Anatomic accuracy, physiologic characteristics, and fidelity of very low birth weight infant airway simulators

Background Medical simulation training requires realistic simulators with high fidelity. This prospective multi-center study investigated anatomic precision, physiologic characteristics, and fidelity of four commercially available very low birth weight infant simulators. Methods We measured airway angles and distances in the simulators Premature AirwayPaul (SIMCharacters), Premature Anne (Laerdal Medical), Premie HAL S2209 (Gaumard), and Preterm Baby (Lifecast Body Simulation) using computer tomography and compared these to human cadavers of premature stillbirths. The simulators’ physiologic characteristics were tested, and highly experienced experts rated their physical and functional fidelity. Results The airway angles corresponded to those of the reference cadavers in three simulators. The nasal inlet to glottis distance and the mouth aperture to glottis distance were only accurate in one simulator. All simulators had airway resistances up to 20 times higher and compliances up to 19 times lower than published reference values. Fifty-six highly experienced experts gave three simulators (Premature AirwayPaul: 5.1 ± 1.0, Premature Anne 4.9 ± 1.1, Preterm Baby 5.0 ± 1.0) good overall ratings and one simulator (Premie HAL S2209: 2.8 ± 1.0) an unfavorable rating. Conclusion The simulator physiology deviated significantly from preterm infants’ reference values concerning resistance and compliance, potentially promoting a wrong ventilation technique. Impact Very low birth weight infant simulators showed physiological properties far deviating from corresponding patient reference values. Only ventilation with very high peak pressure achieved tidal volumes in the simulators, as aimed at in very low birth weight infants, potentially promoting a wrong ventilation technique. Compared to very low birth weight infant cadavers, most tested simulators accurately reproduced the anatomic angular relationships, but their airway dimensions were relatively too large for the represented body. The more professional experience the experts had, the lower they rated the very low birth weight infant simulators.

Routing in Opportunistic Networks: Implementation and Research Challenges

Opportunistic Networks can be defined as Delay Tolerant Network, which are formed dynamically with participating nodes’ help. Opportunistic Networks follows Store-Carry-Forward principle to deliver/route the data in the network. Routing in Opportunistic Network starts with the Seed Node (Source Node) which delivers the data with the help of Intermediate nodes. Intermediate nodes store the data while roaming in the network until it comes in contact with appropriate forwarding node (relay node) or destination node itself. An extensive literature survey is performed to analyse various routing protocols defined for Opportunistic Network. With mobility induced routing, establishing and maintaining the routing path is a major challenge. Further, Store-Carry-Forward routing paradigm imposes various challenges while implementing and executing the network. Due to the unavailability of the suitable relay node, data needs to be stored within the Node’s Memory, imposes buffer storage issues at the node level. Also, uncontrolled flooding may impose link-level Congestion and treated as overhead to maintain the network. Another major challenge can be maintaining the energy level of the nodes in the network. Recently developed ONE (Opportunistic Network Environment) Simulator is used to simulate and emulate the environment required by Opportunistic Network. Along with the extensive literature survey of the protocols, few of the existing protocols viz. Direct Delivery, ProPHET, Epidemic and Spray & Wait Routing are implemented using ONE Simulator to analyse their performance while in execution. Results are being compared, and the researchers’ future direction is identified to address the open problems and challenges in Opportunistic Network.

Evaluating different energized fracturing fluids using an integrated equation-of-state compositional hydraulic fracturing and reservoir simulator

Horizontal wells are often drilled and hydraulically fractured in tight reservoirs to produce hydrocarbons or heat. Different fracturing fluids such as slick water, gas, foam, gel, or a combination can be used with slick water being the most common fracturing fluid. In this paper, we study the impacts of different fracturing fluids on fractured well productivity using an in-house integrated hydraulic fracturing and reservoir simulator with an equation-of-state compositional model. We analyzed the fracture geometry, stress interference, proppant placement, and the subsequent well productivity using different fracturing fluids. The results clearly show that different fracturing fluids result in very different fracture shape, sand distribution, and water and hydrocarbon production. By conducting fracturing and production simulations in one simulator, we ensure that no physics and data loss occurs due to data migration between two different software packages for hydraulic fracturing and reservoir simulation. To the best of the authors’ knowledge, this is the first time that a single integrated equation-of-state compositional hydraulic fracturing and reservoir simulator has been presented and applied for well lifecycle simulation.

A centrality-based history prediction routing protocol for opportunistic networks

Opportunistic networks are a subclass of delay tolerant networks based on a novel communication paradigm that aims at transmitting messages by exploiting direct contacts among nodes, without the need of a predefined infrastructure. Typical characteristics of OppNet include high mobility, short radio range, intermittent links, unstable topology, sparse connectivity, to name a few. As such, routing in such networks is a challenging task since it relies on node cooperation. This thesis focuses on using the concept of centrality to alleviate this task. Unlike other nodes in the network, central nodes are more likely to act as communication hubs to facilitate the message forwarding. In this thesis, a recently proposed History-Based Prediction Routing protocol is redesigned using this concept, yielding the so-called centrality-based HBPR protocol. The proposed CHBPR is evaluated by simulations using the ONE simulator, showing superior performance compared to HBPR without centrality and the Epidemic protocol with centrality.

