.5 cm selected in 33/48 cases (68.8%); 19 of the patients required AUS correction (41.7%). Balloon leak constituted 57.9% (11/19) of failures, followed by cuff failure/urethral atrophy (21.1%), urethral erosion (10.5%), and individual cases of infection and pump failure. Median time to mechanical failure due to balloon leak was 3.67 years (IQR 2.17, 5.33); median time to failure for nonballoon causes was 0.54 years (IQR 0.25, 1.83). Survival of the balloon, cuff, and pump was 100%, 95.7%, and 97.9% at 1 year and 76.9%, 91.0%, and 97.9% at 5 years, respectively. DISCUSSION/SIGNIFICANCE OF IMPACT: Our study identifies fluid leakage from the balloon as the most common cause of AUS failure, particularly in patients presenting between 1 and 5 years after initial placement. For such patients, interrogating the balloon first can decrease infection risk and surgical morbidity as it can avoid manipulation of the urethral cuff. Furthermore, simply replacing lost fluid saves cost and allows for immediate reactivation of the AUS device.

scholarly journals A Randomized Controlled Trial Comparing Novel Triple-Cuffed Double-Lumen Endobronchial Tubes with Conventional Double-Lumen Endobronchial Tubes for Lung Isolation

2020 ◽  
Vol 9 (4) ◽  
pp. 977
Author(s):  
Namo Kim ◽  
Hyo-Jin Byon ◽  
Go Eun Kim ◽  
Chungon Park ◽  
Young Eun Joe ◽  
...  
Keyword(s):  
Controlled Trial ◽  
Fiberoptic Bronchoscopy ◽  
Lung Ventilation ◽  
One Lung Ventilation ◽  
Double Lumen ◽  
Lung Isolation ◽  
Significant Difference ◽  
Initial Placement ◽  
The Difference ◽  
Double Lumen Endobronchial Tube

Placing a double-lumen endobronchial tube (DLT) in an appropriate position to facilitate lung isolation is essential for thoracic procedures. The novel ANKOR DLT is a DLT developed with three cuffs with a newly added carinal cuff designed to prevent further advancement by being blocked by the carina when the cuff is inflated. In this prospective study, the direction and depth of initial placement of ANKOR DLT were compared with those of conventional DLT. Patients undergoing thoracic surgery (n = 190) with one-lung ventilation (OLV) were randomly allocated into either left-sided conventional DLT group (n = 95) or left-sided ANKOR DLT group (n = 95). The direction and depth of DLT position were compared via fiberoptic bronchoscopy (FOB) after endobronchial intubation between the groups. There was no significant difference in the number of right mainstem endobronchial intubations between the two groups (p = 0.468). The difference between the initial depth of DLT placement and the target depth confirmed by FOB was significantly lower in the ANKOR DLT group than in the conventional DLT group (1.8 ± 1.8 vs. 12.9 ± 9.7 mm; p < 0.001). In conclusion, the ANKOR DLT facilitated its initial positioning at the optimal depth compared to the conventional DLT.

A Fused Algorithm for Sovling VLSI Placement Problem

2013 ◽  
Vol 321-324 ◽  
pp. 404-407
Author(s):  
Ya Juan Zhang ◽  
Zong Xin Jin ◽  
Xue Chun Wang
Keyword(s):  
Ant Colony Algorithm ◽  
Simulated Annealing Algorithm ◽  
Placement Problem ◽  
Placement Optimization ◽  
Vlsi Physical Design ◽  
Random Optimization ◽  
Initial Placement ◽  
Iterative Improvement ◽  
Annealing Algorithm

Placement is the crucial step in modern VLSI physical design, and the result may decisively influence the follow-up wiring design. The advantages and limitations of the random optimization algorithm, ant colony algorithm, genetic algorithm, heuristic algorithm and simulated annealing algorithm which are used for placement optimization were analyzed in allusion to optimal search problems of VLSI placement. With a view to speedability of search, global convergence and the optimality of the solution, the initial placement is received through integrated use of all algorithms. In the meantime, the iterative improvement placement is realized by means of dynamic multi-branch tree. Practice has shown that the structure of the algorithm is clear, and it can also ensure the optimality of the received solution.

scholarly journals Effect of text message follow-up on patient's self-reported level of pain and anxiety

2012 ◽  
Vol 83 (4) ◽  
pp. 605-610 ◽  
Author(s):  
Daniel J. Keith ◽  
Daniel J. Rinchuse ◽  
Meghan Kennedy ◽  
Thomas Zullo
Keyword(s):  
Text Message ◽  
Control Group ◽  
Orthodontic Appliances ◽  
Patient Anxiety ◽  
Significant Difference ◽  
Initial Appointment ◽  
Orthodontic Patients ◽  
Initial Placement ◽  
Time Point

ABSTRACT Objectives: To determine whether a text message reduces the severity of patient self-reported levels of pain and anxiety following initial placement of orthodontic appliances. Materials and Methods: Thirty-nine orthodontic patients were randomly assigned to one of two groups and matched for age, gender, and bracket type (self-ligating vs conventional). The subjects completed baseline questionnaires to ascertain their levels of pain and anxiety before initiating orthodontic treatment. Following the initial appointment, subjects completed the pain questionnaire and anxiety inventory at the same time daily for 1 week. One group received a structured text message showing concern and reassurance, while the second group served as a control and received no postprocedural communication. Results: There was a statistically significant difference in pain in relation to time between the text message group and the control group as it was demonstrated that demonstrated that compared with the text message group, mean pain intensity increased and selfreported discomfort was longer in the control group. Anxiety was determined to be at its peak the day following initial orthodontic appliance placement and gradually tapered off from that time point. No intergroup difference was noted when analyzing anxiety. Conclusions: This study demonstrated that a text message sent from an orthodontic office following initial appliance placement resulted in a lower level of patient's self-reported pain. Additionally, patient anxiety is at its peak the day following the initial appointment and decreases from that point forward.

scholarly journals DETERMINISTIC INITIALIZATION OF THE K-MEANS ALGORITHM USING HIERARCHICAL CLUSTERING

2012 ◽  
Vol 26 (07) ◽  
pp. 1250018 ◽  
Author(s):  
M. EMRE CELEBI ◽  
HASSAN A. KINGRAVI
Keyword(s):  
Clustering Algorithm ◽  
Large Data ◽  
Large Data Sets ◽  
Data Sets ◽  
Partitional Clustering ◽  
Highly Sensitive ◽  
Data Points ◽  
Initial Placement ◽  
Random Initialization ◽  
Common Deficiency

K-means is undoubtedly the most widely used partitional clustering algorithm. Unfortunately, due to its gradient descent nature, this algorithm is highly sensitive to the initial placement of the cluster centers. Numerous initialization methods have been proposed to address this problem. Many of these methods, however, have superlinear complexity in the number of data points, making them impractical for large data sets. On the other hand, linear methods are often random and/or order-sensitive, which renders their results unrepeatable. Recently, Su and Dy proposed two highly successful hierarchical initialization methods named Var-Part and PCA-Part that are not only linear, but also deterministic (nonrandom) and order-invariant. In this paper, we propose a discriminant analysis based approach that addresses a common deficiency of these two methods. Experiments on a large and diverse collection of data sets from the UCI machine learning repository demonstrate that Var-Part and PCA-Part are highly competitive with one of the best random initialization methods to date, i.e. k-means++, and that the proposed approach significantly improves the performance of both hierarchical methods.

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