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As the functions of mobile applications become more and more complex, the crowdsourcing testing puts higher demands on the professional skills of testers. Therefore, it is an important factor to ensure test quality how to effectively match test task requirements with test personnel's skill level and achieve accurate crowdsourcing test task recommendation. This paper proposes a crowdsourcing test task recommendation algorithm for mobile applications based on deep learning. Firstly, feature analysis is carried out for testing tasks and testers, and feature systems are designed respectively. Second, the resulting characteristic data is used as input data for the Stacked Marginalized Denoising Autoencoder (SMDA). The deep feature data learned from SMDA are combined as the input of Deep Neural Networks (DNN). Finally, the learning ability of DNN is used for prediction. Experimental results show that the proposed algorithm has obvious advantages in both performance and training time compared with CDL and AUTOSVD ++, which verifies the effectiveness of the proposed algorithm. The proposed algorithm can recommend testing tasks to appropriate testers and improve the precision of the algorithm.

Objective To investigate the factors in frozen-thawed embryo transfer (FET) cycles that affecting the pregnancy outcome. Methods The clinical data of 1 169 couples who underwent FET in Shenzhen Maternity and Child Healthcare Hospital from January, 2017 to December, 2019 were retrospectively analyzed. Univariate analysis and Logistic multivariate regression analysis were performed to identify the factors which influence pregnancy outcome of FET cycles. Results The clinical pregnancy rate of 1 169 FET cycles was 50.13%. Univariate analysis showed that female patients ＞35 years old or infertility duration ＞ 6 years significantly had a reduced embryo implantation rate and clinical pregnancy rate (P＜0.01). But the embryo implantation rate and clinical pregnancy rate were increased by blastocyst or multiple embryos transfer (P＜0.01). Multiple embryo transplantation increased embryo implantation rate (P＜0.05) and endometrial thickness ＞12 mm increased clinical pregnancy rate (P＜0.05). Logistic multivariat regression analysis showed that elder age and decreasing number of optimal embryo transplantation were risk factors for clinical pregnancy rate (P＜0.01). Conclusions Patients age, embryo age and the number of transplanted embryos of high quality are the main factors affecting the pregnancy outcome of FET. Elder age is a risk factor for clinical pregnancy outcome.