A centrality-based history prediction routing protocol for opportunistic networks

Opportunistic networks are a subclass of delay tolerant networks based on a novel communication paradigm that aims at transmitting messages by exploiting direct contacts among nodes, without the need of a predefined infrastructure. Typical characteristics of OppNet include high mobility, short radio range, intermittent links, unstable topology, sparse connectivity, to name a few. As such, routing in such networks is a challenging task since it relies on node cooperation. This thesis focuses on using the concept of centrality to alleviate this task. Unlike other nodes in the network, central nodes are more likely to act as communication hubs to facilitate the message forwarding. In this thesis, a recently proposed History-Based Prediction Routing protocol is redesigned using this concept, yielding the so-called centrality-based HBPR protocol. The proposed CHBPR is evaluated by simulations using the ONE simulator, showing superior performance compared to HBPR without centrality and the Epidemic protocol with centrality.

A history-based energy-efficient routing protocol for opportunistic networks

In this thesis, a history-based energy-efficient routing protocol (called AEHBPR) for opportunistic networks (OppNets) is proposed, which saves the energy consumption by avoiding unnecessary packets transmission in the network and by clearing the buffer of nodes carrying the copies of the already delivered packets. The proposed AEHBPR protocol is evaluated using the Opportunistic NEtwork (ONE) simulator with both synthetic and real mobility traces, showing a superior performance compared to the History-Based Prediction for Routing (HBPR) protocol and AEProphet, in terms of average remaining energy, number of dead nodes, number of delivered messages, and overhead ratio, where AEProphet is the ProPHet routing protocol for OppNets on which the same energy-aware mechanism has been implemented.

A history-based energy-efficient routing protocol for opportunistic networks

In this thesis, a history-based energy-efficient routing protocol (called AEHBPR) for opportunistic networks (OppNets) is proposed, which saves the energy consumption by avoiding unnecessary packets transmission in the network and by clearing the buffer of nodes carrying the copies of the already delivered packets. The proposed AEHBPR protocol is evaluated using the Opportunistic NEtwork (ONE) simulator with both synthetic and real mobility traces, showing a superior performance compared to the History-Based Prediction for Routing (HBPR) protocol and AEProphet, in terms of average remaining energy, number of dead nodes, number of delivered messages, and overhead ratio, where AEProphet is the ProPHet routing protocol for OppNets on which the same energy-aware mechanism has been implemented.

Performance Comparison of Fresh and Spray & Wait Protocol through ONE Simulator

Opportunistic Networks (OppNets) are becoming the prime interest for researchers day-by-day due to the large scope of further research into it. An opportunistic network is used to transmit data in an environment of intermittent connectivity. OppNet offers a variety of routing protocols based on different strategies. Each protocol has some pros and cons. Among the available ones, Fresh Routing Protocol and Spray-and-wait Routing Protocol are the most efficient routing protocols in terms of performance during data transmission. This paper aims to compare these two different routing protocols through simulation on the ground of standard performance metrics. It is believed that this simulation comparison will help upcoming researchers in the selection of appropriate routing protocol as per their requirement

Monitor Potential Attack Locations in a Specific Area within DTN Network

In this paper will discuss and examine message transmission from the attacker process within the scope of Delay Tolerance Networks (DTNs). DTNs are a new area of research that can be developed in networking. Delay-tolerant networks are those networks that may not have a complete path between networks end-to-end via direct links and may be under development for a long time. As part of the improvement, we will compare a survey of DTN routing protocols with a real region area, and then taking into account the possibilities of detecting the presence of areas of weakness that lead to penetration, which will occur in the nodes while on the move. In this study, we will use the ONE simulator to track messages within nodes.

Artificial Intelligence based rule base fire engine testing model for congestion handling in opportunistic networks

Opportunistic network is emerging as a research domain nowadays with the introduction of Internet of things phenomena. In recent years, storage level congestion issue due to handheld devices is considered as a key challenge to be handled in the opportunistic networks. The prime objective of conducting this research is to develop artificial intelligence rule-based fire engine model to be tested using artificial intelligence latest classification algorithms further implemented using ONE simulator tool over MaxProp protocol. The achieved results show 98% accuracy in terms of classification using k-fold validation technique over six algorithms. The achieved results have been compared with MaxProp protocol over evaluation parameters such as delivery ratio, throughput, routing load, and overhead; whereas delivery ratio increase about 20% for node level and 5% for buffer level and throughput tends to increase 500 and 150 kbps for network and buffer levels, respectively.