scholarly journals PENGARUH THRUST DEDUCTION FACTOR DAN WAKE FRACTION TERHADAP EFISIENSI PROPULSI AKIBAT PERUBAHAN DRAFT KAPAL

2021 ◽  
Vol 15 (1) ◽  
pp. 21-30
Author(s):  
Muhammad Sawal Baital Baital ◽  
Kusnindar Priohutomo ◽  
Jatmika Prajayastanda ◽  
Solichin Djazuli Sa'id
Keyword(s):  
Test Data ◽  
Theoretical Approach ◽  
Characteristic Curve ◽  
Data Series ◽  
Propulsion Efficiency ◽  
Using Data ◽  
Fixed Pitch

This study is to investigate propulsion efficiency due to changes in draught of ship using data series and theoretical approach. A hard chain rescue boat with triplet screw was used for the study and to examine the effect of thrust deduction factor and wake fraction due to changes in draught of ship and its relevance to propulsion efficiency by observing hull and propeller interaction based on openwater test by Wageningen Data Series with cavitations analysis has been neglected. The study is done using hydrodynamics analysis for planning hull and using intersection between thrust characteristic curve with openwater test data series for fixed pitch propeller. The result indicated that the changes in ship draught are very influential on the changes in thrust deduction factor and wake fraction value which is one of the contributing factor to change the propulsion efficiency value 1% - 5%.

ANALISA ENGINE PROPELLER MATCHING (EPM) PADA KAPAL RESCUE BOAT KARENA PERUBAHAN TAHAP POWERING PROCESS

2020 ◽  
Vol 21 (1) ◽  
pp. 49-55
Author(s):  
Muhammad Sawal Baital ◽  
Ari Bawono Putranto ◽  
Bambang Sri Waluyo
Keyword(s):  
Theoretical Approach ◽  
Open Water ◽  
Data Series ◽  
Water Efficiency ◽  
Thrust Coefficient ◽  
Process Stage ◽  
Propeller Design ◽  
Main Engine ◽  
Propeller Thrust ◽  
Fixed Pitch

This study is to investigate compatibility between installed main engine in ship with propeller design using theoretical approach and data series. A triple screw rescue boat conducted hard chain hull was used for study and analyze the effect of the changes in powering process stage by observing the result of open water efficiency based on Wageningen Data Series with cavitation analysis has been neglected. The study is considered using intersection between propeller thrust with thrust coefficient and open water efficiency on Wageningen B-Series for fixed pitch propeller. The result indicated that propeller characteristic B5-76 with 41% of efficiency  has compatibility with specification of installed main engine.

The Attention Economy and Esports: An Econometric Analysis of Twitch Viewership

2021 ◽  
pp. 1-14
Author(s):  
Nicholas M. Watanabe ◽  
Hanhan Xue ◽  
Joshua I. Newman ◽  
Grace Yan
Keyword(s):  
Theoretical Approach ◽  
Econometric Analysis ◽  
Scarce Resource ◽  
Structural Factors ◽  
Sport Organizations ◽  
Economic Framework ◽  
Attention Economy ◽  
Growing Body ◽  
And Behaviors ◽  
Using Data

With the expansion of the esports industry, there is a growing body of literature examining the motivations and behaviors of consumers and participants. The current study advances this line of research by considering esports consumption through an economic framework, which has been underutilized in this context. Specifically, the “attention economy” is introduced as a theoretical approach—which operates with the understanding that due to increased connectivity and availability of information, it is the attention of consumers that becomes a scarce resource for which organizations must compete. Using data from the Twitch streaming platform, the results of econometric analysis further highlight the importance of structural factors in drawing attention from online viewers. As such, this research advances the theoretical and empirical understanding of online viewership behaviors, while also providing important ramifications for both esports and traditional sport organizations attempting to capture the attention of users in the digital realm.

scholarly journals Deep Learning Using Multiple Degrees of Maximum-Intensity Projection for PET/CT Image Classification in Breast Cancer

Tomography ◽  
2022 ◽  
Vol 8 (1) ◽  
pp. 131-141
Author(s):  
Kanae Takahashi ◽  
Tomoyuki Fujioka ◽  
Jun Oyama ◽  
Mio Mori ◽  
Emi Yamaga ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Deep Learning ◽  
Image Classification ◽  
Test Data ◽  
Characteristic Curve ◽  
Maximum Intensity Projection ◽  
Maximum Intensity ◽  
Training Data ◽  
Ct Image ◽  
Pet Ct

