scholarly journals A Novel Technique for Duplicate Detection and Classification of Bug Reports

2014 ◽  
Vol E97.D (7) ◽  
pp. 1756-1768
Author(s):  
Tao ZHANG ◽  
Byungjeong LEE
Keyword(s):  
Duplicate Detection ◽  
Novel Technique ◽  
Bug Reports

scholarly journals A Novel Technique for Mapping the Vascularity of Labia Minora Prior to Labiaplasty: Cold Light Illumination

2018 ◽  
Vol 78 (08) ◽  
pp. 775-784 ◽  
Author(s):  
Aski Kaya ◽  
Ozan Dogan ◽  
Murat Yassa ◽  
Alper Basbug ◽  
Eray Çalışkan
Keyword(s):  
Light Source ◽  
Outer Surface ◽  
Descriptive Study ◽  
Light Illumination ◽  
Labia Minora ◽  
Novel Technique ◽  
Group A ◽  
The Right ◽  
Upper Third

Abstract Objective Aim of the study was to assess the feasibility of a novel technique to determine the vascularity of labia minora prior to labiaplasty. Methods A cold light source employed in laparoscopic procedures was used to illuminate the outer surface of the labia minora as described in this prospective descriptive study. Results Of the patients, 46.1% (n = 41) had upper third prominence, 36% (n = 32) had middle third prominence, and 18% (n = 16) had lower third prominence according to the Banwell classification of morphologies. Right labia minora width was 0 – 2 cm in 51.7% (n = 46), 2 – 4 cm in 47.2% (n = 42) and > 4 cm in 1.1% (n = 1) of cases. Left labia minora width was 0 – 2 cm in 52.8% (n = 47), 2 – 4 cm in 41.6% (n = 37) and > 4 cm in 5.6% (n = 5) of cases. The incidence of Anterior 2 and Posterior 1 vessels in the different morphologies were statistically significantly different (p = 0.007, p = 0.018). The Anterior 2 vessel was higher in the lower morphology group whereas the Posterior 1 vessel was higher in the upper morphology group. A central vessel was observed in 93.3% (n = 83) of patients in the left labium minus and the right labium minus. The incidence of the Posterior 1 vessel was significantly higher in the left labium minus than in the right labium minus (p = 0.021). Discussion This novel technique to assess labial vascularity using a cold light source could be very useful to reduce dehiscence by avoiding excessive resection of highly vascularized tissue. Most units can easily access a cold light source, which can be used to assess labial vascularity prior to labiaplasty.

Prediction of Railroad Track Foundation Defects Using Wavelets

2013 ◽  
Author(s):  
Kuya Takami ◽  
Saied Taheri ◽  
Mehdi Taheri ◽  
Tomonari Furukawa
Keyword(s):  
Dynamic Simulation ◽  
Defect Detection ◽  
Detection Algorithm ◽  
Monitoring Systems ◽  
Railroad Track ◽  
Novel Technique ◽  
Accelerometer Signal ◽  
Further Development ◽  
Track Monitoring

This paper presents a novel technique that utilizes wavelet analysis to identify and predict the defects in railroad foundations and rails to prevent derailment or other damages. The proposed defect detection algorithm eliminates the use of wheel and/or track monitoring systems, which are expensive and time inefficient. The algorithm has been validated for the rail crack prediction using only vertical accelerometer signal which accurately detects impending rail breakage while distinguishing the signal generated by special track components such as rail joins and switches. Since the algorithm is flexible, further development can be tailored to detect significantly different rail defects such as track shift and other rail foundation defects. The algorithm is further improved by incorporating SIMPACK dynamic simulation to assist classification of the acceleration signatures. The actual data was then compared to simulation in order to validate the effectiveness of the algorithm.

scholarly journals Introducing a new method for classifying skull shape abnormalities related to craniosynostosis

2020 ◽  
Vol 179 (10) ◽  
pp. 1569-1577 ◽  
Author(s):  
Otto D. M. Kronig ◽  
Sophia A. J. Kronig ◽  
Henri A. Vrooman ◽  
Jifke F. Veenland ◽  
Mariëlle Jippes ◽  
...  
Keyword(s):  
Intraclass Correlation ◽  
Ct Scans ◽  
Surface Rendering ◽  
Characteristic Curves ◽  
Novel Technique ◽  
Anterior Plagiocephaly ◽  
Interclass Correlation ◽  
3D Photogrammetry ◽  
Repeatability And Reproducibility

Abstract We present a novel technique for classification of skull deformities due to most common craniosynostosis. We included 5 children of every group of the common craniosynostoses (scaphocephaly, brachycephaly, trigonocephaly, and right- and left-sided anterior plagiocephaly) and additionally 5 controls. Our outline-based classification method is described, using the software programs OsiriX, MeVisLab, and Matlab. These programs were used to identify chosen landmarks (porion and exocanthion), create a base plane and a plane at 4 cm, segment outlines, and plot resulting graphs. We measured repeatability and reproducibility, and mean curves of groups were analyzed. All raters achieved excellent intraclass correlation scores (0.994–1.000) and interclass correlation scores (0.989–1.000) for identifying the external landmarks. Controls, scaphocephaly, trigonocephaly, and brachycephaly all have the peak of the forehead in the middle of the curve (180°). In contrary, in anterior plagiocephaly, the peak is shifted (to the left of graph in right-sided and vice versa). Additionally, controls, scaphocephaly, and trigonocephaly have a high peak of the forehead; scaphocephaly has the lowest troughs; in brachycephaly, the width/frontal peak ratio has the highest value with a low frontal peak. Conclusion: We introduced a preliminary study showing an objective and reproducible methodology using CT scans for the analysis of craniosynostosis and potential application of our method to 3D photogrammetry. What is Known:• Diagnosis of craniosynostosis is relatively simple; however, classification of craniosynostosis is difficult and current techniques are not widely applicable. What is New:• We introduce a novel technique for classification of skull deformities due to craniosynostosis, an objective and reproducible methodology using CT scans resulting in characteristic curves. The method is applicable to all 3D-surface rendering techniques.• Using external landmarks and curve analysis, specific and characteristic curves for every type of craniosynostosis related to the specific skull deformities are found.

