15941574
Organizational Adaptative Behavior: The Complex Perspective of Individuals-Tasks Interaction
Organizations with different organizational structures have different organizational behaviors when responding environmental changes. In this paper, we use a computational model to examine organizational adaptation on four dimensions: Agility, Robustness, Resilience, and Survivability. We analyze the dynamics of organizational adaptation by a simulation study from a complex perspective of the interaction between tasks and individuals in a sales enterprise. The simulation studies in different scenarios show that more flexible communication between employees and less hierarchy level with the suitable centralization can improve organizational adaptation.
35439746
Role-Based and Agent-Oriental Teamwork Modeling
5679790
Proactive Information Exchange During Team Cooperation
We are concerned, ultimately, with multi-agent teams involving both software and human agents in which the software agents assist in training the humans, e.g., as virtual team members. The software agents must be capable of utilizing the teamwork mechanisms used by humans. In this paper, we describe how to give agents the same implicit communication capabilities, i.e., observation, that humans use. We show how agents can use observations of the environment and teammates' actions to estimate other agents beliefs without bothering them with unnecessary messages; we also show how agents can anticipate information needs among the team and proactively exchange information, reducing the total communication volume. To achieve these goals, we add sensing capabilities to agents and present algorithms that infer teammates' mental state from the observation. Experimental data is presented that shows that the advantage of observation in proactive information exchange as well as enhanced team performance.
1229519
A decision-theoretic approach for designing proactive communication in multi-agent teamwork
Techniques that support effective communication during teamwork processes are of particular importance. Psychological study shows that an effective team often can anticipate information exchange among the team and communicate relevant information proactively. Proactive communication is crucial for understanding and sharing common goals and for cooperative actions. Communication can be valuable if it assists agents with new and timely information; it also has cost because it consumes network resources such as bandwidth. To address these issues, we present a new model that uses information production and need to capture the complex multi-agent communication process and a dynamic decision-theoretic determination of communication strategies. We also introduce a generic utility function and an algorithm, DTPC (Decision-Theoretic Proactive Communication), that focuses on representing information production and need of team members and resolving decision interactions among them for making decisions.
14748203
A history sensitive cascade model in diffusion networks
Diffusion is a process by which information, viruses, ideas and new behavior spread over social networks. The traditional independent cascade model gives activated nodes a one-time chance to activate each of its neighboring nodes with some probability. This paper extends the traditional cascade model to be history dependent. We propose a new model called the History Sensitive Cascade Model (HSCM) that allows activated nodes to receive more than a one-time chance to activate their neighbors. HSCM provides 1) a polynomial algorithm for calculating the probability of activity for any arbitrary node at any arbitrary time in tree structure graphs, and 2) a Markov model for calculating the probability in general graphs. Finally, we perform an empirical study on HSCM under different network settings. These simulations have showed its power to observe and explain the emergent phenomena in the macro level when changing parameters in the micro level.
40423470
Proactive Communication in Observation-Based Agent Team Corporation
40389264
Application of Efficient Numerical Methods in Solution of Ordinary Differential Equations for Modeling Electrical Activity in Cardiac Cells
There is a large number of ordinary differential equations (ODEs) characterize the electrical behavior generated by ionic movements in human myocardial cell. In this paper, several approaches were investigated in order to improve the efficiency of solving the ODE systems for ten Tusscher et al.’s ionic model of human ventricular tissue. By using non-standard finite difference (NSFD) scheme, the stiffness of the ODEs system will be successfully reduced, so a larger step-size can be used. A popular multi-step method called backward differentiation formulation (BDF) was also incorporated into the computational model for testing the largest possible time steps. The results show that NSFD can be as much as 10 times more efficient than standard forward Euler in single cell model simulation while maintaining an acceptable level of accuracy. The investigation of BDF method shows that a large step size is not recommended for the single cell simulation application. All solvers were coupled to the partial differential equations for the complete simulation of heart tissue, and such computation scheme may be a good calculation technique in heart modeling and simulation.
42884670
Eulerian path methods for multiple sequence alignment
With the rapid increase in the size of genome sequence databases, the multiple sequence alignment problem is increasingly important and often requires the alignment of a large number of sequences. Beginning in 1975, many heuristic algorithms have been created to improve the speed of computation and the quality of alignment. We introduce a novel approach that is fundamentally distinct from all currently available methods. Our motivation comes from the Eulerian method for fragment assembly in DNA sequence determination, that transforms all the DNA sequencing fragments into a de Bruijn graph and then reduces sequence assembly to a Eulerian path problem.
17429523
A Novel Trust-based Cooperative Node Selection Scheme in Wireless Sensor Networks
For communication between the cluster head node (CHN) and the distant data fusion center (DFC) with the cooperation of intra-cluster nodes in wireless sensor networks (WSNs), reliable handling of packets by the cooperative node (CN) is difficult to ensure. In this paper, we propose a novel CN selection scheme based on trust for WSNs. This scheme can choose one of high trust nodes to assist in the transmission of CHN, which aims to improve the transmission performance over cooperative communication in the presence of potential malicious nodes. First, we establish a trust model to improve the reliability of transmission by CN in WSNs, which is based on both the direct trust and the indirect trust of nodes. Then the CHN selects a node based on the proposed trust model to aid the CHN in transmission. Simulation results show that the proposed scheme can mitigate the impact of the potential malicious nodes on transmission performance and the simulation results also demonstrate the efficiency of the proposed scheme.
10866526
Adaptive simulation of facial expressions
This paper presents a space-time adaptive refinement approach to simulate facial expressions on the deformable 3D face model at interactive rate. This new computational model benefits from an adaptive sampling of both space and time to minimize computational cost. Using this technique, we achieve a guaranteed frame rate of the dynamic facial expression simulation at low computational expense.
9609952
A survivable routing algorithm with differentiated domain protection based on a virtual topology graph in multi-domain optical networks
In this paper, we propose a novel differentiated domain protection (DDP) scheme to address survivability in multi-domain optical networks. Survivable routing in multi-domain networks is a challenging algorithmic problem because it requires choosing links that provide adequate protection both between domains and within domains that may offer different protection services. To satisfy the survivability requirements of different domains, DDP considers differentiated protection schemes, i.e., dedicated protection, shared protection, or no protection in different domains. In order to respect the principle of transparent management in multiple domains, DDP abstracts a multi-domain optical network to a virtual topology graph (VTG) for solving routing between domains. Simulation results show that DDP, unlike traditional schemes, can provide trade-off between protection methods and also allows better resource utilization.