40 CFR 60.2655 - How do I renew my lapsed operator qualification?

Code of Federal Regulations, 2013 CFR

2013-07-01

... PROGRAMS (CONTINUED) STANDARDS OF PERFORMANCE FOR NEW STATIONARY SOURCES Emissions Guidelines and Compliance Times for Commercial and Industrial Solid Waste Incineration Units Model Rule-Operator Training...) For a lapse of less than 3 years, you must complete a standard annual refresher course described in...

Simulation of operating rules and discretional decisions using a fuzzy rule-based system integrated into a water resources management model

NASA Astrophysics Data System (ADS)

Macian-Sorribes, Hector; Pulido-Velazquez, Manuel

2013-04-01

Water resources systems are operated, mostly, using a set of pre-defined rules not regarding, usually, to an optimal allocation in terms of water use or economic benefits, but to historical and institutional reasons. These operating policies are reproduced, commonly, as hedging rules, pack rules or zone-based operations, and simulation models can be used to test their performance under a wide range of hydrological and/or socio-economic hypothesis. Despite the high degree of acceptation and testing that these models have achieved, the actual operation of water resources systems hardly follows all the time the pre-defined rules with the consequent uncertainty on the system performance. Real-world reservoir operation is very complex, affected by input uncertainty (imprecision in forecast inflow, seepage and evaporation losses, etc.), filtered by the reservoir operator's experience and natural risk-aversion, while considering the different physical and legal/institutional constraints in order to meet the different demands and system requirements. The aim of this work is to expose a fuzzy logic approach to derive and assess the historical operation of a system. This framework uses a fuzzy rule-based system to reproduce pre-defined rules and also to match as close as possible the actual decisions made by managers. After built up, the fuzzy rule-based system can be integrated in a water resources management model, making possible to assess the system performance at the basin scale. The case study of the Mijares basin (eastern Spain) is used to illustrate the method. A reservoir operating curve regulates the two main reservoir releases (operated in a conjunctive way) with the purpose of guaranteeing a high realiability of supply to the traditional irrigation districts with higher priority (more senior demands that funded the reservoir construction). A fuzzy rule-based system has been created to reproduce the operating curve's performance, defining the system state (total water stored in the reservoirs) and the month of the year as inputs; and the demand deliveries as outputs. The developed simulation management model integrates the fuzzy-ruled system of the operation of the two main reservoirs of the basin with the corresponding mass balance equations, the physical or boundary conditions and the water allocation rules among the competing demands. Historical information on inflow time series is used as inputs to the model simulation, being trained and validated using historical information on reservoir storage level and flow in several streams of the Mijares river. This methodology provides a more flexible and close to real policies approach. The model is easy to develop and to understand due to its rule-based structure, which mimics the human way of thinking. This can improve cooperation and negotiation between managers, decision-makers and stakeholders. The approach can be also applied to analyze the historical operation of the reservoir (what we have called a reservoir operation "audit").

14 CFR 91.1063 - Testing and training: Applicability and terms used.

Code of Federal Regulations, 2013 CFR

2013-01-01

... proficiency check requirements of § 91.1069. (iii) Testing requirements of § 91.1065. (iv) Recurrent flight... 14 Aeronautics and Space 2 2013-01-01 2013-01-01 false Testing and training: Applicability and... TRANSPORTATION (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Fractional...

14 CFR 91.1063 - Testing and training: Applicability and terms used.

Code of Federal Regulations, 2010 CFR

2010-01-01

... proficiency check requirements of § 91.1069. (iii) Testing requirements of § 91.1065. (iv) Recurrent flight... 14 Aeronautics and Space 2 2010-01-01 2010-01-01 false Testing and training: Applicability and... TRANSPORTATION (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Fractional...

14 CFR 91.1063 - Testing and training: Applicability and terms used.

Code of Federal Regulations, 2012 CFR

2012-01-01

... proficiency check requirements of § 91.1069. (iii) Testing requirements of § 91.1065. (iv) Recurrent flight... 14 Aeronautics and Space 2 2012-01-01 2012-01-01 false Testing and training: Applicability and... TRANSPORTATION (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Fractional...

14 CFR 91.1063 - Testing and training: Applicability and terms used.

Code of Federal Regulations, 2011 CFR

2011-01-01

... proficiency check requirements of § 91.1069. (iii) Testing requirements of § 91.1065. (iv) Recurrent flight... 14 Aeronautics and Space 2 2011-01-01 2011-01-01 false Testing and training: Applicability and... TRANSPORTATION (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Fractional...

14 CFR 91.1063 - Testing and training: Applicability and terms used.

Code of Federal Regulations, 2014 CFR

2014-01-01

... proficiency check requirements of § 91.1069. (iii) Testing requirements of § 91.1065. (iv) Recurrent flight... 14 Aeronautics and Space 2 2014-01-01 2014-01-01 false Testing and training: Applicability and... TRANSPORTATION (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Fractional...

78 FR 67799 - Qualification, Service, and Use of Crewmembers and Aircraft Dispatchers

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-12

...This final rule revises the training requirements for pilots in air carrier operations. The regulations enhance air carrier pilot training programs by emphasizing the development of pilots' manual handling skills and adding safety-critical tasks such as recovery from stall and upset. The final rule also requires enhanced runway safety training and pilot monitoring training to be incorporated into existing requirements for scenario-based flight training and requires air carriers to implement remedial training programs for pilots. The FAA expects these changes to contribute to a reduction in aviation accidents. Additionally, the final rule revises recordkeeping requirements for communications between the flightcrew and dispatch; ensures that personnel identified as flight attendants have completed flight attendant training and qualification requirements; provides civil enforcement authority for making fraudulent statements; and, provides a number of conforming and technical changes to existing air carrier crewmember training and qualification requirements. The final rule also includes provisions that provide opportunities for air carriers to modify training program requirements for flightcrew members when the air carrier operates multiple aircraft types with similar design and flight handling characteristics.

Application of Decision Tree to Obtain Optimal Operation Rules for Reservoir Flood Control Considering Sediment Desilting-Case Study of Tseng Wen Reservoir

NASA Astrophysics Data System (ADS)

ShiouWei, L.

