Analysis and Detection of Information Types of Open Source Software Issue Discussions

Most modern Issue Tracking Systems (ITSs) for open source software (OSS) projects allow users to add comments to issues. Over time, these comments accumulate into discussion threads embedded with rich information about the software project, which can potentially satisfy the diverse needs of OSS stakeholders. However, discovering and retrieving relevant information from the discussion threads is a challenging task, especially when the discussions are lengthy and the number of issues in ITSs are vast. In this paper, we address this challenge by identifying the information types presented in OSS issue discussions. Through qualitative content analysis of 15 complex issue threads across three projects hosted on GitHub, we uncovered 16 information types and created a labeled corpus containing 4656 sentences. Our investigation of supervised, automated classification techniques indicated that, when prior knowledge about the issue is available, Random Forest can effectively detect most sentence types using conversational features such as the sentence length and its position. When classifying sentences from new issues, Logistic Regression can yield satisfactory performance using textual features for certain information types, while falling short on others. Our work represents a nontrivial first step towards tools and techniques for identifying and obtaining the rich information recorded in the ITSs to support various software engineering activities and to satisfy the diverse needs of OSS stakeholders.Comment: 41st ACM/IEEE International Conference on Software Engineering (ICSE2019

RDD2022: A multi-national image dataset for automatic Road Damage Detection

The data article describes the Road Damage Dataset, RDD2022, which comprises 47,420 road images from six countries, Japan, India, the Czech Republic, Norway, the United States, and China. The images have been annotated with more than 55,000 instances of road damage. Four types of road damage, namely longitudinal cracks, transverse cracks, alligator cracks, and potholes, are captured in the dataset. The annotated dataset is envisioned for developing deep learning-based methods to detect and classify road damage automatically. The dataset has been released as a part of the Crowd sensing-based Road Damage Detection Challenge (CRDDC2022). The challenge CRDDC2022 invites researchers from across the globe to propose solutions for automatic road damage detection in multiple countries. The municipalities and road agencies may utilize the RDD2022 dataset, and the models trained using RDD2022 for low-cost automatic monitoring of road conditions. Further, computer vision and machine learning researchers may use the dataset to benchmark the performance of different algorithms for other image-based applications of the same type (classification, object detection, etc.).Comment: 16 pages, 20 figures, IEEE BigData Cup - Crowdsensing-based Road damage detection challenge (CRDDC'2022

Crowdsensing-based Road Damage Detection Challenge (CRDDC-2022)

This paper summarizes the Crowdsensing-based Road Damage Detection Challenge (CRDDC), a Big Data Cup organized as a part of the IEEE International Conference on Big Data'2022. The Big Data Cup challenges involve a released dataset and a well-defined problem with clear evaluation metrics. The challenges run on a data competition platform that maintains a real-time online evaluation system for the participants. In the presented case, the data constitute 47,420 road images collected from India, Japan, the Czech Republic, Norway, the United States, and China to propose methods for automatically detecting road damages in these countries. More than 60 teams from 19 countries registered for this competition. The submitted solutions were evaluated using five leaderboards based on performance for unseen test images from the aforementioned six countries. This paper encapsulates the top 11 solutions proposed by these teams. The best-performing model utilizes ensemble learning based on YOLO and Faster-RCNN series models to yield an F1 score of 76% for test data combined from all 6 countries. The paper concludes with a comparison of current and past challenges and provides direction for the future.Comment: 9 pages 2 figures 5 tables. arXiv admin note: text overlap with arXiv:2011.0874

Preserving the Natural Smile by Immediate Re-attachment of Fractured Tooth: Report of Two Cases

Abstract : Traumatic injuries are most common in maxillary anterior teeth which mainly affect the esthetics and function. This article describes the immediate reattachment of fractured tooth fragment for the restoration of function and esthetics at the emergency visit.These case reports describe immediate treatment of oblique crown root fracture of maxillary right lateral incisor, and mandibular left central incisor. By reattaching the natural tooth fragment in the first case the root canal treatment was done then after fractured fragment was reattached with the titanium post. While in the second case the tooth was previously root canal treated, in which titanium post was used to reattach the fractured fragment .Successful pain management with immediate restoration of function, esthetics, and phonetics was the prime objective when treating these cases

AI-Driven Road Condition Monitoring across Multiple Nations

The doctoral work summarized here is an application of Artificial Intelligence (AI) for social good. The successful implementation would contribute towards low-cost, faster monitoring of road conditions across different nations, resulting in safer roads for everyone. Additionally, the study provides recommendations for re-using the road image data and the Deep Learning models released by any country for detecting road damage in other countries

A Brief Review on Tejovati (Zanthoxyllum Armatum.Dc.) in Vedas and Samhita: An Ethnomedicinally Rich Plant

Medicinal plants are considered as a rich resources of ingredients which can be used in drug development either pharmacopoeial, non- pharmacopoeial or synthetic drugs. A part from that, these plants play a critical role in the development of human cultures around the world. Traditional Indian medicine (Ayurveda) is becoming increasingly popular, with many chronic conditions responding to it well. Most patients begin to take conventional medications as soon as their diagnoses are made, so Ayurvedic treatments are usually undergone alongside and/or after conventional medical approaches. WHO (World Health Organization) estimated that 80 percent of people worldwide rely on herbal medicines for some aspect of their primary health care needs. According to WHO, around 21,000 plant species have the potential for being used as medicinal plants. Elaborate description of the plant and its therapeutic action are explained by our Acharyas in Vedas, Puranas, and Samhitas and in the later Nighantus. Tejovati is such a drug which is widely available and is having many mentioning in the classics for its effectiveness in many diseases. Tejovati does not have any controversies in any of the literatures or classics regarding its identification or usage. The current article is to highlight the importance of drug and references has been collected from Vedas, Puranas, Samhita kala, Nighantu kala. Synonyms, Gana Varga, Vernacular names etc has been collected and arranged systematically

Color matching in facial prosthetics: A systematic review

Color matching to the surrounding skin is extremely important in patients wearing maxillofacial prostheses. It is of utmost importance to know the different techniques of color matching and coloring in maxillofacial prostheses. The purpose of this study is to review the literature data with regard to color matching in maxillofacial prosthetics. An electronic search of peer review restricted to English language dental literature was conducted to identify the relevant scientific article on color matching and coloring in maxillofacial prostheses. The publication year was up to December 2015 so that the search could include all the articles provided in that particular database. Two independent observers independently read the abstracts and later preselected full-text articles. A full-text review was carried out only for 15 articles. Out of the 15 articles, 7 were related to coloring using tinting, spraying, milling, and use of commercial cosmetics. Three studies were related to shade matching in maxillofacial prostheses. Two studies conducted the measurement of color in maxillofacial prostheses. Only one study had explained color and its relevance in maxillofacial prosthetics. Only one study was done for reproducing silicone shade guide matching Indian skin color. In addition, a single pilot study was done to measure facial skin and lip color in a human population sample stratified by race, gender, and age. Currently, there is no evidence discussing the best technique available for perfectly matching the color for the fabrication of maxillofacial prostheses. However, the latest instruments such as spectrophotometer and colorimeters are believed to have improved efficiency in matching the color