This paper proposes a graph-based approach to representing spatio-temporal trajectory data that allows an effective visualization and characterization of city-wide traffic dynamics. With the advance of sensor, mobile, and Internet of Things (IoT) technologies, vehicle and passenger trajectories are being increasingly collected on a massive scale and are becoming a critical source of insight into traffic pattern and traveller behaviour. To leverage such trajectory data to better understand traffic dynamics in a large-scale urban network, this study develops a trajectory-based network traffic analysis method that converts individual trajectory data into a sequence of graphs that evolve over time (known as dynamic graphs or time-evolving graphs) and analyses network-wide traffic patterns in terms of a compact and informative graph-representation of aggregated traffic flows. First, we partition the entire network into a set of cells based on the spatial distribution of data points in individual trajectories, where the cells represent spatial regions between which aggregated traffic flows can be measured. Next, dynamic flows of moving objects are represented as a time-evolving graph, where regions are graph vertices and flows between them are treated as weighted directed edges. Given a fixed set of vertices, edges can be inserted or removed at every time step depending on the presence of traffic flows between two regions at a given time window. Once a dynamic graph is built, we apply graph mining algorithms to detect change-points in time, which represent time points where the graph exhibits significant changes in its overall structure and, thus, correspond to change-points in city-wide mobility pattern throughout the day (e.g., global transition points between peak and off-peak periods).

知识可定义是合理的真实信念（“JTB”）？我们认为，人们可以积极地或负面地回答，具体取决于一个人的真实信仰是否合理，我们称之为足够的原因。为了促进我们的论点，我们介绍了一个简单的基于理性的信念的命题逻辑，并提出了充分性的概念的公理表征。我们表明，此逻辑足以灵活，以适应各种有用的功能，包括由于原因的量化。我们使用我们的框架对比JTB的两位概念进行对比：一个内部家，另一家族。我们认为Gettier案例基本上挑战了内部概念，但不是外科医生。我们的方法致力于一系列关于知识的非押金主义，但它也让我们陷入困境，即知识是否涉及只有足够的原因，或者留下房间的原因不足。我们赞成后者的立场，这反映了一个更温和和更现实的无押金主义。