2014-12-01

Reservoirs are the most important water resources facilities in Taiwan.However,due to the steep slope and fragile geological conditions in the mountain area,storm events usually cause serious debris flow and flood,and the flood then will flush large amount of sediment into reservoirs.The sedimentation caused by flood has great impact on the reservoirs life.Hence,how to operate a reservoir during flood events to increase the efficiency of sediment desilting without risk the reservoir safety and impact the water supply afterward is a crucial issue in Taiwan. 　Therefore,this study developed a novel optimization planning model for reservoir flood operation considering flood control and sediment desilting,and proposed easy to use operating rules represented by decision trees.The decision trees rules have considered flood mitigation,water supply and sediment desilting.The optimal planning model computes the optimal reservoir release for each flood event that minimum water supply impact and maximum sediment desilting without risk the reservoir safety.Beside the optimal flood operation planning model,this study also proposed decision tree based flood operating rules that were trained by the multiple optimal reservoir releases to synthesis flood scenarios.The synthesis flood scenarios consists of various synthesis storm events,reservoir's initial storage and target storages at the end of flood operating. 　Comparing the results operated by the decision tree operation rules(DTOR) with that by historical operation for Krosa Typhoon in 2007,the DTOR removed sediment 15.4% more than that of historical operation with reservoir storage only8.38×106m3 less than that of historical operation.For Jangmi Typhoon in 2008,the DTOR removed sediment 24.4% more than that of historical operation with reservoir storage only 7.58×106m3 less than that of historical operation.The results show that the proposed DTOR model can increase the sediment desilting efficiency and extend the reservoir life.

40 CFR 60.2660 - What site-specific documentation is required?

Code of Federal Regulations, 2014 CFR

2014-07-01

... PROGRAMS (CONTINUED) STANDARDS OF PERFORMANCE FOR NEW STATIONARY SOURCES Emissions Guidelines and Compliance Times for Commercial and Industrial Solid Waste Incineration Units Model Rule-Operator Training... and are suitable for inspection upon request. (1) Summary of the applicable standards under this...

40 CFR 60.2660 - What site-specific documentation is required?

Code of Federal Regulations, 2013 CFR

2013-07-01

... PROGRAMS (CONTINUED) STANDARDS OF PERFORMANCE FOR NEW STATIONARY SOURCES Emissions Guidelines and Compliance Times for Commercial and Industrial Solid Waste Incineration Units Model Rule-Operator Training... and are suitable for inspection upon request. (1) Summary of the applicable standards under this...

Modified Levenberg-Marquardt Method for RÖSSLER Chaotic System Fuzzy Modeling Training

NASA Astrophysics Data System (ADS)

Wang, Yu-Hui; Wu, Qing-Xian; Jiang, Chang-Sheng; Xue, Ya-Li; Fang, Wei

Generally, fuzzy approximation models require some human knowledge and experience. Operator's experience is involved in the mathematics of fuzzy theory as a collection of heuristic rules. The main goal of this paper is to present a new method for identifying unknown nonlinear dynamics such as Rössler system without any human knowledge. Instead of heuristic rules, the presented method uses the input-output data pairs to identify the Rössler chaotic system. The training algorithm is a modified Levenberg-Marquardt (L-M) method, which can adjust the parameters of each linear polynomial and fuzzy membership functions on line, and do not rely on experts' experience excessively. Finally, it is applied to training Rössler chaotic system fuzzy identification. Comparing this method with the standard L-M method, the convergence speed is accelerated. The simulation results demonstrate the effectiveness of the proposed method.

14 CFR 91.501 - Applicability.

Code of Federal Regulations, 2012 CFR

2012-01-01

.... (8) Passenger ground transportation. (9) Flight planning and weather contract services. (10) An... AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Large and Turbine-Powered Multiengine...) Ferry or training flights; (2) Aerial work operations such as aerial photography or survey, or pipeline...

14 CFR 91.501 - Applicability.

Code of Federal Regulations, 2010 CFR

2010-01-01

.... (8) Passenger ground transportation. (9) Flight planning and weather contract services. (10) An... AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Large and Turbine-Powered Multiengine...) Ferry or training flights; (2) Aerial work operations such as aerial photography or survey, or pipeline...

14 CFR 91.501 - Applicability.

Code of Federal Regulations, 2013 CFR

2013-01-01

.... (8) Passenger ground transportation. (9) Flight planning and weather contract services. (10) An... AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Large and Turbine-Powered Multiengine...) Ferry or training flights; (2) Aerial work operations such as aerial photography or survey, or pipeline...

14 CFR 91.501 - Applicability.

Code of Federal Regulations, 2011 CFR

2011-01-01

.... (8) Passenger ground transportation. (9) Flight planning and weather contract services. (10) An... AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Large and Turbine-Powered Multiengine...) Ferry or training flights; (2) Aerial work operations such as aerial photography or survey, or pipeline...

14 CFR 91.501 - Applicability.

Code of Federal Regulations, 2014 CFR

2014-01-01

.... (8) Passenger ground transportation. (9) Flight planning and weather contract services. (10) An... AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Large and Turbine-Powered Multiengine...) Ferry or training flights; (2) Aerial work operations such as aerial photography or survey, or pipeline...

14 CFR 91.711 - Special rules for foreign civil aircraft.

Code of Federal Regulations, 2014 CFR

2014-01-01

... aircraft of U.S. manufacture for the purpose of— (i) Flight testing the aircraft; (ii) Training foreign... TRANSPORTATION (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Foreign... States shall give flight notification or file a flight plan in accordance with the Supplementary...

14 CFR 91.711 - Special rules for foreign civil aircraft.

Code of Federal Regulations, 2013 CFR

2013-01-01

... aircraft of U.S. manufacture for the purpose of— (i) Flight testing the aircraft; (ii) Training foreign... TRANSPORTATION (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Foreign... States shall give flight notification or file a flight plan in accordance with the Supplementary...

14 CFR 91.711 - Special rules for foreign civil aircraft.

Code of Federal Regulations, 2012 CFR

2012-01-01

... aircraft of U.S. manufacture for the purpose of— (i) Flight testing the aircraft; (ii) Training foreign... TRANSPORTATION (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Foreign... States shall give flight notification or file a flight plan in accordance with the Supplementary...

14 CFR 91.711 - Special rules for foreign civil aircraft.

Code of Federal Regulations, 2011 CFR

2011-01-01

... aircraft of U.S. manufacture for the purpose of— (i) Flight testing the aircraft; (ii) Training foreign... TRANSPORTATION (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Foreign... States shall give flight notification or file a flight plan in accordance with the Supplementary...

