The management of large-scale events poses significant resilience challenges to urban traffic systems, where classical computational methods often prove inadequate for the resulting complex, dynamic optimization problems. This paper introduces a quantum-enhanced hybrid high-performance computing framework designed to improve traffic resilience during such events. The framework leverages a Quantum Annealing (QA) algorithm to solve a Quadratic Unconstrained Binary Optimization (QUBO) model of key traffic optimization tasks, integrated with classical computing for data processing and workflow control. Using the traffic management for a major concert at Hefei Luogang Park as a case study, we focus on modeling and applying this framework to two core resilience problems: Dynamic Evacuation Route Optimization (DERO) and Emergency Resource Allocation (ERA). Our simulation results provide empirical validation of the framework's effectiveness, demonstrating that the proposed quantumenhanced approach reduces total evacuation time by 20.0 % and average emergency response time by 32.2 % compared to welldefined greedy heuristics. These findings highlight the potential of quantum computing as an emerging high-performance computing paradigm for addressing the intricate challenges of traffic resilience.

The proliferation of Unmanned Aerial Vehicles (UAVs) for urban public safety is critically hindered by operational risks inherent in complex environments. To address these challenges, this paper introduces a “UAV-as-a-Service” (UaaS) paradigm, an application paradigm innovation that leverages the core infrastructure of telecom operators. Our primary contribution is a closed-loop intelligent method, representing an algorithmic innovation, centered on a 3D Dynamic Risk Map (DRM). The DRM is generated in real-time by a Dynamic Bayesian Network (DBN) and explicitly informs both a risk-aware Multi-Agent Reinforcement Learning (MARL) dispatcher and a hybrid Rapidly-exploring Random Tree Star (RRT*)-Model Predictive Control (MPC) path planner. This tight coupling ensures that tactical decisions are grounded in a holistic understanding of risk. Simulation results demonstrate that the proposed UaaS model substantially enhances operational outcomes, reducing the time to achieve critical situational awareness by over 75 % and decreasing firefighter risk exposure by$\mathbf{7 8 \%}$. These technical advancements validate a novel and viable Business-to-Government (B2G) service model, demonstrating significant technologycommercial synergy.

The construction of information system stability assurance capabilities has a long history of development. However, with the gradually increasing load pressure of the information system, the distributed architecture has gradually become the mainstream architecture of information system. Furthermore, the stability guarantee of the information system has entered a new stage, which requires extensive optimization in both theoretical and practical aspects. This paper researches on the relevant background, basic principles, key elements, core competencies, and evaluation system of information system stability assurance capacity construction in the new stage. In addition, this paper explores the future development trend of stability assurance work.

With the advancement of digital transformation in various fields, the information industry has developed rapidly in the 21st century. Significant changes in system scale, research and development operation and maintenance models, technical architecture, and user groups have made the impact of information system failures wider and more severe. Disaster recovery systems can protect the data and applications of information systems before disasters occur, ensure the security of data in the event of a disaster, and achieve rapid business recovery. They have become an indispensable foundation for modern data infrastructure. This article provides a brief introduction to various disaster recovery technologies, followed by a summary of the principles that should be followed during the construction process of the disaster recovery system. Finally, it provides a detailed introduction to how to execute and manage the entire process of the disaster recovery system construction and proposes corresponding suggestions.

With the fast development of information technology, the databases used as the fundamental storage and computing component of information system have to deal with much more complicated scenarios with high frequency and concurrency. Distributed databases are becoming more and more common in data-intensive industries such as banking and telecommunications. The selection of distributed database products requires comprehensively consider the function, performance, security, ease of use and stability of the product. The stability of distributed database is known to be difficult in testing and product selection. The method widely used in database testing is TPC-DS (transaction processing performance council-decision support) benchmark, which is only suitable for functional and performance testing. To deal with this drawback, a distributed database stability testing platform based on chaos engineering methodology is developed. Through the perturbation injection by using the stability testing platform, the performance fluctuation of the database under pressure condition can be observed, and the stability of the database can then be evaluated.

In industry, analytic database is known to be difficult in testing and product selection. The traditional TPC-DS (transaction processing performance council-decisioin support) benchmark [1], which only has one retail scene, is not sufficient enough for database product selection of other business type. To deal with this drawback, an analytical database testing platform which can plug-in a variety of business scenes was developed. The telecommunication scene was also provided to explain the design concept, system architecture and scene development of this testing platform. The platform provides scene plug-in function which is easy to use without any programming background. Users can select and edit scenes according to their own business type to meet the requirements of analytical database testing and selection in different industries.

A prototype of fully flexible intelligent contact lens, which are shown in the impressive action movie series of “MISSION: IMPOSSIBLE”, has become the Possible Mission in this work. Hereon, the system adopts analog-to-information processing method to build a specific Multi-Layer Perceptron network for image classification tasks with flexible devices and circuits, where the information is extracted from raw data of the sensing analog signal directly. Simulated with HSPICE of Level-62 TFT device model, for standard test image data set of MNIST, the classification accuracy of the presented flexible neural network circuit is up to 92.99%; meanwhile, the classification speed is as fast as 10k fps, and the energy consumption is low to only 15.16μJ. Additionally, for the imperfections of flexible devices of larger devices mismatch and process variations, the fault-tolerance of the system has been evaluated as well, which demonstrates the feasibility of the presented methods and lowers the barrier to integrated all kinds of FLEXIBLE Devices into a FULLY FLEXIBLE Systems with sensors, processing parts and even energy harvesting parts, etc., in the future wearable smart terminals.