Memory Mountain Experiment Analysis

2021 ◽  
Author(s):  
Bo Sun
Keyword(s):  
Experiment Analysis

Nearshore Canyon Experiment: Analysis Surfzone Hole: Pilot

2006 ◽  
Author(s):  
Steve Elgar ◽  
Britt Raubenheimer ◽  
R. T. Guza
Keyword(s):  
Experiment Analysis

MATHURA (MBI) - A NOVEL IMPUTATION MEASURE FOR IMPUTATION OF MISSING VALUES IN MEDICAL DATASETS

2019 ◽  
Vol 13 ◽  
Author(s):  
B. Mathura Bai ◽  
N. Mangathayaru ◽  
B. Padmaja Rani ◽  
Shadi Aljawarneh
Keyword(s):  
Similarity Measure ◽  
Medical Records ◽  
Missing Values ◽  
Similarity Measures ◽  
Common Problems ◽  
Experiment Analysis

: Missing attribute values in medical datasets are one of the most common problems faced when mining medical datasets. Estimation of missing values is a major challenging task in pre-processing of datasets. Any wrong estimate of missing attribute values can lead to inefficient and improper classification thus resulting in lower classifier accuracies. Similarity measures play a key role during the imputation process. The use of an appropriate and better similarity measure can help to achieve better imputation and improved classification accuracies. This paper proposes a novel imputation measure for finding similarity between missing and non-missing instances in medical datasets. Experiments are carried by applying both the proposed imputation technique and popular benchmark existing imputation techniques. Classification is carried using KNN, J48, SMO and RBFN classifiers. Experiment analysis proved that after imputation of medical records using proposed imputation technique, the resulting classification accuracies reported by the classifiers KNN, J48 and SMO have improved when compared to other existing benchmark imputation techniques.

Experiment analysis of high output pressure piezoelectric pump with straight arm wheeled check valve

2021 ◽  
pp. 1045389X2098700
Author(s):  
Lipeng He ◽  
Xiaoqiang Wu ◽  
Zheng Zhang ◽  
Zhe Wang ◽  
Bangcheng Zhang ◽  
...  
Keyword(s):  
Chemical Analysis ◽  
Energy Loss ◽  
Check Valve ◽  
Experimental Results ◽  
Piezoelectric Pump ◽  
Output Pressure ◽  
Pressure Characteristic ◽  
Analysis System ◽  
Experiment Analysis ◽  
High Output

Piezoelectric pumps are applied in many fields, such as chemical analysis system and fluid pumping systems. Piezoelectric pumps with high output pressure can meet the needs of more fields. This article introduces the design and fabrication of a high output pressure piezoelectric pump with straight arm wheeled check valve. In this paper, the influence of straight arm wheeled check valve on the output pressure of piezoelectric pump is deeply discussed from the aspect of energy loss. This study investigated the effect of valve arm number ( N = 2, 3,4, and 5), the valve arm width ( W = 0.8, 1.0, and 1.2 mm), and the valve arm length ( L = 1.92, 2.02, and 2.12 mm) on the output pressure of piezoelectric pump. The output pressure characteristic of straight arm wheeled check valve piezoelectric pump with different valve parameters is obtained by experiment. Experimental results show that when N = 4, W = 1.0 mm, L = 2.02 mm, the output pressure of the straight arm wheeled check valve piezoelectric pump has the best output pressure of 27.41 kPa at 220 V and 85 Hz. This study provides a reference for the further application of piezoelectric pumps in fluid pumping field.

A Study on Carbon Electro-Conductive Filler for the Epoxy Conductive Coating

2011 ◽  
Vol 291-294 ◽  
pp. 41-46
Author(s):  
Bing Li ◽  
Yan Hong Li ◽  
Wen Xing Chen
Keyword(s):  
Carbon Black ◽  
Titanium Oxide ◽  
Epoxy Resins ◽  
Conductive Filler ◽  
Resistance Rate ◽  
Conductive Coating ◽  
Different Types ◽  
Optimal Mix ◽  
Oil Tank ◽  
Experiment Analysis

To ensure the use of oil tank safely, it is necessary that the conductive coating was used in inner oil tank. This paper concentrates on a study of the electrical properties (surface resistance rate) of epoxy resins filled with different types of carbon pigments, such as colloid graphite, carbon black and mixture of colloid graphite/carbon black, as well as on the investigation of some mechanical properties, appearance and morphology .To produce a light grey and conductive coating, titanium oxide and carbon electro-conductive pigments were investigated in this article. The objective of the experiment therefore was to choose the optimal electro-conductive filler and determine the optimal mix ratio of colloid graphite/ carbon black and titanium oxide /colloid graphite and titanium oxide /mixable electro-conductive filler. From the experiment analysis, it was found that the optimized colloid graphite and carbon black mix ratio is 3:1; the optimized titanium oxide and colloid graphite mix ratio is 1:1; the optimized titanium oxide and mixable electro-conductive filler mix ratio is 8:1. In terms of resistance rate and color, we may arrive at the conclusion that 15μm colloid graphite as the optimized electro- conductive pigments and the optimal mix ratio of titanium oxide /colloid graphite is 1:1.