The Design of Model-Based Training Programs

NASA Technical Reports Server (NTRS)

Polson, Peter; Sherry, Lance; Feary, Michael; Palmer, Everett; Alkin, Marty; McCrobie, Dan; Kelley, Jerry; Rosekind, Mark (Technical Monitor)

1997-01-01

This paper proposes a model-based training program for the skills necessary to operate advance avionics systems that incorporate advanced autopilots and fight management systems. The training model is based on a formalism, the operational procedure model, that represents the mission model, the rules, and the functions of a modem avionics system. This formalism has been defined such that it can be understood and shared by pilots, the avionics software, and design engineers. Each element of the software is defined in terms of its intent (What?), the rationale (Why?), and the resulting behavior (How?). The Advanced Computer Tutoring project at Carnegie Mellon University has developed a type of model-based, computer aided instructional technology called cognitive tutors. They summarize numerous studies showing that training times to a specified level of competence can be achieved in one third the time of conventional class room instruction. We are developing a similar model-based training program for the skills necessary to operation the avionics. The model underlying the instructional program and that simulates the effects of pilots entries and the behavior of the avionics is based on the operational procedure model. Pilots are given a series of vertical flightpath management problems. Entries that result in violations, such as failure to make a crossing restriction or violating the speed limits, result in error messages with instruction. At any time, the flightcrew can request suggestions on the appropriate set of actions. A similar and successful training program for basic skills for the FMS on the Boeing 737-300 was developed and evaluated. The results strongly support the claim that the training methodology can be adapted to the cockpit.

Evaluating Flight Crew Operator Manual Documentation

NASA Technical Reports Server (NTRS)

Sherry, Lance; Feary, Michael

1998-01-01

Aviation and cognitive science researchers have identified situations in which the pilot s expectations for the behavior of the avionics are not matched by the actual behavior of the avionics. Researchers have attributed these "automation surprises" to the complexity of the avionics mode logic, the absence of complete training, limitations in cockpit displays, and ad-hoc conceptual models of the avionics. Complete canonical rule-based descriptions of the behavior of the autopilot provide the basis for understanding the perceived complexity of the autopilots, the differences between the pilot s and autopilot s conceptual models, and the limitations in training materials and cockpit displays. This paper compares the behavior of the autopilot Vertical Speed/Flight Path Angle (VS-FPA) mode as described in the Flight Crew Operators Manual (FCOM) and the actual behavior of the VS-FPA mode defined in the autopilot software. This example demonstrates the use of the Operational Procedure Model (OPM) as a method for using the requirements specification for the design of the software logic as information requirements for training.

78 FR 37657 - Petition for Waiver of Compliance

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-21

... Division of the Regional Transportation Authority (Metra) and its operating company, the Northeast Illinois... CFR Part 236, Rules, Standards, and Instructions Governing the Installation, Inspection, Maintenance... each train operating in train stop, train control or cab signal territory; equipped. Specifically...

14 CFR 91.1433 - CAMP: Maintenance and preventive maintenance training program.

Code of Federal Regulations, 2010 CFR

2010-01-01

..., DEPARTMENT OF TRANSPORTATION (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Fractional Ownership Operations Program Management § 91.1433 CAMP: Maintenance and preventive... each person (including inspection personnel) who determines the adequacy of work done is fully informed...

Analysis 320 coal mine accidents using structural equation modeling with unsafe conditions of the rules and regulations as exogenous variables.

PubMed

Zhang, Yingyu; Shao, Wei; Zhang, Mengjia; Li, Hejun; Yin, Shijiu; Xu, Yingjun

2016-07-01

Mining has been historically considered as a naturally high-risk industry worldwide. Deaths caused by coal mine accidents are more than the sum of all other accidents in China. Statistics of 320 coal mine accidents in Shandong province show that all accidents contain indicators of "unsafe conditions of the rules and regulations" with a frequency of 1590, accounting for 74.3% of the total frequency of 2140. "Unsafe behaviors of the operator" is another important contributory factor, which mainly includes "operator error" and "venturing into dangerous places." A systems analysis approach was applied by using structural equation modeling (SEM) to examine the interactions between the contributory factors of coal mine accidents. The analysis of results leads to three conclusions. (i) "Unsafe conditions of the rules and regulations," affect the "unsafe behaviors of the operator," "unsafe conditions of the equipment," and "unsafe conditions of the environment." (ii) The three influencing factors of coal mine accidents (with the frequency of effect relation in descending order) are "lack of safety education and training," "rules and regulations of safety production responsibility," and "rules and regulations of supervision and inspection." (iii) The three influenced factors (with the frequency in descending order) of coal mine accidents are "venturing into dangerous places," "poor workplace environment," and "operator error." Copyright © 2016 Elsevier Ltd. All rights reserved.

Adaptive Neurons For Artificial Neural Networks

NASA Technical Reports Server (NTRS)

Tawel, Raoul

1990-01-01

Training time decreases dramatically. In improved mathematical model of neural-network processor, temperature of neurons (in addition to connection strengths, also called weights, of synapses) varied during supervised-learning phase of operation according to mathematical formalism and not heuristic rule. Evidence that biological neural networks also process information at neuronal level.

14 CFR 91.1087 - Approval of aircraft simulators and other training devices.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 2 2011-01-01 2011-01-01 false Approval of aircraft simulators and other... OF TRANSPORTATION (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Fractional Ownership Operations Program Management § 91.1087 Approval of aircraft simulators and...

14 CFR 91.1087 - Approval of aircraft simulators and other training devices.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 2 2012-01-01 2012-01-01 false Approval of aircraft simulators and other... OF TRANSPORTATION (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Fractional Ownership Operations Program Management § 91.1087 Approval of aircraft simulators and...

14 CFR 91.1087 - Approval of aircraft simulators and other training devices.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 14 Aeronautics and Space 2 2013-01-01 2013-01-01 false Approval of aircraft simulators and other... OF TRANSPORTATION (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Fractional Ownership Operations Program Management § 91.1087 Approval of aircraft simulators and...

14 CFR 91.1087 - Approval of aircraft simulators and other training devices.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 14 Aeronautics and Space 2 2014-01-01 2014-01-01 false Approval of aircraft simulators and other... OF TRANSPORTATION (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Fractional Ownership Operations Program Management § 91.1087 Approval of aircraft simulators and...

14 CFR 91.1097 - Pilot and flight attendant crewmember training programs.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 2 2012-01-01 2012-01-01 false Pilot and flight attendant crewmember..., DEPARTMENT OF TRANSPORTATION (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Fractional Ownership Operations Program Management § 91.1097 Pilot and flight attendant crewmember...

