No abstract

A mobile app interface usually consists of a set of user interface modules. How to properly design these user interface modules is vital to achieving user satisfaction for a mobile app. However, there are few methods to determine design variables for user interface modules except for relying on the judgment of designers. Usually, a laborious post-processing step is necessary to verify the key change of each design variable. Therefore, there is a only very limited amount of design solutions that can be tested. It is timeconsuming and almost impossible to figure out the best design solutions as there are many modules. To this end, we introduce FEELER, a framework to fast and intelligently explore design solutions of user interface modules with a collective machine learning approach. FEELER can help designers quantitatively measure the preference score of different design solutions, aiming to facilitate the designers to conveniently and quickly adjust user interface module. We conducted extensive experimental evaluations on two real-life datasets to demonstrate its applicability in real-life cases of user interface module design in the Baidu App, which is one of the most popular mobile apps in China.

In most coverless image steganography methods, the number of images increases exponentially with the increase of hidden message bits, which is difficult to construct such a dataset. And several images in semantic irrelevance are usually needed to represent more secret message bits, which are easy to cause the attacker’s attention and bring some insecurity. To solve these two problems, a coverless video steganography method based on inter frame combination is proposed in this manuscript. In the proposed method, the hash sequence of a frame is generated by the CNNs and hash generator. To hide more information bits in one video, a special mapping rule is proposed. Through this mapping rule, some key frames in one video are selected. In the selected frames, one or several frames are used to represent a piece of information with equal length. To quickly index out the corresponding frames, a three-level index structure is proposed in this manuscript. Since the proposed coverless video steganography method does not embed one bit in video, it can effectively resist steganalysis algorithms. The experimental results and analysis show that the proposed method has a large capacity, good robustness and high security.

No abstract

No abstract