We investigate an interactive evolutionary computation (IEC) using multiple users' gaze information when users partially participate in each design evaluation. Many previous IEC systems have a problem that user evaluation loads are too large. Hence, we proposed to employ user gaze information for evaluating designs generated by IEC systems in order to solve this problem. In this proposed system, users just view the presented designs, not assess, then the system automatically creates users' favorite designs. With the user's gaze information, the proposed system generates coordination that can satisfy many users. In our previous study, we verified the effectiveness of the proposed system from a real system operation viewpoint. However, we did not consider the fluctuation of the users during a solution candidate evaluation. In the actual operation of the proposed system, users may change during the process due to the user interchange. Therefore, in this study, we verify the effectiveness of the proposed system when varying the users participating in each evaluation for each generation. In the experiment, we employ two types of situations as assumed in real environments. The first situation changes the number of users evaluating the designs for each generation. The second situation employs various users from the predefined population to evaluate the designs for each generation. From the experimental results in the first situation, we confirm that, despite the change in the number of users during the solution candidate evaluation, the proposed system can generate coordination to satisfy many users. Also, from the results in the second situation, we verify that the proposed system can also generate coordination which both users who participate in the coordination evaluation can more satisfy.

Multi-view video streaming plays an important role in new interactive and augmented video applications such as telepresence, remote surgery, and entertainment. For those applications, interactive multi-view video transmission schemes have been proposed that aim to reduce the amount of video traffic. Specifically, these schemes only encode and transmit video frames, which are potentially displayed by users, based on periodical feedback from the users. However, existing schemes are vulnerable to frame loss, which often occurs during transmissions, because they encode most video frames using inter prediction and inter-view prediction to reduce traffic. Frame losses induce significant quality degradation due to the collapse of the decoding operations. To improve the loss resilience, we propose an encoding/decoding system, Frame Popularity-based Multi-view Video Streaming (FP-MVS), for interactive multi-view video streaming services. The main idea of FP-MVS is to assign intra (I) frames in the prediction structure for less/more popular (i.e., few/many observed users) potential frames in order to mitigate the impact of a frame loss. In addition, FP-MVS utilizes overlapping and non-overlapping areas between all user's potential frames to prevent redundant video transmission. Although each intra-frame has a large data size, the video traffic can be reduced within a network constraint by combining multicast and unicast for overlapping and non-overlapping area transmissions. Evaluations using Joint Multi-view Video Coding (JMVC) demonstrated that FP-MVS achieves higher video quality even in loss-prone environments. For example, our scheme improves video quality by 11.81dB compared to the standard multi-view video encoding schemes at the loss rate of 5%.

We consider the problems of access control and encrypted keyword search for cryptographic cloud storage in such a way that they can be implemented for a multiple users setting. Our fine-grained access control aware multi-user secure keyword search approach interdependently harmonizes these two security notions, access control and encrypted keyword search. Owing to the shrinkage of the cloud server's search space to the user's decryptable subset, the proposed scheme both decreases information leakage and is shown to be efficient by the results of our contrastive performance simulation.

Multi-view video consists of multiple video sequences which are captured by multiple closely spaced cameras from different angles and positions. It enables each user to freely switch viewpoints by playing different video sequences. However, the transmission of multi-view video requires more bandwidth than conventional multimedia. To reduce the bandwidth, UDMVT (User Dependent Multi-view Video Transmission) based on MVC (Multi-view Video Coding) for a single user has been proposed. In UDMVT, the same frames are encoded into different versions for different users, which increases the redundant transmission. To overcome this problem and extend UDMVT to multiple users' environment, this paper proposes UMSM (User dependent Multi-view video Streaming for Multi-users). UMSM calculates the overlapping and un-overlapping frame area for multiple users from all frames based on feedback information at a server. Proposed UMSM exploits the combination of multicasting overlapping area to multiple users and unicasting un-overlapping area to each user. By means of this concept, UMSM only transmits required frames for each user. To achieve further reduction of the traffic, UMSM combines other two features with this concept. The first one is that offset of the requests from multiple users is aligned periodically to maximize the overlapping frame area. The second one is that the SP-frames standardized in H.264/AVC are exploited as the anchor frame of overlapping frame area to prevent redundant transmissions of overlapping frames. The combination of these three techniques achieves substantial reduction of the transmission bitrate for multiple users in multi-view video streaming. Simulation results using benchmark test sequences provided by MERL show that UMSM decreases the transmission bit-rate 47.2% on average for 4 users are watching the same multi-view video compared to UDMVT.