14 CFR 91.1097 - Pilot and flight attendant crewmember training programs.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 14 Aeronautics and Space 2 2014-01-01 2014-01-01 false Pilot and flight attendant crewmember..., DEPARTMENT OF TRANSPORTATION (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Fractional Ownership Operations Program Management § 91.1097 Pilot and flight attendant crewmember...

14 CFR 91.1097 - Pilot and flight attendant crewmember training programs.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 14 Aeronautics and Space 2 2013-01-01 2013-01-01 false Pilot and flight attendant crewmember..., DEPARTMENT OF TRANSPORTATION (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Fractional Ownership Operations Program Management § 91.1097 Pilot and flight attendant crewmember...

14 CFR 91.1103 - Pilots: Initial, transition, upgrade, requalification, and differences flight training.

Code of Federal Regulations, 2013 CFR

2013-01-01

... simulator or training device; and (2) A flight check in the aircraft or a check in the simulator or training..., requalification, and differences flight training. 91.1103 Section 91.1103 Aeronautics and Space FEDERAL AVIATION... OPERATING AND FLIGHT RULES Fractional Ownership Operations Program Management § 91.1103 Pilots: Initial...

14 CFR 91.1103 - Pilots: Initial, transition, upgrade, requalification, and differences flight training.

Code of Federal Regulations, 2014 CFR

2014-01-01

... simulator or training device; and (2) A flight check in the aircraft or a check in the simulator or training..., requalification, and differences flight training. 91.1103 Section 91.1103 Aeronautics and Space FEDERAL AVIATION... OPERATING AND FLIGHT RULES Fractional Ownership Operations Program Management § 91.1103 Pilots: Initial...

14 CFR 91.1103 - Pilots: Initial, transition, upgrade, requalification, and differences flight training.

Code of Federal Regulations, 2011 CFR

2011-01-01

... simulator or training device; and (2) A flight check in the aircraft or a check in the simulator or training..., requalification, and differences flight training. 91.1103 Section 91.1103 Aeronautics and Space FEDERAL AVIATION... OPERATING AND FLIGHT RULES Fractional Ownership Operations Program Management § 91.1103 Pilots: Initial...

14 CFR 91.1103 - Pilots: Initial, transition, upgrade, requalification, and differences flight training.

Code of Federal Regulations, 2012 CFR

2012-01-01

... simulator or training device; and (2) A flight check in the aircraft or a check in the simulator or training..., requalification, and differences flight training. 91.1103 Section 91.1103 Aeronautics and Space FEDERAL AVIATION... OPERATING AND FLIGHT RULES Fractional Ownership Operations Program Management § 91.1103 Pilots: Initial...

14 CFR 91.1103 - Pilots: Initial, transition, upgrade, requalification, and differences flight training.

Code of Federal Regulations, 2010 CFR

2010-01-01

... simulator or training device; and (2) A flight check in the aircraft or a check in the simulator or training..., requalification, and differences flight training. 91.1103 Section 91.1103 Aeronautics and Space FEDERAL AVIATION... OPERATING AND FLIGHT RULES Fractional Ownership Operations Program Management § 91.1103 Pilots: Initial...

14 CFR 142.53 - Training center instructor training and testing requirements.

Code of Federal Regulations, 2013 CFR

2013-01-01

... include instruction in— (i) Performance and analysis of flight training procedures and maneuvers... covering aircraft subsystems and operating rules applicable to the training courses that the instructor is...

14 CFR 142.53 - Training center instructor training and testing requirements.

Code of Federal Regulations, 2011 CFR

2011-01-01

... include instruction in— (i) Performance and analysis of flight training procedures and maneuvers... covering aircraft subsystems and operating rules applicable to the training courses that the instructor is...

14 CFR 142.53 - Training center instructor training and testing requirements.

Code of Federal Regulations, 2012 CFR

2012-01-01

... include instruction in— (i) Performance and analysis of flight training procedures and maneuvers... covering aircraft subsystems and operating rules applicable to the training courses that the instructor is...

14 CFR 142.53 - Training center instructor training and testing requirements.

Code of Federal Regulations, 2014 CFR

2014-01-01

... include instruction in— (i) Performance and analysis of flight training procedures and maneuvers... covering aircraft subsystems and operating rules applicable to the training courses that the instructor is...

An on-line modified least-mean-square algorithm for training neurofuzzy controllers.

PubMed

Tan, Woei Wan

2007-04-01

The problem hindering the use of data-driven modelling methods for training controllers on-line is the lack of control over the amount by which the plant is excited. As the operating schedule determines the information available on-line, the knowledge of the process may degrade if the setpoint remains constant for an extended period. This paper proposes an identification algorithm that alleviates "learning interference" by incorporating fuzzy theory into the normalized least-mean-square update rule. The ability of the proposed methodology to achieve faster learning is examined by employing the algorithm to train a neurofuzzy feedforward controller for controlling a liquid level process. Since the proposed identification strategy has similarities with the normalized least-mean-square update rule and the recursive least-square estimator, the on-line learning rates of these algorithms are also compared.

Evolving optimised decision rules for intrusion detection using particle swarm paradigm

NASA Astrophysics Data System (ADS)

Sivatha Sindhu, Siva S.; Geetha, S.; Kannan, A.

2012-12-01

The aim of this article is to construct a practical intrusion detection system (IDS) that properly analyses the statistics of network traffic pattern and classify them as normal or anomalous class. The objective of this article is to prove that the choice of effective network traffic features and a proficient machine-learning paradigm enhances the detection accuracy of IDS. In this article, a rule-based approach with a family of six decision tree classifiers, namely Decision Stump, C4.5, Naive Baye's Tree, Random Forest, Random Tree and Representative Tree model to perform the detection of anomalous network pattern is introduced. In particular, the proposed swarm optimisation-based approach selects instances that compose training set and optimised decision tree operate over this trained set producing classification rules with improved coverage, classification capability and generalisation ability. Experiment with the Knowledge Discovery and Data mining (KDD) data set which have information on traffic pattern, during normal and intrusive behaviour shows that the proposed algorithm produces optimised decision rules and outperforms other machine-learning algorithm.

49 CFR 240.125 - Criteria for testing knowledge.

Code of Federal Regulations, 2010 CFR

2010-10-01

... practices for the safe operation of trains. (c) The testing methods selected by the railroad shall be: (1) Designed to examine a person's knowledge of the railroad's rules and practices for the safe operation of...) Personal safety practices; (ii) Operating practices; (iii) Equipment inspection practices; (iv) Train...

