scholarly journals Marine Icing Sensor with Phase Discrimination

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 612
Author(s):  
Abdulrazak Elzaidi ◽  
Vlastimil Masek ◽  
Stephen Bruneau
Keyword(s):  
Signal Processing ◽  
Decision Tree ◽  
Decision Tree Model ◽  
Tree Model ◽  
Two Phase ◽  
Phase Layer ◽  
Phase Discrimination ◽  
Novel Approach ◽  
Signal Characteristics ◽  
Decision Tree Method

In this paper, a novel approach is presented to the measurement of marine icing phenomena under the presence of a two-phase condition. We have developed a sensor consisting of an electrostatic array and a signal processing based on a decision tree method. A three-element electrostatic array is employed to derive signals having linearly decoupled characteristics from which two key parameters, ice and water accretion layer dimension, can be determined for the purpose of environmental monitoring. The quantified characteristics revealed a correlation with the ice layer thickness in spite of the strong influence from the top water phase layer. The decision tree model established a relationship between the signal characteristics and the two accretion thickness parameters of water and ice layer. Through experimental verification, it has been observed that our sensor array in combination with the decision tree model based signal processing provides a simple practical solution to the challenging field of a two phase composition measurement such as in the marine icing considered in this study.

scholarly journals Common Metamodel of Questionnaire Model and Decision Tree Model

2018 ◽  
Vol 10 (3) ◽  
pp. 106
Author(s):  
Mirza Suljic ◽  
Edin Osmanbegovic ◽  
Željko Dobrović
Keyword(s):  
Decision Making ◽  
Decision Tree ◽  
Decision Trees ◽  
Decision Tree Model ◽  
Tree Model ◽  
Meta Model ◽  
The Subject ◽  
Decision Tree Method ◽  
Questionnaire Method ◽  
Tree Method

The subject of this paper is metamodeling and its application in the field of scientific research. The main goal is to explore the possibilities of integration of two methods: questionnaires and decision trees. The questionnaire method was established as one of the methods for data collecting, while the decision tree method represents an alternative way of presenting and analyzing decision making situations. These two methods are not completely independent, but on the contrary, there is a strong natural bond between them. Therefore, the result reveals a common meta-model that over common concepts and with the use of metamodeling connects the methods: questionnaires and decision trees. The obtained results can be used to create a CASE tool or create repository that can be suitable for exchange between different systems. The proposed meta-model is not necessarily the final product. It could be further developed by adding more entities that will keep some other data.

scholarly journals Analisa Expected Monetary Value Produksi Kapal Ikan Fiberglass Menggunakan Metode Decision Tree

2020 ◽  
Vol 4 (1) ◽  
pp. 63-69
Author(s):  
Romadhoni Romadhoni ◽  
Nurhasanah Nurhasanah
Keyword(s):  
Decision Tree ◽  
New Products ◽  
New Product ◽  
Decision Tree Model ◽  
Tree Model ◽  
Monetary Value ◽  
Decision Tree Method ◽  
Tree Method ◽  
Expected Monetary Value

To make decisions in the production of fiberglass vessels in traditional shipyards in Bengkalis Regency, it is necessary to carry out economic calculations using the Expected Monetary Value (EMV) method related to the production of fiberglass ships and wooden ships using the decision tree method. This is done to determine the chances of the producers succeeding or not with the development of fiberglass ship products, then some forecasting will be conducted on various possibilities that will occur. These possibilities will be formulated with a decision tree model so that producers will be able to decide whether the fiberglass ship product can be continued or only continue by running the old product, which is producing wooden ships. The results of this modeling can later become a reference for producers to look for further solutions if it turns out that after modeling new product results, the fiberglass ship has a greater chance of failure compared to its chances of success. Based on the results of modeling using the decision tree model, it is expected that the opportunity for producers to succeed with their new products, namely fiberglass ships, will be obtained. Keywords: EMV, Fiberglass, Decision Tree, economic

A Hybrid Decision Tree Model for Fast Voltage Contingency Screening and Ranking

2007 ◽  
Vol 8 (4) ◽  
Author(s):  
Narayan Prasad Patidar ◽  
Jaydev Sharma
Keyword(s):  
Decision Tree ◽  
Load Flow ◽  
Decision Tree Model ◽  
Tree Model ◽  
Contingency Screening ◽  
Energy Management Systems ◽  
On Line ◽  
Decision Tree Method ◽  
Bus Voltage ◽  
Testing Patterns

This paper presents a new decision tree (DT) based approach for fast voltage contingency screening and ranking for on-line applications in energy management systems. The hybrid decision tree model is developed to learn all the selected contingencies simultaneously, therefore fewer DTs are required. To reduce the size and improve the accuracy of the decision tree, the K-class problem is converted into the set of K two-class problems, and separate decision tree modules are trained for each of the two class problems. All the selected contingencies are presented to the filter module, which is trained to separate them in critical and non-critical contingency classes, which reduces the burden on ranking modular DT. The critical contingencies screened out by the filter module are presented to the ranking modular decision tree for their further ranking. To measure the severity of contingencies, bus voltage violation based scalar performance index is used. Full AC load flow is performed to generate the training and testing patterns for the proposed hybrid decision tree, under each contingency. The effectiveness of the proposed approach is tested on IEEE test systems. Once trained, a hybrid decision tree method gives fast and accurate screening and ranking of contingencies for unknown load patterns.