scholarly journals An HMM-based approach for automatic detection and classification of duplicate bug reports

2019 ◽  
Vol 113 ◽  
pp. 98-109 ◽  
Author(s):  
Neda Ebrahimi ◽  
Abdelaziz Trabelsi ◽  
Md. Shariful Islam ◽  
Abdelwahab Hamou-Lhadj ◽  
Kobra Khanmohammadi
Keyword(s):  
Automatic Detection ◽  
Bug Reports ◽  
Duplicate Bug Reports

scholarly journals A NOVEL TECHNIQUE FOR CLASSIFICATION OF MYOELECTRIC SIGNALS FOR PROSTHESIS

2002 ◽  
Vol 35 (1) ◽  
pp. 447-451 ◽  
Author(s):  
B. Karlik ◽  
M.O. Tokhi ◽  
M. Alci
Keyword(s):  
Myoelectric Signals ◽  
Novel Technique

MULTI-CLUSTER SUPPORT VECTOR MACHINE CLASSIFIER FOR THE CLASSIFICATION OF SUSPICIOUS AREAS IN DIGITAL MAMMOGRAMS

2011 ◽  
Vol 10 (04) ◽  
pp. 481-494 ◽  
Author(s):  
PETER MC LEOD ◽  
BRIJESH VERMA
Keyword(s):  
Support Vector Machine ◽  
Support Vector Machine Classifier ◽  
Screening Mammography ◽  
Support Vector ◽  
Svm Classifier ◽  
Anova Analysis ◽  
Novel Technique ◽  
Digital Database ◽  
Benchmark Database

This paper presents a novel technique for the classification of suspicious areas in digital mammograms. The proposed technique is based on clustering of input data into numerous clusters and amalgamating them with a Support Vector Machine (SVM) classifier. The technique is called multi-cluster support vector machine (MCSVM) and is designed to provide a fast converging technique with good generalization abilities leading to an improved classification as a benign or malignant class. The proposed MCSVM technique has been evaluated on data from the Digital Database of Screening Mammography (DDSM) benchmark database. The experimental results showed that the proposed MCSVM classifier achieves better results than standard SVM. A paired t-test and Anova analysis showed that the results are statistically significant.

Predicting Bug Priority Using Topic Modelling in Imbalanced Learning Environments

2021 ◽  
Vol 11 (1) ◽  
pp. 31-42
Author(s):  
Jayalath Bandara Ekanayake
Keyword(s):  
Logistic Regression ◽  
Decision Tree ◽  
Prediction Models ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Potential Candidate ◽  
Priority Level ◽  
Bug Reports ◽  
Manual Classification

Manual classification of bug reports is time-consuming as the reports are received in large quantities. Alternatively, this project proposed automatic bug prediction models to classify the bug reports. The topics or the candidate keywords are mined from the developer description in bug reports using RAKE algorithm and converted into attributes. These attributes together with the target attribute—priority level—construct the training datasets. Naïve Bayes, logistic regression, and decision tree learner algorithms are trained, and the prediction quality was measured using area under recursive operative characteristics curves (AUC) as AUC does not consider the biasness in datasets. The logistics regression model outperforms the other two models providing the accuracy of 0.86 AUC whereas the naïve Bayes and the decision tree learner recorded 0.79 AUC and 0.81 AUC, respectively. The bugs can be classified without developer involvement and logistic regression is also a potential candidate as naïve Bayes for bug classification.

Efficient and Effective Duplicate Detection in Hierarchical Data

2020 ◽  
Vol 17 (8) ◽  
pp. 3548-3552
Author(s):  
M. S. Roobini ◽  
P. B. S. Sumanth Kumar ◽  
P. B. Raviteja Reddy ◽  
Anitha Ponraj ◽  
J. Aruna
Keyword(s):  
High Accuracy ◽  
Cutting Edge ◽  
Hierarchical Data ◽  
Copy Detection ◽  
Bayesian Algorithm ◽  
Social Data ◽  
Xml Data ◽  
Duplicate Detection ◽  
Novel Technique

Although there is a long profession on distinguishing duplicates, just a handful in social data arrangements center around copy detection in ever more complex progressive systems, including XML data. Right now, present a novel technique for XML duplicate discovery, Renamed XMLDup. XMLDup utilizes a Bayesian algorithm defining the chance of duplicating two XML components, taking into account the data within the components, but also how data is structured. Likewise, to improve the effectiveness of Unit Review, Novel technique for pruning, equipped for noteworthy increases over the un-streamlined calculation rule, is introduced. We demonstrate through trials that our estimate is can accomplish high accuracy via trials we show our estimation is outflanking another cutting-edge duplicate discovery arrangement, both as far as proficiency and of adequacy.

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