962,207 research outputs found
On the Design of Clean-Slate Network Control and Management Plane
We provide a design of clean-slate control and management plane for data networks using the abstraction of 4D architecture, utilizing and extending 4D’s concept of a logically centralized Decision plane that is responsible for managing network-wide resources. In this paper, a scalable protocol and a dynamically adaptable algorithm for assigning Data plane devices to a physically distributed Decision plane are investigated, that enable a network to operate with minimal configuration and human intervention while providing optimal convergence and robustness against failures. Our work is especially relevant in the context of ISPs and large geographically dispersed enterprise networks. We also provide an extensive evaluation of our algorithm using real-world and artificially generated ISP topologies along with an experimental evaluation using ns-2 simulator
Bayesian networks and decision trees in the diagnosis of female urinary incontinence
This study compares the effectiveness of Bayesian networks versus Decision Trees in modeling the Integral Theory of Female Urinary Incontinence diagnostic algorithm. Bayesian networks and Decision Trees were developed and trained using data from 58 adult women presenting with urinary incontinence symptoms. A Bayesian Network was developed in collaboration with an expert specialist who regularly utilizes a non-automated diagnostic algorithm in clinical practice. The original Bayesian network was later refined using a more connected approach. Diagnoses determined from all automated approaches were compared with the diagnoses of a single human expert. In most cases, Bayesian networks were found to be at least as accurate as the Decision Tree approach. The refined Connected Bayesian Network was found to be more accurate than the Original Bayesian Network accurately discriminated between diagnoses despite the small sample size. In contrast, the Connected and Decision Tree approaches were less able to discriminate between diagnoses. The Original Bayesian Network was found to provide an excellent basis for graphically communicating the correlation between symptoms and laxity defects in a given anatomical zone. Performance measures in both networks indicate that Bayesian networks could provide a potentially useful tool in the management of female pelvic floor dysfunction. Before the technique can be utilized in practice, well-established learning algorithms should be applied to improve network structure. A larger training data set should also improve network accuracy, sensitivity, and specificity
An experimental paradigm for team decision processes
The study of distributed information processing and decision making is presently hampered by two factors: (1) The inherent complexity of the mathematical formulation of decentralized problems has prevented the development of models that could be used to predict performance in a distributed environment; and (2) The lack of comprehensive scientific empirical data on human team decision making has hindered the development of significant descriptive models. As a part of a comprehensive effort to find a new framework for multihuman decision making problems, a novel experimental research paradigm was developed involving human terms in decision making tasks. Attempts to construct parts of an integrated model with ideas from queueing networks, team theory, distributed estimation and decentralized resource management are described
M-ATTEMPT: A New Energy-Efficient Routing Protocol for Wireless Body Area Sensor Networks
In this paper, we propose a new routing protocol for heterogeneous Wireless
Body Area Sensor Networks (WBASNs); Mobility-supporting Adaptive
Threshold-based Thermal-aware Energy-efficientMulti-hop ProTocol (M-ATTEMPT). A
prototype is defined for employing heterogeneous sensors on human body. Direct
communication is used for real-time traffic (critical data) or on-demand data
while Multi-hop communication is used for normal data delivery. One of the
prime challenges in WBASNs is sensing of the heat generated by the implanted
sensor nodes. The proposed routing algorithm is thermal-aware which senses the
link Hot-spot and routes the data away from these links. Continuous mobility of
human body causes disconnection between previous established links. So,
mobility support and energy-management is introduced to overcome the problem.
Linear Programming (LP) model for maximum information extraction and minimum
energy consumption is presented in this study. MATLAB simulations of proposed
routing algorithm are performed for lifetime and successful packet delivery in
comparison with Multi-hop communication. The results show that the proposed
routing algorithm has less energy consumption and more reliable as compared to
Multi-hop communication.Comment: arXiv admin note: substantial text overlap with arXiv:1208.609
Migrant networks, language learning and tourism employment
This paper examines the relationship between migrants’ social networks, the processes of language acquisition and tourism employment. Data collected using netnography and interviews are used to identify the strategies that Polish workers in the UK use to develop their language skills. The paper highlights the roles played by co-workers, co-nationals and customers in migrants’ language learning, both in the physical spaces of work and the virtual spaces of internet forums. It also shows how migrant workers exchange knowledge about the use of English during different stages of their migration careers: prior to leaving their country of origin and getting a job, during their employment and after leaving their job. Implications for academic inquiry and human resource management practice are outlined
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