Precision and Recall for Time Series

Classical anomaly detection is principally concerned with point-based anomalies, those anomalies that occur at a single point in time. Yet, many real-world anomalies are range-based, meaning they occur over a period of time. Motivated by this observation, we present a new mathematical model to evaluate the accuracy of time series classification algorithms. Our model expands the well-known Precision and Recall metrics to measure ranges, while simultaneously enabling customization support for domain-specific preferences

A Zero-Positive Learning Approach for Diagnosing Software Performance Regressions

The field of machine programming (MP), the automation of the development of software, is making notable research advances. This is, in part, due to the emergence of a wide range of novel techniques in machine learning. In this paper, we apply MP to the automation of software performance regression testing. A performance regression is a software performance degradation caused by a code change. We present AutoPerf–a novel approach to automate regression testing that utilizes three core techniques:(i) zero-positive learning,(ii) autoencoders, and (iii) hardware telemetry. We demonstrate AutoPerf’s generality and efficacy against 3 types of performance regressions across 10 real performance bugs in 7 benchmark and open-source programs. On average, AutoPerf exhibits 4% profiling overhead and accurately diagnoses more performance bugs than prior state-of-the-art approaches. Thus far, AutoPerf has produced no false negatives

Prevalence and multidrug resistance pattern of Salmonella isolated from resident wild birds of Bangladesh

Aim: Salmonellosis is one of the most common zoonotic diseases, and the presence of antimicrobial resistant Salmonella in wild birds is global public health threat. Throughout the last decades, multidrug resistance of Salmonella spp. has increased, particularly in developing countries. Therefore, a cross-sectional study was conducted to investigate the prevalence of Salmonella spp. and antimicrobial resistance pattern against Salmonella spp. from two species of resident wild birds namely house crow (Corvus splendens) and Asian pied starling (Gracupica contra). Materials and Methods: Samples were collected from cloacal swabs of house crows and Asian pied starling for isolating Salmonella spp. (bacteriological culture methods) followed by antimicrobial susceptibility testing (disk diffusion method) against Salmonella spp. isolates during March to December 2014. Results: The prevalence of Salmonella in Asian pied starling and house crows were 67% and 65%, respectively. Within the category of samples from different species, the variation in prevalence was not varied significantly (p>0.05). Isolated Salmonella spp. was tested for resistance to six different antimicrobial agents. Among six antimicrobial tested, 100% resistance were found to penicillin, oxacillin, and clindamycin followed by erythromycin (50-93%), kanamycin (7-20%), and cephalothin (30-67%) from both species of birds. Kanamycin remained sensitive in (70-73%), cephalothin (26-70%), and erythromycin appeared to be (0-30%) sensitive against Salmonella spp. isolates. Isolated Salmonella spp. was multidrug resistant up to three of the six antimicrobials tested. Conclusion: It can be said that the rational use of antimicrobials needs to be adopted in the treatment of disease for livestock, poultry, and human of Bangladesh to limit the emergence of drug resistance to Salmonella spp