A novel enhanced decision tree model for detecting chronic kidney disease

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Avijit Kumar Chaudhuri ◽  
Deepankar Sinha ◽  
Dilip K. Banerjee ◽  
Anirban Das
Keyword(s):  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Decision Tree ◽  
Decision Tree Model ◽  
Tree Model

scholarly journals Risk of Pre-Malignancy or Malignancy in Postmenopausal Endometrial Polyps: A CHAID Decision Tree Analysis

Diagnostics ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1094
Author(s):  
Michael Wong ◽  
Nikolaos Thanatsis ◽  
Federica Nardelli ◽  
Tejal Amin ◽  
Davor Jurkovic
Keyword(s):  
Decision Tree ◽  
Expectant Management ◽  
Decision Tree Model ◽  
Decision Tree Analysis ◽  
Focal Lesions ◽  
Tree Model ◽  
Normal Endometrium ◽  
Endometrial Polyps ◽  
Tree Analysis ◽  
Interaction Detection

Background and aims: Postmenopausal endometrial polyps are commonly managed by surgical resection; however, expectant management may be considered for some women due to the presence of medical co-morbidities, failed hysteroscopies or patient’s preference. This study aimed to identify patient characteristics and ultrasound morphological features of polyps that could aid in the prediction of underlying pre-malignancy or malignancy in postmenopausal polyps. Methods: Women with consecutive postmenopausal polyps diagnosed on ultrasound and removed surgically were recruited between October 2015 to October 2018 prospectively. Polyps were defined on ultrasound as focal lesions with a regular outline, surrounded by normal endometrium. On Doppler examination, there was either a single feeder vessel or no detectable vascularity. Polyps were classified histologically as benign (including hyperplasia without atypia), pre-malignant (atypical hyperplasia), or malignant. A Chi-squared automatic interaction detection (CHAID) decision tree analysis was performed with a range of demographic, clinical, and ultrasound variables as independent, and the presence of pre-malignancy or malignancy in polyps as dependent variables. A 10-fold cross-validation method was used to estimate the model’s misclassification risk. Results: There were 240 women included, 181 of whom presented with postmenopausal bleeding. Their median age was 60 (range of 45–94); 18/240 (7.5%) women were diagnosed with pre-malignant or malignant polyps. In our decision tree model, the polyp mean diameter (≤13 mm or >13 mm) on ultrasound was the most important predictor of pre-malignancy or malignancy. If the tree was allowed to grow, the patient’s body mass index (BMI) and cystic/solid appearance of the polyp classified women further into low-risk (≤5%), intermediate-risk (>5%–≤20%), or high-risk (>20%) groups. Conclusions: Our decision tree model may serve as a guide to counsel women on the benefits and risks of surgery for postmenopausal endometrial polyps. It may also assist clinicians in prioritizing women for surgery according to their risk of malignancy.

scholarly journals Reanalysis and External Validation of a Decision Tree Model for Detecting Unrecognized Diabetes in Rural Chinese Individuals

2017 ◽  
Vol 2017 ◽  
pp. 1-6 ◽  
Author(s):  
Zhong Xin ◽  
Lin Hua ◽  
Xu-Hong Wang ◽  
Dong Zhao ◽  
Cai-Guo Yu ◽  
...  
Keyword(s):  
Decision Tree ◽  
Predictive Value ◽  
Early Stage ◽  
Current Model ◽  
External Validation ◽  
Area Under The Curve ◽  
Decision Tree Model ◽  
Tree Model ◽  
Chinese Adult ◽  
Significant Difference

We reanalyzed previous data to develop a more simplified decision tree model as a screening tool for unrecognized diabetes, using basic information in Beijing community health records. Then, the model was validated in another rural town. Only three non-laboratory-based risk factors (age, BMI, and presence of hypertension) with fewer branches were used in the new model. The sensitivity, specificity, positive predictive value, negative predictive value, and area under the curve (AUC) for detecting diabetes were calculated. The AUC values in internal and external validation groups were 0.708 and 0.629, respectively. Subjects with high risk of diabetes had significantly higher HOMA-IR, but no significant difference in HOMA-B was observed. This simple tool will help general practitioners and residents assess the risk of diabetes quickly and easily. This study also validates the strong associations of insulin resistance and early stage of diabetes, suggesting that more attention should be paid to the current model in rural Chinese adult populations.

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