In order to strengthen the monitoring of old people and reduce the safety risks caused by falls， a new indoor fall detection algorithm based on Res2Net-YOLACT and fusion feature was proposed. For the video image sequences， firstly， the YOLACT network integrated with Res2Net module was used to extract the human body contour， and then a two-level judgment method was used to make a fall decision. In the first level， whether an abnormal state occurs was judged roughly through the movement speed feature， and in the second level， the human body posture was determined through the model structure that combines the body shape features and the depth feature. Finally， when fall posture was detected and the occurrence time was greater than the threshold， a fall alarm was given. Experimental results show that the proposed fall detection algorithm can extract the human body contour well in complex scenes， which has good robustness to illumination as well as a real-time performance of up to 28 fps （frames per second）. In addition， the classification performance of the algorithm after adding manual features is better， the classification accuracy is 98.65%， which is 1.03 percentage points higher than that of the algorithm with original CNN （Convolutional Neural Network） features.

Ensemble resampling technology can solve the problem of imbalanced samples in financial early warning research to some extent. Different ensemble models and different ensemble resampling technologies have different suitabilities. It is found in the study that Up-Down ensemble sampling and Tomek-Smote ensemble sampling were respectively suitable for Bagging-Vote ensemble model and Stacking fusion model. Based on the above， a Stacking-Bagging-Vote （SBV） multi-source information fusion model was built. Firstly， the Bagging-Vote model based on Up-Down ensemble sampling and the Stacking model based on Tomek-Smote sampling were fused. Then， the stock trading data were added and processed by Kalman filtering， so that the interactive fusion optimization of data level and model level was realized， and the SBV multi-source information fusion model was finally obtained. This fusion model not only has a great improvement in the prediction performance by taking into account prediction accuracy and prediction precision simultaneously， but also can select the corresponding SBV multi-source information fusion model to perform the financial early warning to meet the actual needs of different stakeholders by adjusting the parameters of the model.

To improve the computational efficiency in the threshold signature scheme, the authors proposed a new threshold signature scheme based on bilinear pairing via combining Gennaro's (GENNARO R, JAREAKI S, KRAWCZYK H, et al. Secure distributed key generation for discrete-log based cryptosystem. Journal of Cryptology, 2007, 20(1): 51-83) distributed secret key generation solution and Gu's (GU K, JIA W J, JIANG C L. Efficient and secure identity-based signature scheme. Journal of Software, 2011, 22(6): 1350-1360) signature scheme in the standard model. There was no trusted dealer for secret key share distribution and each party could verify the validity of some important information, which guaranteed the proposed scheme can avoid the malicious private key generator attack and public key share replacing attack. The comparison results with two previous threshold signature schemes show that the proposed scheme needs less pairing computation and raises the computational efficiency.

Survivability is one of the technical indicators, which needed to consider in the highest priority, in the design and use of Unmanned Aerial Vehicle (UAV). According to the requirements of real-time display of situation and visual expression of analysis results in modern battlefield simulation, UAV survivability analysis system was developed with MapX component technology. First the primary frame and characteristics of MapX were introduced briefly. The function and composition of UAV survivability analysis system were discussed. And the module partition and program flow of system were given. Then the functions of war zone map display-roaming-zooming, combat scenario and display and process of survivability data with MapX technology in VC++ environment were analyzed in detail. Finally the simulation examples of survivability analysis were given. Simulation experiments indicate that the battlefield geographic environment of UAV is factually, vividly and dynamically displayed in the system. It is convenient to analyze the influence factors on survivability.

The Quality of Experience (QoE) of audio stream is significantly affected by packet loss in packet-switch network. To control the loss and analyze its effect on QoE, a simulated multimedia transport test bed was designed. And the mapping model between packet loss rate and QoE was established by regression analysis under specific encoding/decoding mode and Real-time Transport Protocol (RTP) packet interval. The model has low computational complexity and can predicate the impairment of packet loss on user experience in real-time.

Ability difference of P2P nodes causes the work load imbalance which always swaps between nodes. To address this problem, the concept of virtual node was originally presented that the nodes were transferred into logical nodes with similar abilities, by dividing and aggregating the nodes. Virtual node can eliminate the ability difference at best effort, achieve load balance, and increase performance and efficiency.

The modular structure of irregular fragments reconstruction based on contour feature was introduced, and a new traversing algorithm for the sequence of fragments merging was presented. In the algorithm, the locating and merging of a fragment were determined by the current matching-fragment and another fragment, which ensured the process of fragments merging. An example was given and experiment results illustrate the algorithm efficient.