Deep learning (DL) has become a remarkably powerful tool for image processing recently. However, the usefulness of DL in positron emission tomography (PET)/computed tomography (CT) for breast cancer (BC) has been insufficiently studied. This study investigated whether a DL model using images with multiple degrees of PET maximum-intensity projection (MIP) images contributes to increase diagnostic accuracy for PET/CT image classification in BC. We retrospectively gathered 400 images of 200 BC and 200 non-BC patients for training data. For each image, we obtained PET MIP images with four different degrees (0°, 30°, 60°, 90°) and made two DL models using Xception. One DL model diagnosed BC with only 0-degree MIP and the other used four different degrees. After training phases, our DL models analyzed test data including 50 BC and 50 non-BC patients. Five radiologists interpreted these test data. Sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were calculated. Our 4-degree model, 0-degree model, and radiologists had a sensitivity of 96%, 82%, and 80–98% and a specificity of 80%, 88%, and 76–92%, respectively. Our 4-degree model had equal or better diagnostic performance compared with that of the radiologists (AUC = 0.936 and 0.872–0.967, p = 0.036–0.405). A DL model similar to our 4-degree model may lead to help radiologists in their diagnostic work in the future.

scholarly journals Illegal Police Protection and the Market for Stolen Vehicles in Buenos Aires

2012 ◽  
Vol 44 (4) ◽  
pp. 679-702 ◽  
Author(s):  
MATÍAS DEWEY
Keyword(s):  
Theoretical Approach ◽  
Buenos Aires ◽  
Vehicle Theft ◽  
The Public ◽  
Role Of The State ◽  
Auto Parts ◽  
Police Protection ◽  
Using Data ◽  
Depth Interviews

AbstractIn comparison to some illegal enterprises whose operations generate decisive moral rejection on the part of the public, vehicle theft remains an illicit underground activity that citizens largely tolerate or even exploit. In the province of Buenos Aires, the persistence, depth and breadth of transactions related to this black market cannot be explained without referring to the role of the state police. This article uses a theoretical approach to illegal police protection in order to understand the complicity between the police and criminals as fundamental to the market for stolen cars in the province. Using data from in-depth interviews and official documents, the article examines how exactly the police protect thieves, dismantlers and distributors of cars and/or auto parts. It analyses three elements that condition the sale of illegal protection to criminals by the police: threats and selective implementation of penalties; control of consequences; and bureaucratic falsification.

Diagnostic assessment of a deep learning system for detecting atrial fibrillation in pulse waveforms

Heart ◽  
2018 ◽  
Vol 104 (23) ◽  
pp. 1921-1928 ◽  
Author(s):  
Ming-Zher Poh ◽  
Yukkee Cheung Poh ◽  
Pak-Hei Chan ◽  
Chun-Ka Wong ◽  
Louise Pun ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Deep Learning ◽  
Test Data ◽  
Predictive Value ◽  
Characteristic Curve ◽  
Performance Comparison ◽  
Learning System ◽  
Training Data ◽  
Validation Data ◽  
Data Set

ObjectiveTo evaluate the diagnostic performance of a deep learning system for automated detection of atrial fibrillation (AF) in photoplethysmographic (PPG) pulse waveforms.MethodsWe trained a deep convolutional neural network (DCNN) to detect AF in 17 s PPG waveforms using a training data set of 149 048 PPG waveforms constructed from several publicly available PPG databases. The DCNN was validated using an independent test data set of 3039 smartphone-acquired PPG waveforms from adults at high risk of AF at a general outpatient clinic against ECG tracings reviewed by two cardiologists. Six established AF detectors based on handcrafted features were evaluated on the same test data set for performance comparison.ResultsIn the validation data set (3039 PPG waveforms) consisting of three sequential PPG waveforms from 1013 participants (mean (SD) age, 68.4 (12.2) years; 46.8% men), the prevalence of AF was 2.8%. The area under the receiver operating characteristic curve (AUC) of the DCNN for AF detection was 0.997 (95% CI 0.996 to 0.999) and was significantly higher than all the other AF detectors (AUC range: 0.924–0.985). The sensitivity of the DCNN was 95.2% (95% CI 88.3% to 98.7%), specificity was 99.0% (95% CI 98.6% to 99.3%), positive predictive value (PPV) was 72.7% (95% CI 65.1% to 79.3%) and negative predictive value (NPV) was 99.9% (95% CI 99.7% to 100%) using a single 17 s PPG waveform. Using the three sequential PPG waveforms in combination (<1 min in total), the sensitivity was 100.0% (95% CI 87.7% to 100%), specificity was 99.6% (95% CI 99.0% to 99.9%), PPV was 87.5% (95% CI 72.5% to 94.9%) and NPV was 100% (95% CI 99.4% to 100%).ConclusionsIn this evaluation of PPG waveforms from adults screened for AF in a real-world primary care setting, the DCNN had high sensitivity, specificity, PPV and NPV for detecting AF, outperforming other state-of-the-art methods based on handcrafted features.

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