Optimization for software release and crash

Software testing is a process to detect faults in the completeness and quality of developed computer software. Testing is a key process in assuring quality by identifying defects in software, and possibly fixing them, before it is delivered to end-users. A major decision to make during this software testing is, to determine whether to continue testing and eventually releasing the software, or when to stop the test and ‘crash’ it. Such a decision needs to be made to optimally balance the tradeoff between the cost of development and the reliability of the software. In this paper, a new optimal strategy is developed based on a conditional non-homogeneous Poisson process (Conditional-NHPP) on a continuous time horizon to determine when the optimal time is to release or crash the software

Evaluation of five dry particle deposition parameterizations for incorporation into atmospheric transport models

Despite considerable effort to develop mechanistic dry particle deposition parameterizations for atmospheric transport models, current knowledge has been inadequate to propose quantitative measures of the relative performance of available parameterizations. In this study, we evaluated the performance of five dry particle deposition parameterizations developed by Zhang et al. (2001) ( Z01 ), Petroff and Zhang (2010) ( PZ10 ), Kouznetsov and Sofiev (2012) ( KS12 ), Zhang and He (2014) ( ZH14 ), and Zhang and Shao (2014) ( ZS14 ), respectively. The evaluation was performed in three dimensions: model ability to reproduce observed deposition velocities, Vd (accuracy); the influence of imprecision in input parameter values on the modeled Vd (uncertainty); and identification of the most influential parameter( s) (sensitivity). The accuracy of the modeled Vd was evaluated using observations obtained from five land use categories (LUCs): grass, coniferous and deciduous forests, natural water, and ice/snow. To ascertain the uncertainty in modeled Vd, and quantify the influence of imprecision in key model input parameters, a Monte Carlo uncertainty analysis was performed. The Sobol\u27 sensitivity analysis was conducted with the objective to determine the parameter ranking from the most to the least influential. Comparing the normalized mean bias factors (indicators of accuracy), we find that the ZH14 parameterization is the most accurate for all LUCs except for coniferous forest, for which it is second most accurate. From Monte Carlo simulations, the estimated mean normalized uncertainties in the modeled Vd obtained for seven particle sizes (ranging from 0.005 to 2.5 μm) for the five LUCs are 17, 12, 13, 16, and 27% for the Z01, PZ10, KS12, ZH14, and ZS14 parameterizations, respectively. From the Sobol\u27 sensitivity results, we suggest that the parameter rankings vary by particle size and LUC for a given parameterization. Overall, for dp D0.001 to 1.0 μm, friction velocity was one of the three most influential parameters in all parameterizations. For giant particles (dp D10 μm), relative humidity was the most influential parameter. Because it is the least complex of the five parameterizations, and it has the greatest accuracy and least uncertainty, we propose that the ZH14 parameterization is currently superior for incorporation into atmospheric transport models

Opinion of fishermen towards their well-being under Agricultural Diversification and Intensification Project (ADIP) in Bangladesh

Agricultural Diversification and intensification Project (ADIP) was the collaborative program of the Government of Bangladesh (GOB ) and donor agencies. The program was implemented in four district of Bangladesh in order to upgrade the living-standard of the poor people who were engaged in agricultural activities. This study took the initiative to assess the impact of microcredit on the living-standard in terms of household expenditure of the borrowers under ADIP’s fishery program. Primary data was collected from landless and marginal borrowers through a simple random sampling technique from the project areas who took loan for the first time for fisheries activities. Weighted Least Square (WLS) technique was used to examine the influence of socioeconomic variables on the dependent variable “household total expenditure”. The study shows that six variables such as household’s income, years of schooling of the borrowers, training, investment on fishery activities, expenditure on food, distance of rural market from borrower’s dwelling place were significantly related to the household’s total expenditure. The study also indicates that the fishery credit did not have any significant influence on borrowers’ living-standard in terms of household’s total expenditure

Impact of COVID-19 pandemic on ride-hailing services based on large-scale Twitter data analysis

Ride-hailing services have gained popularity in recent years due to attributes such as reduced travel costs, traffic congestion, and emissions. However, with the impact of COVID-19, the ridehailing market is estimated to lose its fair share of an uprising as a transportation mode. During normal and critical circumstances, ride-hailing service users express their concerns, habits, and emotions through posting on social platforms such as Twitter. Hence, Twitter, as an emerging data source, is an effective and innovative digital platform to observe the rider\u27s behavior in ridehailing services. This study hydrates large-scale Twitter reactions related to shared mobility to perform comparative sentiment and emotion analysis to understand the impact of COVID-19 on transportation network services in pre-pandemic and during pandemic conditions. Amid pandemic, negative tweets (34%) associated with \u27sad\u27 (15%) and \u27anger\u27 (15%) emotions were most prevalent in the dataset

Impact of Audit Quality on Real Earnings Management: Moderating Role of Corporate Governance

Purpose: This study aims to examine the effectiveness of audit quality in restricting earnings management in the presence of country’s governance system. Methodology: The data was collected from 195 Pakistani-based and 150 UK based non-financial companies. The sampling period is ten years from 2010 to 2019. To test the hypotheses, the Generalized Method of Moments was applied. Findings: The results showed that firms switch from accrual earnings management to real earnings management in developed economies which are characterized by strong governance mechanism. Moreover, the negative association between governance mechanism and earnings management is increased in the presence of Big-4 auditor. Conclusion: It is concluded that audit quality restricts the firms to use real earnings management especially in those countries where governance mechanism is strong

A Review of Contact Tracing Approaches for Controlling COVID-19 Pandemic

The year 2020 will always be in the history of mankind due to the deadly outbreak of COVID-19. Many people are already infected around the world due to the spreading of this novel coronavirus. The virus mainly replicates through close contacts, so there are no other alternatives than to keep social distance, use proper safety gear, and maintain self-quarantine. As a result, the growth of the virus has changed the lifestyle of every individual to a great extent. It is also compelling the Governments to dictate strict lock-downs of the highly affected areas, impose work-from-home approaches where applicable, enforce strict social distancing standards, and so on. Some of the countries are also using smartphonebased applications for contact tracing to track the possibly infected individuals. However, there is a lot of discussion around the world about these contact tracing applications and also about their architecture, attribute, data privacy, and so on. In this paper, we have provided a comprehensive review of these contact tracing approaches in terms of their system architecture, key attributes, and data privacy. We have also outlined a list of potential research directions that can improvise the tracing performance while maintaining the privacy of the user to a great extent