Mask-guided Style Transfer Network for Purifying Real Images

Recently, the progress of learning-by-synthesis has proposed a training model for synthetic images, which can effectively reduce the cost of human and material resources. However, due to the different distribution of synthetic images compared with real images, the desired performance cannot be achieved. To solve this problem, the previous method learned a model to improve the realism of the synthetic images. Different from the previous methods, this paper try to purify real image by extracting discriminative and robust features to convert outdoor real images to indoor synthetic images. In this paper, we first introduce the segmentation masks to construct RGB-mask pairs as inputs, then we design a mask-guided style transfer network to learn style features separately from the attention and bkgd(background) regions and learn content features from full and attention region. Moreover, we propose a novel region-level task-guided loss to restrain the features learnt from style and content. Experiments were performed using mixed studies (qualitative and quantitative) methods to demonstrate the possibility of purifying real images in complex directions. We evaluate the proposed method on various public datasets, including LPW, COCO and MPIIGaze. Experimental results show that the proposed method is effective and achieves the state-of-the-art results.Comment: arXiv admin note: substantial text overlap with arXiv:1903.0582

An investigation into gender differences in participation in higher education among final year secondary school students in Cameroon

The importance of female education is gradually being recognised and gender equality in education has been promoted through different international commitments (e.g., EFA, MDGs and SDGs). However, in sub-Saharan Africa, educational gender inequality remains, and the higher education participation rate is still low. Cameroon, in particular, has a low higher education participation rate compared with developed countries, along with gender gaps in participation in higher education. Students, particularly female students, might face barriers to participation in higher education in Cameroon. Therefore, this study was designed to investigate barriers to participation in higher education in Cameroon for final year secondary school students, with a particular focus on gender differences. The conceptual framework for this study was based on the studies by Hyde (1993) and Gorard et al. (2007). Five types of barriers were discussed: economic barriers, socio-cultural barriers, institutional barriers, family barriers and personal barriers. This longitudinal study adopted an explanatory sequential mixed methods research design. In total, 1,975 questionnaires were collected with students from 14 schools in Cameroon, and 25 semi-structured interviews and 14 follow-up interviews were conducted. The questionnaire data was analysis through univariate, bivariate and multivariate analysis methods, interview data was analysis through thematic analysis. This study revealed no gender differences regarding students’ attitudes towards participation in higher education – both females and males were positive about continuing to higher education. However, their preferred higher education institutions and subject streams varied by gender. Parental and institutional factors were shown to be associated with students’ higher education attitudes and choices. Strong gender stereotyped views were revealed from the interviews, yet these did not influence their attitudes towards higher education, implying that education might have provided a ‘sanctuary’ place for those final year students and they were somewhat insulated from the gender-biased views of wider society. The results of this study suggest that, if females can remain in education longer, their aspirations to attend higher education will be similar to those of males. Therefore, one implication for policy makers is to intervene at earlier stages of education to ensure that females remain in the education system longer. Furthermore, the regional and institutional imbalance within Cameroon should also be dealt with by policy makers. Parents and students themselves should also change their mind sets and attitudes towards higher education

CellTradeMap: Delineating trade areas for urban commercial districts with cellular networks

Understanding customer mobility patterns to com-mercial districts is crucial for urban planning, facility manage-ment, and business strategies. Trade areas are a widely appliedmeasure to quantify where the visitors are from. Traditionaltrade area analysis is limited to small-scale or store-level studiesbecause information such as visits to competitor commercialentities and place of residence is collected by labour-intensivequestionnaires or heavily biased location-based social media data.In this paper, we propose CellTradeMap, a novel district-leveltrade area analysis framework using mobile flow records (MFRs),a type of fine-grained cellular network data. CellTradeMap ex-tracts robust location information from the irregularly sampled,noisy MFRs, adapts the generic trade area analysis frameworkto incorporate cellular data, and enhances the original trade areamodel with cellular-based features. We evaluate CellTradeMap ona large-scale cellular network dataset covering 3.5 million mobilephone users in a metropolis in China. Experimental results showthat the trade areas extracted by CellTradeMap are aligned withdomain knowledge and CellTradeMap can model trade areaswith a high predictive accuracy

Evidence for a causal relationship between psoriasis and cutaneous melanoma: a bidirectional two-sample Mendelian randomized study

Background and objectiveExisting cross-sectional and retrospective studies were unable to establish a causal relationship between psoriasis and cutaneous melanoma (CM). We sought to evaluate the causal role between psoriasis and CM.MethodsWe performed a bidirectional two-sample Mendelian randomization analysis using summary statistics from genome-wide association studies of psoriasis and CM among individuals of predominantly European ancestry. Mendelian randomization–Egger regression, inverse variance weighting, Mendelian Randomization Pleiotropy RESidual Sum and Outlier, weighted mode, and weighted median were used to examine the causal effect between psoriasis and CM.ResultsGenetically predicted psoriasis was a significant risk factor for CM (odds ratio, 1.69; 95% confidence interval, 1.15–2.48; P = 0.025). In contrast, no association was observed between genetically predicted CM and psoriasis.ConclusionOur findings corroborated the existence of genetically predicted psoriasis increases risk of CM. Enhanced early screening of cutaneous melanoma in patients with psoriasis may improve clinical burden. However, we did not find evidence for a causal link from CM to psoriasis, so further studies are required to elucidate the effect of CM activity on psoriasis