Acquisition of Inductive Biconditional Reasoning Skills: Training of Simultaneous and Sequential Processing.

ERIC Educational Resources Information Center

Lee, Seong-Soo

1982-01-01

Tenth-grade students (n=144) received training on one of three processing methods: coding-mapping (simultaneous), coding only, or decision tree (sequential). The induced simultaneous processing strategy worked optimally under rule learning, while the sequential strategy was difficult to induce and/or not optimal for rule-learning operations.…

Targeted training of the decision rule benefits rule-guided behavior in Parkinson's disease.

PubMed

Ell, Shawn W

2013-12-01

The impact of Parkinson's disease (PD) on rule-guided behavior has received considerable attention in cognitive neuroscience. The majority of research has used PD as a model of dysfunction in frontostriatal networks, but very few attempts have been made to investigate the possibility of adapting common experimental techniques in an effort to identify the conditions that are most likely to facilitate successful performance. The present study investigated a targeted training paradigm designed to facilitate rule learning and application using rule-based categorization as a model task. Participants received targeted training in which there was no selective-attention demand (i.e., stimuli varied along a single, relevant dimension) or nontargeted training in which there was selective-attention demand (i.e., stimuli varied along a relevant dimension as well as an irrelevant dimension). Following training, all participants were tested on a rule-based task with selective-attention demand. During the test phase, PD patients who received targeted training performed similarly to control participants and outperformed patients who did not receive targeted training. As a preliminary test of the generalizability of the benefit of targeted training, a subset of the PD patients were tested on the Wisconsin card sorting task (WCST). PD patients who received targeted training outperformed PD patients who did not receive targeted training on several WCST performance measures. These data further characterize the contribution of frontostriatal circuitry to rule-guided behavior. Importantly, these data also suggest that PD patient impairment, on selective-attention-demanding tasks of rule-guided behavior, is not inevitable and highlight the potential benefit of targeted training.

A Bayesian model averaging method for the derivation of reservoir operating rules

NASA Astrophysics Data System (ADS)

Zhang, Jingwen; Liu, Pan; Wang, Hao; Lei, Xiaohui; Zhou, Yanlai

2015-09-01

Because the intrinsic dynamics among optimal decision making, inflow processes and reservoir characteristics are complex, functional forms of reservoir operating rules are always determined subjectively. As a result, the uncertainty of selecting form and/or model involved in reservoir operating rules must be analyzed and evaluated. In this study, we analyze the uncertainty of reservoir operating rules using the Bayesian model averaging (BMA) model. Three popular operating rules, namely piecewise linear regression, surface fitting and a least-squares support vector machine, are established based on the optimal deterministic reservoir operation. These individual models provide three-member decisions for the BMA combination, enabling the 90% release interval to be estimated by the Markov Chain Monte Carlo simulation. A case study of China's the Baise reservoir shows that: (1) the optimal deterministic reservoir operation, superior to any reservoir operating rules, is used as the samples to derive the rules; (2) the least-squares support vector machine model is more effective than both piecewise linear regression and surface fitting; (3) BMA outperforms any individual model of operating rules based on the optimal trajectories. It is revealed that the proposed model can reduce the uncertainty of operating rules, which is of great potential benefit in evaluating the confidence interval of decisions.

14 CFR 91.1083 - Crewmember emergency training.

Code of Federal Regulations, 2010 CFR

2010-01-01

... (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Fractional Ownership... passenger oxygen. (6) Removal of life rafts from the aircraft, inflation of the life rafts, use of lifelines, and boarding of passengers and crew, if applicable. (7) Donning and inflation of life vests and the...

Visual perceptual learning by operant conditioning training follows rules of contingency.

PubMed

Kim, Dongho; Seitz, Aaron R; Watanabe, Takeo

2015-01-01

Visual perceptual learning (VPL) can occur as a result of a repetitive stimulus-reward pairing in the absence of any task. This suggests that rules that guide Conditioning, such as stimulus-reward contingency (e.g. that stimulus predicts the likelihood of reward), may also guide the formation of VPL. To address this question, we trained subjects with an operant conditioning task in which there were contingencies between the response to one of three orientations and the presence of reward. Results showed that VPL only occurred for positive contingencies, but not for neutral or negative contingencies. These results suggest that the formation of VPL is influenced by similar rules that guide the process of Conditioning.

Visual perceptual learning by operant conditioning training follows rules of contingency

PubMed Central

Kim, Dongho; Seitz, Aaron R; Watanabe, Takeo

2015-01-01

Visual perceptual learning (VPL) can occur as a result of a repetitive stimulus-reward pairing in the absence of any task. This suggests that rules that guide Conditioning, such as stimulus-reward contingency (e.g. that stimulus predicts the likelihood of reward), may also guide the formation of VPL. To address this question, we trained subjects with an operant conditioning task in which there were contingencies between the response to one of three orientations and the presence of reward. Results showed that VPL only occurred for positive contingencies, but not for neutral or negative contingencies. These results suggest that the formation of VPL is influenced by similar rules that guide the process of Conditioning. PMID:26028984

Infrared small target detection based on Danger Theory

NASA Astrophysics Data System (ADS)

Lan, Jinhui; Yang, Xiao

2009-11-01

To solve the problem that traditional method can't detect the small objects whose local SNR is less than 2 in IR images, a Danger Theory-based model to detect infrared small target is presented in this paper. First, on the analog with immunology, the definition is given, in this paper, to such terms as dangerous signal, antigens, APC, antibodies. Besides, matching rule between antigen and antibody is improved. Prior to training the detection model and detecting the targets, the IR images are processed utilizing adaptive smooth filter to decrease the stochastic noise. Then at the training process, deleting rule, generating rule, crossover rule and the mutation rule are established after a large number of experiments in order to realize immediate convergence and obtain good antibodies. The Danger Theory-based model is built after the training process, and this model can detect the target whose local SNR is only 1.5.

20 CFR 616.4 - Rules, regulations, procedures, forms-resolution of disagreements.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 20 Employees' Benefits 3 2010-04-01 2010-04-01 false Rules, regulations, procedures, forms-resolution of disagreements. 616.4 Section 616.4 Employees' Benefits EMPLOYMENT AND TRAINING ADMINISTRATION..., procedures, forms—resolution of disagreements. All State agencies shall operate in accordance with such rules...

