A hybrid model for simulating crowd evacuation

Macroscopic and microscopic models are typical approaches for simulating crowd behaviour and movement to simulate crowd and pedestrian movement, respectively. However, the two models are unlikely to address the issues beyond their modelling targets (i.e., pedestrian movement for microscopic models and crowd movement for macroscopic models). In order to solve such problem, we propose a hybrid model integrating macroscopic model into microscopic model, which is capable of taking into account issues both from crowd movement tendency and individual diversity to simulate crowd evacuation. In each simulation time step, the macroscopic model is executed first and generates a course-grain simulation result depicting the crowd movement, which directs microscopic model for goal selection and path planning to generate a fine-grain simulation result. In the mean time, different level-of-detail simulation results can also be obtained due to the proposed model containing two complete models. A synchronization mechanism is proposed to convey simulation results from one model to the other one. The simulation results via case study indicate the proposed model can simulate the crowd and agent behaviour in dynamic environments, and the simulation cost is proved to be efficient

Covert voice over internet protocol communications with packet loss based on fractal interpolation

The last few years have witnessed an explosive growth in the research of information hiding in multimedia objects, but few studies have taken into account packet loss in multimedia networks. As one of the most popular real-time services in the Internet, Voice over Internet Protocol (VoIP) contributes to a large part of network traffic for its advantages of real time, high flow, and low cost. So packet loss is inevitable in multimedia networks and affects the performance of VoIP communications. In this study, a fractal-based VoIP steganographic approach was proposed to realise covert VoIP communications in the presence of packet loss. In the proposed scheme, secret data to be hidden were divided into blocks after being encrypted with the block cipher, and each block of the secret data was then embedded into VoIP streaming packets. The VoIP packets went through a packet loss system based on Gilbert model which simulates a real network situation. And a prediction model based on fractal interpolation was built to decide whether a VoIP packet was suitable for data hiding. The experimental results indicated that the speech quality degradation increased with the escalating packet-loss level. The average variance of speech quality metrics (PESQ score) between the "no-embedding" speech samples and the “with-embedding” stego-speech samples was about 0.717, and the variances narrowed with the increasing packet-loss level. Both the average PESQ scores and the SNR values of stego-speech samples and the data retrieving rates had almost the same varying trends when the packet-loss level increased, indicating that the success rate of the fractal prediction model played an important role in the performance of covert VoIP communications

A Digital Mask-Voiceprint System for Postpandemic Surveillance and Tracing Based on the STRONG Strategy

Lockdowns and border closures due to COVID-19 imposed mental, social, and financial hardships in many societies. Living with the virus and resuming normal life are increasingly being advocated due to decreasing virus severity and widespread vaccine coverage. However, current trends indicate a continued absence of effective contingency plans to stop the next more virulent variant of the pandemic. The COVID-19–related mask waste crisis has also caused serious environmental problems and virus spreads. It is timely and important to consider how to precisely implement surveillance for the dynamic clearance of COVID-19 and how to efficiently manage discarded masks to minimize disease transmission and environmental hazards. In this viewpoint, we sought to address this issue by proposing an appropriate strategy for intelligent surveillance of infected cases and centralized management of mask waste. Such an intelligent strategy against COVID-19, consisting of wearable mask sample collectors (masklect) and voiceprints and based on the STRONG (Spatiotemporal Reporting Over Network and GPS) strategy, could enable the resumption of social activities and economic recovery and ensure a safe public health environment sustainably