Dealing with the ever-growing complexity of railway systems requires scalable approaches for detecting inconsistent safety requirements in practice. Despite significant efforts to automate the requirements consistency detection, current inconsistency analysis techniques of railway safety requirements still suffer from scalability issues. This paper proposes a two-layer approach for detecting inconsistencies in time-related safety requirements of railway systems, integrating two distinct formal methods from a pragmatic perspective. At the SafeNL layer, we employ an SMT-based approach to extract conflict patterns and use them to filter out inconsistent requirements descriptions, thus avoiding the more expensive general use of the SMT-based approach. At the CCSL layer, temporal dependencies in requirements are transformed into causal relations, which are then detected for circular inconsistencies using a graph search technique. Our evaluations demonstrate the utility and scalability of our approach.

UML interactions, aka sequence diagrams, are frequently used by engineers to describe expected scenarios of good or bad behaviors of systems under design, as they provide allegedly a simple enough syntax to express a quite large variety of behaviors. This paper uses them to express formal safety requirements for safety critical systems in an incremental way, where the scenarios are progressively refined after checking the consistency of the requirements. As before, the semantics of these scenarios are expressed by transforming them into an intermediate semantic model amenable to formal verification. We rely on the Clock Constraint Specification Language (CCSL) as the intermediate semantic language. An SMT-based analysis tool called MyCCSL is used to check consistency of the sequence diagrams. We compare these requirements against actual execution traces to prove the validity of our transformation. In some sense, sequence diagrams and CCSL constraints both express a family of acceptable infinite traces that must include the behaviors given by the finite set of finite execution traces against which we validate. Finally, the whole process is illustrated on partial requirements for a railway transit system.

We propose a novel texture feature extraction technique based on coefficients' co-occurrence histogram of discrete wavelet frame transformed image, which capture the information about relationship between each high frequency subband and the low frequency subband of the decomposed image at the corresponding level. It is not independently utilizing the information of each subband coefficient. The classification performance is analyzed using the k-NN classifier. And the experimental results demonstrate the effectiveness of our proposed texture feature in achieving the improved classification performance. Comparisons with the Gabor filter and a recently proposed approach are also provided.

The goal of handoffs in a 4G wireless network is not only to keep the data traffic from being disrupted due to user mobility, but also to switch the connection to the network which best satisfies users' requirements. In this work, we propose a scheme which dynamically switches a mobile user's connection between different access networks. In each handoff, a user will adjust its bandwidth requirement according to the utilization of the current access network. A profitability function is established to evaluate the profits gained from a handoff and to select the target network accordingly. Through vertical handoffs, traffic load will be balanced among the access networks and radio resources will be efficiently utilized. Our simulation result shows that the scheme will effectively decrease call blocking and dropping rate. System throughput and users' experience will also be improved.