Achieving Accreditation Council for Graduate Medical Education duty hours compliance within advanced surgical training: a simulation-based feasibility assessment.

PubMed

Obi, Andrea; Chung, Jennifer; Chen, Ryan; Lin, Wandi; Sun, Siyuan; Pozehl, William; Cohn, Amy M; Daskin, Mark S; Seagull, F Jacob; Reddy, Rishindra M

2015-11-01

Certain operative cases occur unpredictably and/or have long operative times, creating a conflict between Accreditation Council for Graduate Medical Education (ACGME) rules and adequate training experience. A ProModel-based simulation was developed based on historical data. Probabilistic distributions of operative time calculated and combined with an ACGME compliant call schedule. For the advanced surgical cases modeled (cardiothoracic transplants), 80-hour violations were 6.07% and the minimum number of days off was violated 22.50%. There was a 36% chance of failure to fulfill any (either heart or lung) minimum case requirement despite adequate volume. The variable nature of emergency cases inevitably leads to work hour violations under ACGME regulations. Unpredictable cases mandate higher operative volume to ensure achievement of adequate caseloads. Publically available simulation technology provides a valuable avenue to identify adequacy of case volumes for trainees in both the elective and emergency setting. Copyright © 2015 Elsevier Inc. All rights reserved.

14 CFR 133.37 - Crewmember training, currency, and testing requirements.

Code of Federal Regulations, 2010 CFR

2010-01-01

... requirements. 133.37 Section 133.37 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF... ROTORCRAFT EXTERNAL-LOAD OPERATIONS Operating Rules and Related Requirements § 133.37 Crewmember training... Administrator knowledge and skill with respect to the rotorcraft-load combination in accordance with § 133.23...

14 CFR 135.329 - Crewmember training requirements.

Code of Federal Regulations, 2010 CFR

2010-01-01

... of the crewmember: (1) Basic indoctrination ground training for newly hired crewmembers including... 14 Aeronautics and Space 3 2010-01-01 2010-01-01 false Crewmember training requirements. 135.329... REQUIREMENTS: COMMUTER AND ON DEMAND OPERATIONS AND RULES GOVERNING PERSONS ON BOARD SUCH AIRCRAFT Training...

75 FR 72664 - System Personnel Training Reliability Standards

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-26

...Under section 215 of the Federal Power Act, the Commission approves two Personnel Performance, Training and Qualifications (PER) Reliability Standards, PER-004-2 (Reliability Coordination--Staffing) and PER-005-1 (System Personnel Training), submitted to the Commission for approval by the North American Electric Reliability Corporation, the Electric Reliability Organization certified by the Commission. The approved Reliability Standards require reliability coordinators, balancing authorities, and transmission operators to establish a training program for their system operators, verify each of their system operators' capability to perform tasks, and provide emergency operations training to every system operator. The Commission also approves NERC's proposal to retire two existing PER Reliability Standards that are replaced by the standards approved in this Final Rule.

Design of operating rules in complex water resources systems using historical records, expert criteria and fuzzy logic

NASA Astrophysics Data System (ADS)

Pulido-Velazquez, Manuel; Macian-Sorribes, Hector; María Benlliure-Moreno, Jose; Fullana-Montoro, Juan

2015-04-01

Water resources systems in areas with a strong tradition in water use are complex to manage by the high amount of constraints that overlap in time and space, creating a complicated framework in which past, present and future collide between them. In addition, it is usual to find "hidden constraints" in system operations, which condition operation decisions being unnoticed by anyone but the river managers and users. Being aware of those hidden constraints requires usually years of experience and a degree of involvement in that system's management operations normally beyond the possibilities of technicians. However, their impact in the management decisions is strongly imprinted in the historical data records available. The purpose of this contribution is to present a methodology capable of assessing operating rules in complex water resources systems combining historical records and expert criteria. Both sources are coupled using fuzzy logic. The procedure stages are: 1) organize expert-technicians preliminary meetings to let the first explain how they manage the system; 2) set up a fuzzy rule-based system (FRB) structure according to the way the system is managed; 3) use the historical records available to estimate the inputs' fuzzy numbers, to assign preliminary output values to the FRB rules and to train and validate these rules; 4) organize expert-technician meetings to discuss the rule structure and the input's quantification, returning if required to the second stage; 5) once the FRB structure is accepted, its output values must be refined and completed with the aid of the experts by using meetings, workshops or surveys; 6) combine the FRB with a Decision Support System (DSS) to simulate the effect of those management decisions; 7) compare its results with the ones offered by the historical records and/or simulation or optimization models; and 8) discuss with the stakeholders the model performance returning, if it's required, to the fifth or the second stage. The methodology proposed has been applied to the Jucar River Basin (Spain). This basin has 3 reservoirs, 4 headwaters, 11 demands and 5 environmental flows; which form together a complex constraint set. After the preliminary meetings, one 81-rule FRB was created, using as inputs the system state variables at the start of the hydrologic year, and as outputs the target reservoir release schedule. The inputs' fuzzy numbers were estimated jointly using surveys. Fifteen years of historical records were used to train the system's outputs. The obtained FRB was then refined during additional expert-technician meetings. After that, the resulting FRB was introduced into a DSS simulating the effect of those management rules for different hydrological conditions. Three additional FRB's were created using: 1) exclusively the historical records; 2) a stochastic optimization model; and 3) a deterministic optimization model. The results proved to be consistent with the expectations, with the stakeholder's FRB performance located between the data-driven simulation and the stochastic optimization FRB's; and reflect the stakeholders' major goals and concerns about the river management. ACKNOWLEDGEMENT: This study has been partially supported by the IMPADAPT project (CGL2013-48424-C2-1-R) with Spanish MINECO (Ministerio de Economía y Competitividad) funds.

Dense modifiable interconnections utilizing photorefractive volume holograms

NASA Astrophysics Data System (ADS)

Psaltis, Demetri; Qiao, Yong

1990-11-01

This report describes an experimental two-layer optical neural network built at Caltech. The system uses photorefractive volume holograms to implement dense, modifiable synaptic interconnections and liquid crystal light valves (LCVS) to perform nonlinear thresholding operations. Kanerva's Sparse, Distributed Memory was implemented using this network and its ability to recognize handwritten character-alphabet (A-Z) has been demonstrated experimentally. According to Kanerva's model, the first layer has fixed, random weights of interconnections and the second layer is trained by sum-of-outer-products rule. After training, the recognition rates of the network on the training set (104 patterns) and test set (520 patterns) are 100 and 50 percent, respectively.

