15993806
A Workflow Model with Temporal Logic Constraints and Its Automated Verification
Traditional workflow models are weak in describing the temporal properties and constraints between activities, while some high-level extensions based on time or temporal logic have another problem that the soundness verification of the model requires high academic knowledge. In order to solve these problems, a new workflow model LTL-WF based on WF-net and linear temporal logic is proposed in this paper. Besides introducing the new model, we also bring forward a method for automated verification of LTL-WF. The method proposed here provides the verification of workflow model with a convenient environment for model checking.
33694964
Workflow scheduling in grids: an ant colony optimization approach
Grid applications in virtue of open service grid architecture (OGSA) are promising next-generation computation techniques. One of the most important and challenging problems about grid application is the workflow scheduling problem to achieve the users' QoS (quality of service) requirements as well as to minimize the cost. This paper proposes an ant colony optimization (ACO) algorithm to tackle this problem. Several new features are introduced to the algorithm. First, we define two kinds of pheromone and three kinds of heuristic information to guide the search direction of ants for this bi-criteria problem. Each ant uses either one from these heuristic types and pheromone types in each iteration based on the probabilities controlled by two parameters. These two parameters are adaptively adjusted in the process of the algorithm. Second, we use the information of partial solutions to modify the bias of ants so that inferior choices will be ignored. Moreover, the experimental results in 3 workflow applications under different deadline constraints show that the performance of our algorithm is very promising, for it outperforms the Deadline-MDP algorithm in most cases.
9006284
A workflow model based on fuzzy-timing Petri nets
Time information management in workflow has been recognized as one of the most significant tasks in workflow management. The uncertainties in time and time-related constraints in workflow models should be taken into consideration. Based on introducing time constraints on elements in fuzzy-timing Petri nets, this paper propose a new workflow model named fuzzy temporal workflow nets (FTWF-nets). The calculation of temporal elements in FTWF-nets is given. Then time modeling and time possibility analysis of temporal phenomena in FTWF-nets are investigated. Finally an example is given to illustrate how to use these methods. Research results show that FTWF-nets can be used to model time information in those workflows, which have time uncertainty and have time constraints on resources and activities, and analyze the time possibility on some constraints.
14448098
Research on Dynamic Task Assignment in Grid Workflow System
Task assignment in grid workflow system should be designed to adapt well with the grid which allow people from different organizations to work together in the same workflow process. To ensure grid workflow systems could assign the task to the most suitable person, a novel solution is proposed firstly. Then two description languages GHRSL and HRRL are defined. GHRSL (grid human resource specification language) describes people as grid resources. HRRL (human resources requirement language) describes human resources requirement of workflow tasks. Finally, the evaluation method and the algorithm of dynamic task assignment are also proposed. Based on these, the grid workflow system could assign tasks dynamically to the correct person(s)
17624107
3D Simulation of Real-Time Infrared Scene Based on DSP
Nowadays 3D simulation of Infrared scene is quite popular. Most of these simulations were realized on PC and under the help of many free or commercial 3D APIs or libraries. We carried out our simulation by a rendering engine written by ourselves, and implement this engine on a DSP board, which gave us much convenience to directly inject the digital result into the IR tracking and alarming systems which use the result as their data source. We also used some techniques such as look-up table, culling, etc, to accelerate the IR radiance calculation and rendering speed. The result shows that itpsilas a valuable attempt, which can make the IR scene generator smaller and more portable, and gain advantage in the hardware acceleration as well as convenience in future system connection.
6570934
Human appearance modeling for matching across video sequences
We present an appearance model for establishing correspondence between tracks of people which may be taken at different places, at different times or across different cameras. The appearance model is constructed by kernel density estimation. To incorporate structural information and to achieve invariance to motion and pose, besides color features, an additional feature of path-length is used. To achieve illumination invariance, two types of illumination insensitive color features are discussed: brightness color feature and RGB rank feature. The similarity between a test image and an appearance model is measured by the information gain or Kullback–Leibler distance. To thoroughly represent the information contained in a video sequence with as little data as possible, a key frame selection and matching scheme is proposed. Experimental results demonstrate the important role of the path-length feature in the appearance model and the effectiveness of the proposed appearance model and matching method.
2706190
Shedding New Light on Sequence Design Criteria for Multipath Channels
The merit factor (MF) introduced by Golay has long been accepted as the standard criterion to evaluate and design binary sequences with good anti-multipath property in sonar, radar, and communication systems for its theoretical tightness and practical simplicity. In this paper, we first show that the MF is a biased anti-multipath performance evaluation metric in theory and, more importantly, is not a pertinent sequence design criterion in practice for most binary sequences of practical interest. Then we propose the weighted merit factor (WMF) based on a non-uniform weighting of the out-of-phase aperiodic autocorrelation function (ACF) that provides accurate measurement of self-generated interference for the constant amplitude complex-valued sequences and the nonconstant modulus ones. Based on the WMF, a list of "bad" (of low MFs) binary sequences (lengths 33-95) with better anti-multipath performance than the "best" (known) ones have been designed to verify its greater pertinence over the MF as a sequence design criterion for sonar, radar, and communication systems. Moreover, we extend the weighted correlation model of the WMF to the code-division multiple-access (CDMA) systems and propose the weighted cross-correlation factor (WCF) to evaluate the sequence set's multiple-access interference (MAI) rejection property in the context of multipath propagation. Theoretical analysis corroborated by simulations confirms that the WCF provides greater practical pertinence and analytical tractability over the current standard criterion.
8259100
Adapt Bagging to Nearest Neighbor Classifiers
It is well-known that in order to build a strong ensemble, the component learners should be with high diversity as well as high accuracy. If perturbing the training set can cause significant changes in the component learners constructed, then Bagging can effectively improve accuracy. However, for stable learners such as nearest neighbor classifiers, perturbing the training set can hardly produce diverse component learners, therefore Bagging does not work well. This paper adapts Bagging to nearest neighbor classifiers through injecting randomness to distance metrics. In constructing the component learners, both the training set and the distance metric employed for identifying the neighbors are perturbed. A large scale empirical study reported in this paper shows that the proposed BagInRand algorithm can effectively improve the accuracy of nearest neighbor classifiers.
16908353
The Dynamic Grey Radial Basis Function Prediction Model and its Applications
The dynamic gray radial basis function (DGRBF) prediction model is the improvement of traditional dynamic grey prediction model GM (1,1). It gives the dynamic algorithm of acquiring optimized initial conditions and identifying parameters like metabolism, and then the model combines the characters of RBF neural networks, and therefore has the ability of dynamic prediction on small volume of samples. The DGRBF prediction model has been applied in the practical engineering successfully, and the experiment results demonstrate that model and its intelligent optimizing algorithm are capable of predicting in a long term and the desired data could be acquired accurately, easily and conveniently