The Experts below are selected from a list of 148959 Experts worldwide ranked by ideXlab platform
Edson L Ursini - One of the best experts on this subject based on the ideXlab platform.
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reducing power consumption in smart campus network applications through simulation of high priority Service Traffic balancing prediction and fuzzy logic
Winter Simulation Conference, 2018Co-Authors: J Emiliano R Leite, Flavio R Massaro, Paulo Martins, Edson L UrsiniAbstract:In this work, we tackle power consumption reduction of battery-dependent devices in a smart campus (including hospital) application. These devices are connected by networked systems which may be subject to fluctuation of the message delays that control essential equipment. We show through five case studies using discrete event simulation that power consumption may be reduced using proper prioritization and balancing of the network emergency Traffic. A predictor algorithm and a fuzzy logic controller were used to indicate the level upon which the system must switch off the load in order to reduce power consumption. The analysis of a case study shows that a considerable reduction in power consumption was achieved through the reduction of message delays and also due to the fuzzy control of AC and lighting equipment.
Abdallah Shami - One of the best experts on this subject based on the ideXlab platform.
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energy efficient quality of Service Traffic scheduler for mimo downlink svd channels
IEEE Transactions on Wireless Communications, 2010Co-Authors: Daniel J Dechene, Abdallah ShamiAbstract:In this paper we focus on minimizing the long-term average power consumption of a single transmitter providing Quality of Service (QoS) enabled Traffic to a single receiver. Both the transmitting and receiving stations are equipped with multiple antennas. First, we present a general {Kx M} system model where K is the number of independently buffered QoS streams and M is the number of parallel channels available through MIMO SVD eigenmode transmission. Through application of the constrained Markov decision process (MDP) framework combined with a novel MAC layer rate assignment scheme, a randomized per-buffer scheduling policy is obtained. The designed policy exploits queue state information to schedule Traffic while meeting throughput, delay and loss constraints. Packets scheduled for transmission during each frame are mapped across the set eigenmode channels subject to available channel resources and the set of channel eigenvalues. Simulation results are provided for several scenarios. System drawbacks, limitations and extensions are also discussed.
B F Spencer - One of the best experts on this subject based on the ideXlab platform.
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railroad bridge monitoring using wireless smart sensors
Structural Control & Health Monitoring, 2017Co-Authors: Fernando Moreu, B F SpencerAbstract:Summary Railroads carry more than 40% of the freight, in terms of tons per mile transported in North America. A critical portion of the railroad infrastructure is the more than 100,000 bridges, which occur, on the average, every 1.4 miles of track. Railroads have a limited budget for capital investment. Therefore, decisions on which bridges to repair/replace become critical for both safety and economy. North American railroads regularly inspected bridges to ensure safe operation that can meet transport demands, using inspection reports to decide which bridges may need maintenance, replacement, or further investigation. Current bridge inspection practices recommend observing bridge responses under live load to help assess bridge condition. However, measuring bridge responses under train loads in the field is a challenging, expensive, and complex task. This research explores the potential of using wireless smart sensors (WSS) to measure bridge responses under revenue Service Traffic that can be used to inform bridge management decisions. Wireless strain gages installed on the rail measure real-time train loads. Wireless accelerometers and magnetic strain gages installed in the bridge measure associated bridge responses. The system is deployed and validated on a double-track steel truss bridge on the south side of Chicago, Illinois, owned by the Canadian National Railway. A calibrated finite element model of the bridge with known train input load estimated the responses of the bridge at arbitrary, unmeasured locations, showing the possibility of applying the system for decision making process. These results demonstrate the potential of WSS technology to assist with railroad bridge inspection and management practice. Copyright © 2016 John Wiley & Sons, Ltd.
J Emiliano R Leite - One of the best experts on this subject based on the ideXlab platform.
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reducing power consumption in smart campus network applications through simulation of high priority Service Traffic balancing prediction and fuzzy logic
Winter Simulation Conference, 2018Co-Authors: J Emiliano R Leite, Flavio R Massaro, Paulo Martins, Edson L UrsiniAbstract:In this work, we tackle power consumption reduction of battery-dependent devices in a smart campus (including hospital) application. These devices are connected by networked systems which may be subject to fluctuation of the message delays that control essential equipment. We show through five case studies using discrete event simulation that power consumption may be reduced using proper prioritization and balancing of the network emergency Traffic. A predictor algorithm and a fuzzy logic controller were used to indicate the level upon which the system must switch off the load in order to reduce power consumption. The analysis of a case study shows that a considerable reduction in power consumption was achieved through the reduction of message delays and also due to the fuzzy control of AC and lighting equipment.
Fernando Moreu - One of the best experts on this subject based on the ideXlab platform.
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railroad bridge monitoring using wireless smart sensors
Structural Control & Health Monitoring, 2017Co-Authors: Fernando Moreu, B F SpencerAbstract:Summary Railroads carry more than 40% of the freight, in terms of tons per mile transported in North America. A critical portion of the railroad infrastructure is the more than 100,000 bridges, which occur, on the average, every 1.4 miles of track. Railroads have a limited budget for capital investment. Therefore, decisions on which bridges to repair/replace become critical for both safety and economy. North American railroads regularly inspected bridges to ensure safe operation that can meet transport demands, using inspection reports to decide which bridges may need maintenance, replacement, or further investigation. Current bridge inspection practices recommend observing bridge responses under live load to help assess bridge condition. However, measuring bridge responses under train loads in the field is a challenging, expensive, and complex task. This research explores the potential of using wireless smart sensors (WSS) to measure bridge responses under revenue Service Traffic that can be used to inform bridge management decisions. Wireless strain gages installed on the rail measure real-time train loads. Wireless accelerometers and magnetic strain gages installed in the bridge measure associated bridge responses. The system is deployed and validated on a double-track steel truss bridge on the south side of Chicago, Illinois, owned by the Canadian National Railway. A calibrated finite element model of the bridge with known train input load estimated the responses of the bridge at arbitrary, unmeasured locations, showing the possibility of applying the system for decision making process. These results demonstrate the potential of WSS technology to assist with railroad bridge inspection and management practice. Copyright © 2016 John Wiley & Sons, Ltd.
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dynamic assessment of timber railroad bridges using displacements
Journal of Bridge Engineering, 2015Co-Authors: Fernando Moreu, F Spence, Robi E Kim, S Scola, Sooji Cho, A Kimmle, James Michael LafaveAbstract:Abstract Infrastructure spending is such a large component of a railroad budget that it must be prioritized to meet the concurrent safety and line capacity requirements. Current bridge inspection and rating practices recommend observing bridge movements under a live load to help assess bridge conditions. However, measuring bridge movements under trains in the field is a challenging task. Even when they are measured, the relationships between bridge displacements and different loads/speeds are generally unknown. The research reported herein shows the effects of known train loadings, speeds, and Traffic directions on the magnitude and frequency of displacements as measured on timber pile bents of a Class I railroad bridge. Researchers collected both vertical and transverse (lateral) displacements under revenue Service Traffic and work trains using LVDTs with a sampling frequency of 100 Hz. To investigate the effect of Traffic on timber railroad bridges, displacements were measured under crossing events at d...