Assessing Prior Experience in the Selection of Air Traffic Control Specialists

DTIC Science & Technology

2013-04-01

Crosstabulation --------------------------B1 APPENDIX C: IFR Operations Experience • Academy Training Performance Crosstabulation ---------C1 APPENDIX...Control Specialist (ATCS) rating? (n=9,333) BQ35 – Do you have prior Instrument Flight Rules ( IFR ) operations experience? (n = 9,349) 2. Hold or...not have a prior ATCS rating. Do you have prior IFR (Instrument Flight Rules) Operations experience? Of the 9,349 respondents to this question

14 CFR 141.79 - Flight training.

Code of Federal Regulations, 2010 CFR

2010-01-01

... OTHER CERTIFICATED AGENCIES PILOT SCHOOLS Operating Rules § 141.79 Flight training. (a) No person other than a certificated flight instructor or commercial pilot with a lighter-than-air rating who has the... student flight training under an approved course of training. (b) No student pilot may be authorized to...

49 CFR 236.528 - Restrictive condition resulting from open hand-operated switch; requirement.

Code of Federal Regulations, 2010 CFR

2010-10-01

... INSTRUCTIONS GOVERNING THE INSTALLATION, INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Rules and... with circuit controller is used, the resultant restrictive condition of an automatic train stop or...

49 CFR 236.528 - Restrictive condition resulting from open hand-operated switch; requirement.

Code of Federal Regulations, 2011 CFR

2011-10-01

... INSTRUCTIONS GOVERNING THE INSTALLATION, INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Rules and... with circuit controller is used, the resultant restrictive condition of an automatic train stop or...

14 CFR 141.81 - Ground training.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 3 2010-01-01 2010-01-01 false Ground training. 141.81 Section 141.81... OTHER CERTIFICATED AGENCIES PILOT SCHOOLS Operating Rules § 141.81 Ground training. (a) Except as provided in paragraph (b) of this section, each instructor who is assigned to a ground training course must...

14 CFR 141.81 - Ground training.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 3 2011-01-01 2011-01-01 false Ground training. 141.81 Section 141.81... OTHER CERTIFICATED AGENCIES PILOT SCHOOLS Operating Rules § 141.81 Ground training. (a) Except as provided in paragraph (b) of this section, each instructor who is assigned to a ground training course must...

14 CFR 141.91 - Satellite bases.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 3 2011-01-01 2011-01-01 false Satellite bases. 141.91 Section 141.91... OTHER CERTIFICATED AGENCIES PILOT SCHOOLS Operating Rules § 141.91 Satellite bases. The holder of a... training in an approved course of training at a base other than its main operations base if: (a) An...

14 CFR 141.91 - Satellite bases.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 14 Aeronautics and Space 3 2013-01-01 2013-01-01 false Satellite bases. 141.91 Section 141.91... OTHER CERTIFICATED AGENCIES PILOT SCHOOLS Operating Rules § 141.91 Satellite bases. The holder of a... training in an approved course of training at a base other than its main operations base if: (a) An...

14 CFR 141.91 - Satellite bases.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 3 2012-01-01 2012-01-01 false Satellite bases. 141.91 Section 141.91... OTHER CERTIFICATED AGENCIES PILOT SCHOOLS Operating Rules § 141.91 Satellite bases. The holder of a... training in an approved course of training at a base other than its main operations base if: (a) An...

14 CFR 141.91 - Satellite bases.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 3 2010-01-01 2010-01-01 false Satellite bases. 141.91 Section 141.91... OTHER CERTIFICATED AGENCIES PILOT SCHOOLS Operating Rules § 141.91 Satellite bases. The holder of a... training in an approved course of training at a base other than its main operations base if: (a) An...

49 CFR 236.329 - Bolt lock.

Code of Federal Regulations, 2010 CFR

2010-10-01

... TRANSPORTATION RULES, STANDARDS, AND INSTRUCTIONS GOVERNING THE INSTALLATION, INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Interlocking Rules and Instructions... derail and displaying an aspect indicating stop cannot be operated to display a less restrictive aspect...

14 CFR 91.161 - Special awareness training required for pilots flying under visual flight rules within a 60...

Code of Federal Regulations, 2012 CFR

2012-01-01

... pilots flying under visual flight rules within a 60-nautical mile radius of the Washington, DC VOR/DME... flight rules within a 60-nautical mile radius of the Washington, DC VOR/DME. (a) Operations within a 60-nautical mile radius of the Washington, DC VOR/DME under visual flight rules (VFR). Except as provided...

14 CFR 91.161 - Special awareness training required for pilots flying under visual flight rules within a 60...

Code of Federal Regulations, 2011 CFR

2011-01-01

... pilots flying under visual flight rules within a 60-nautical mile radius of the Washington, DC VOR/DME... flight rules within a 60-nautical mile radius of the Washington, DC VOR/DME. (a) Operations within a 60-nautical mile radius of the Washington, DC VOR/DME under visual flight rules (VFR). Except as provided...

14 CFR 91.161 - Special awareness training required for pilots flying under visual flight rules within a 60...

Code of Federal Regulations, 2013 CFR

2013-01-01

... pilots flying under visual flight rules within a 60-nautical mile radius of the Washington, DC VOR/DME... flight rules within a 60-nautical mile radius of the Washington, DC VOR/DME. (a) Operations within a 60-nautical mile radius of the Washington, DC VOR/DME under visual flight rules (VFR). Except as provided...

14 CFR 91.161 - Special awareness training required for pilots flying under visual flight rules within a 60...

Code of Federal Regulations, 2014 CFR

2014-01-01

... pilots flying under visual flight rules within a 60-nautical mile radius of the Washington, DC VOR/DME... flight rules within a 60-nautical mile radius of the Washington, DC VOR/DME. (a) Operations within a 60-nautical mile radius of the Washington, DC VOR/DME under visual flight rules (VFR). Except as provided...

16 CFR 437.1 - The Rule.

Code of Federal Regulations, 2010 CFR

2010-01-01

... operating officer, financial, business opportunity marketing, training and service officers). With regard to... the management of the business opportunity seller, a statement disclosing: (i) The nature and extent... CONCERNING BUSINESS OPPORTUNITIES § 437.1 The Rule. In connection with the advertising, offering, licensing...