Dynamics Analysis of Industrial Sewing Machine Frame Based on FEA and Modal Experiment

2013 ◽  
Vol 419 ◽  
pp. 122-126
Author(s):  
Li Zhang ◽  
Chen Kai ◽  
Xue Jiao Wang
Keyword(s):  
3D Model ◽  
Element Model ◽  
Impact Testing ◽  
Testing System ◽  
Dynamics Analysis ◽  
Sewing Machine ◽  
Good Consistency ◽  
The Finite Element Model ◽  
Experiment Analysis ◽  
Abaqus Software

The industrial sewing machine frame is one of the most important components of the sewing machine system, so studying its dynamic characteristics is particularly important. In this paper, based on the 3D model, the theory modal analysis of the industrial sewing machine is conducted with ABAQUS software and the modal experiment analysis is carried out through LMS(Lab Impact Testing system). The experimental results are in good consistency, which shows that the finite element model built in the paper is reasonable. This paper provides theoretical reference for vibration and noise reduction of the industrial sewing machine.

Orthogonal Experiment Analysis of Mechanical Thermal Conductivity on Multi-Component Fillers

2013 ◽  
Vol 753-755 ◽  
pp. 2379-2382
Author(s):  
Shi Meng Xu ◽  
Run Bo Ma ◽  
Jian Hua Du ◽  
Jun Hong Liu ◽  
Qi Jin
Keyword(s):  
Mechanical Properties ◽  
Thermal Conductivity ◽  
Carbon Black ◽  
Orthogonal Experiment ◽  
Experiment Design ◽  
Rubber Composites ◽  
Orthogonal Experiment Design ◽  
Rubber Composite ◽  
Al Powder ◽  
Experiment Analysis

Filled the N330 carbon black, silica T80 carbon black and Al powder and Fe2O3 magnetic nanoparticles, the rubber composites on multi-component electromagnetic fillers were prepared according to orthogonal experiment analysis, and the preliminary experiment conclusions of the filler prescription designs were given; Based on the experiment design, the mechanical properties and thermal conductivity of the rubber composite were tested, and the testing results were analyzed by using variance analysis. Thus, the paper shows that the effects of N330 on rubber mechanical properties are significant, and the effects of Al powder on the rubber thermal conductivity are significant. Moreover, it is highly emphasized in this paper that the orthogonal experiment design must be carefully explored before the tests are executed.

Functional Delineation of Prefrontal Networks Underlying Working Memory in Schizophrenia: A Cross-data-set Examination

2021 ◽  
pp. 1-29
Author(s):  
Nicole Sanford ◽  
Todd S. Woodward
Keyword(s):  
Working Memory ◽  
Mixed Model ◽  
Data Sets ◽  
Generation Task ◽  
Data Set ◽  
Set Switching ◽  
Dorsolateral Prefrontal ◽  
Task Conditions ◽  
Experiment Analysis ◽  
Internal Attention

Abstract Background: Working memory (WM) impairment in schizophrenia substantially impacts functional outcome. Although the dorsolateral pFC has been implicated in such impairment, a more comprehensive examination of brain networks comprising pFC is warranted. The present research used a whole-brain, multi-experiment analysis to delineate task-related networks comprising pFC. Activity was examined in schizophrenia patients across a variety of cognitive demands. Methods: One hundred schizophrenia patients and 102 healthy controls completed one of four fMRI tasks: a Sternberg verbal WM task, a visuospatial WM task, a Stroop set-switching task, and a thought generation task (TGT). Task-related networks were identified using multi-experiment constrained PCA for fMRI. Effects of task conditions and group differences were examined using mixed-model ANOVA on the task-related time series. Correlations between task performance and network engagement were also performed. Results: Four spatially and temporally distinct networks with pFC activation emerged and were postulated to subserve (1) internal attention, (2) auditory–motor attention, (3) motor responses, and (4) task energizing. The “energizing” network—engaged during WM encoding and diminished in patients—exhibited consistent trend relationships with WM capacity across different data sets. The dorsolateral-prefrontal-cortex-dominated “internal attention” network exhibited some evidence of hypoactivity in patients, but was not correlated with WM performance. Conclusions: Multi-experiment analysis allowed delineation of task-related, pFC-anchored networks across different cognitive constructs. Given the results with respect to the early-responding “energizing” network, WM deficits in schizophrenia may arise from disruption in the “energization” process described by Donald Stuss' model of pFC functions.

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