A Web-based flood forecasting system for Shuangpai region

Traditional flood forecasting and operation of reservoirs in China are based on manual calculations by hydrologists or through standalone computer programs. The main drawbacks of these methods are long forecasting time due to time-consuming nature, individual knowledge, lack of communication, absence of experts, etc. A Web-based flood forecasting system (WFFS), which includes five main modules: real-time rainfall data conversion, model-driven hydrologic forecasting, model calibration, precipitation forecasting, and flood analysis, is presented in this paper. The WFFS brings significant convenience to personnel engaged in flood forecasting and control and allows real-time contribution of a wide range of experts at other spatial locations in times of emergency. The conceptual framework and detailed components of the proposed WFFS, which employs a multi-tiered architecture, are illustrated. Multi-tiered architecture offers great flexibility, portability, reusability and reliability. The prototype WFFS has been developed in Java programming language and applied in Shuangpai region with a satisfactory result.     

Automated clustering to support the reflexion method

A significant aspect in applying the Reflexion Method is the mapping of components found in the source code onto the conceptual components defined in the hypothesized architecture. To date, this mapping is established manually, which requires a lot of work for large software systems. In this paper, we present a new approach, in which clustering techniques are applied to support the user in the mapping activity. The result is a semi-automated mapping technique that accommodates the automatic clustering of the source model with the user’s hypothesized knowledge about the system’s architecture.This paper describes three case studies in which the semi-automated mapping technique, called HuGMe, has been applied successfully to extend a partial map of real-world software applications. In addition, the results of another case study from an earlier publication are summarized, which lead to comparable results. We evaluated the extended versions of two automatic software clustering techniques, namely, MQAttract and CountAttract, with oracle mappings. We closely study the influence of the degree of completeness of the existing mapping and other controlling variables of the technique to make reliable suggestions.Both clustering techniques were able to achieve a mapping quality where more than 90% of the automatic mapping decisions turned out to be correct. Moreover, the experiments indicate that the attraction function (CountAttract′) based on local coupling and cohesion is more suitable for semi-automated mapping than the approach MQAttract′ based on a global assessment of coupling and cohesion.     

Using spectral method as an approximation for solving hyperbolic PDEs

We demonstrate an application of the spectral method as a numerical approximation for solving hyperbolic PDEs. In this method a finite basis is used for approximating the solutions. In particular, we demonstrate a set of such solutions for cases which would be otherwise almost impossible to solve by the more routine methods such as the Finite Difference Method. Eigenvalue problems are included in the class of PDEs that are solvable by this method. Although any complete orthonormal basis can be used, we discuss two particularly interesting bases: the Fourier basis and the quantum oscillator eigenfunction basis. We compare and discuss the relative advantages of each of these two bases.     

Model checking response times in Networked Automation Systems using jitter bounds

Response time (RT) of Networked Automation Systems (NAS) is affected by timing imperfections induced due to the network, computing and hardware components. Guaranteeing RT in the presence of such timing imperfections is essential for building dependable NAS, and to avoid costly upgrades after deployment in industries.This investigation proposes a methodology and work-flow that combines modelling, simulation, verification, experiments, and software tools to verify the RT of the NAS during the design, rather than after deployment. The RT evaluation work-flow has three phases: model building, modelling and verification. During the model building phase component reaction times are specified and their timing performance is measured by combining experiments with simulation. During the modelling phase, component based mathematical models that capture the network architecture and inter-connection are proposed. Composition of the component models gives the NAS model required for studying the RT performance on system level. Finally, in the verification step, the NAS formal models are abstracted as UPPAAL timed automata with their timing interfaces. To model timing interfaces, the action patterns, and their timing wrapper are proposed. The formal model of high level of abstraction is used to verify the total response time of the NAS where the reactions to be verified are specified using a subset of timed computation tree logic (TCTL) in UPPAAL model checker. The proposed approach is illustrated on an industrial steam boiler deployment.     

Automated classification of touching or overlapping M-FISH chromosomes by region fusion and homolog pairing

Automated separation and classification of touching or overlapping chromosomes in a metaphase image is a critical step in computer-aided chromosome analysis. The advent of the multiplex fluorescence in situ hybridization (M-FISH) technology enables multi-spectral chromosome image with rich spectral information and DAPI image with abundant texture information. This paper presents a fusion classification scheme to improve the segmentation of overlapping and touching chromosomes. First, the texture and spectral information is fused to partition the chromosome cluster into a series of homologous regions. Then a graph-theoretical classification and pairing method is proposed to resolve any remaining ambiguity of the aforementioned separation process. Experiment results demonstrate that the proposed method outperforms conventional multi-spectral classification methods in touching and overlapping chromosome separation.     

Bounded Consensus Algorithms for Multi‐Agent Systems in Directed Networks

In this paper, the consensus problem is investigated via bounded controls for the multi‐agent systems with or without communication. Based on the nested saturation method, the saturated control laws are designed to solve the consensus problem. Under the designed saturated control laws, the transient performance of the closed‐loop system can be improved by tuning the saturation level. First of all, asymptotical consensus algorithms with bounded control inputs are proposed for the multi‐agent systems with or without communication delays. Under these consensus algorithms, the states’ consensus can be achieved asymptotically. Then, based on a kind of novel nonlinear saturation functions, bounded finite‐time consensus algorithms are further developed. It is shown that the states’ consensus can be achieved in finite time. Finally, two examples are given to verify the efficiency of the proposed methods.     

Multiconsensus of second order multiagent systems with directed topologies

A novel multiconsensus problem is introduced in multiagent systems. The states of multiple agents in each subnetwork asymptotically converge to a consistent value with information exchanges among subnetworks. The multiconsensus problem of second order multiagent systems with directed topologies is studied. Three linear protocols are proposed to solve the multiconsensus problem. Necessary and sufficient conditions are derived based on matrix theory. Simulations are provided to demonstrate the effectiveness of the theoretical results.     

Theory and techniques of data mining in CGF behavior modeling

For the large quantity of data,rules and models generated in the course of computer generated forces (CGFs) behavior modeling,the common analytical methods are statistical methods based on the tactical rules,tactical doctrine and empirical knowledge.However,from the viewpoint of data mining,we can find many of these analytical methods are also each-and-every different data mining methods.In this paper,we survey the data mining theory and techniques that have appeared in the course of CGF behavior modeling f...