Individual differences in learning and transfer: stable tendencies for learning exemplars versus abstracting rules.

PubMed

McDaniel, Mark A; Cahill, Michael J; Robbins, Mathew; Wiener, Chelsea

2014-04-01

We hypothesize that during training some learners may focus on acquiring the particular exemplars and responses associated with the exemplars (termed exemplar learners), whereas other learners attempt to abstract underlying regularities reflected in the particular exemplars linked to an appropriate response (termed rule learners). Supporting this distinction, after training (on a function-learning task), participants displayed an extrapolation profile reflecting either acquisition of the trained cue-criterion associations (exemplar learners) or abstraction of the function rule (rule learners; Studies 1a and 1b). Further, working memory capacity (measured by operation span [Ospan]) was associated with the tendency to rely on rule versus exemplar processes. Studies 1c and 2 examined the persistence of these learning tendencies on several categorization tasks. Study 1c showed that rule learners were more likely than exemplar learners (indexed a priori by extrapolation profiles) to resist using idiosyncratic features (exemplar similarity) in generalization (transfer) of the trained category. Study 2 showed that the rule learners but not the exemplar learners performed well on a novel categorization task (transfer) after training on an abstract coherent category. These patterns suggest that in complex conceptual tasks, (a) individuals tend to either focus on exemplars during learning or on extracting some abstraction of the concept, (b) this tendency might be a relatively stable characteristic of the individual, and (c) transfer patterns are determined by that tendency.

Preparing Specialized Undergraduate Pilot Training Graduates for F-35A Training

DTIC Science & Technology

2010-06-11

the two sides of this argument and analyze the new data acquired from an F-22A lead-in program and the fact that the F-35A has started flying with...flight operations under Instrument or Visual Flight Rules to include day / night IFR operations in the terminal and enroute environment. Have limited

14 CFR 141.79 - Flight training.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 3 2012-01-01 2012-01-01 false Flight training. 141.79 Section 141.79... OTHER CERTIFICATED AGENCIES PILOT SCHOOLS Operating Rules § 141.79 Flight training. (a) No person other than a certificated flight instructor or commercial pilot with a lighter-than-air rating who has the...

14 CFR 141.79 - Flight training.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 14 Aeronautics and Space 3 2013-01-01 2013-01-01 false Flight training. 141.79 Section 141.79... OTHER CERTIFICATED AGENCIES PILOT SCHOOLS Operating Rules § 141.79 Flight training. (a) No person other than a certificated flight instructor or commercial pilot with a lighter-than-air rating who has the...

14 CFR 141.79 - Flight training.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 3 2011-01-01 2011-01-01 false Flight training. 141.79 Section 141.79... OTHER CERTIFICATED AGENCIES PILOT SCHOOLS Operating Rules § 141.79 Flight training. (a) No person other than a certificated flight instructor or commercial pilot with a lighter-than-air rating who has the...

14 CFR 141.79 - Flight training.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 14 Aeronautics and Space 3 2014-01-01 2014-01-01 false Flight training. 141.79 Section 141.79... OTHER CERTIFICATED AGENCIES PILOT SCHOOLS Operating Rules § 141.79 Flight training. (a) No person other than a certificated flight instructor or commercial pilot with a lighter-than-air rating who has the...

75 FR 25037 - Lead; Clearance and Clearance Testing Requirements for the Renovation, Repair, and Painting Program

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-06

.... Other technical and trade schools (NAICS code 611519), e.g., training providers. Engineering services... Renovation, Repair, and Painting Program (RRP) rule that established accreditation, training, certification... operate a training program for individuals who perform any of these activities. ``Target housing'' is...

14 CFR 91.1097 - Pilot and flight attendant crewmember training programs.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 2 2011-01-01 2011-01-01 false Pilot and flight attendant crewmember... RULES Fractional Ownership Operations Program Management § 91.1097 Pilot and flight attendant crewmember training programs. (a) Each program manager must establish and maintain an approved pilot training program...

14 CFR 91.1097 - Pilot and flight attendant crewmember training programs.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 2 2010-01-01 2010-01-01 false Pilot and flight attendant crewmember... RULES Fractional Ownership Operations Program Management § 91.1097 Pilot and flight attendant crewmember training programs. (a) Each program manager must establish and maintain an approved pilot training program...

Rasmussen's model of human behavior in laparoscopy training.

PubMed

Wentink, M; Stassen, L P S; Alwayn, I; Hosman, R J A W; Stassen, H G

2003-08-01

Compared to aviation, where virtual reality (VR) training has been standardized and simulators have proven their benefits, the objectives, needs, and means of VR training in minimally invasive surgery (MIS) still have to be established. The aim of the study presented is to introduce Rasmussen's model of human behavior as a practical framework for the definition of the training objectives, needs, and means in MIS. Rasmussen distinguishes three levels of human behavior: skill-, rule-, and knowledge-based behaviour. The training needs of a laparoscopic novice can be determined by identifying the specific skill-, rule-, and knowledge-based behavior that is required for performing safe laparoscopy. Future objectives of VR laparoscopy trainers should address all three levels of behavior. Although most commercially available simulators for laparoscopy aim at training skill-based behavior, especially the training of knowledge-based behavior during complications in surgery will improve safety levels. However, the cost and complexity of a training means increases when the training objectives proceed from the training of skill-based behavior to the training of complex knowledge-based behavior. In aviation, human behavior models have been used successfully to integrate the training of skill-, rule-, and knowledge-based behavior in a full flight simulator. Understanding surgeon behavior is one of the first steps towards a future full-scale laparoscopy simulator.

14 CFR 91.126 - Operating on or in the vicinity of an airport in Class G airspace.

Code of Federal Regulations, 2012 CFR

2012-01-01

..., DEPARTMENT OF TRANSPORTATION (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT... parachute must avoid the flow of fixed-wing aircraft. (c) Flap settings. Except when necessary for training...

14 CFR 91.126 - Operating on or in the vicinity of an airport in Class G airspace.

Code of Federal Regulations, 2011 CFR

2011-01-01

..., DEPARTMENT OF TRANSPORTATION (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT... parachute must avoid the flow of fixed-wing aircraft. (c) Flap settings. Except when necessary for training...

14 CFR 91.126 - Operating on or in the vicinity of an airport in Class G airspace.

Code of Federal Regulations, 2014 CFR

2014-01-01

..., DEPARTMENT OF TRANSPORTATION (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT... parachute must avoid the flow of fixed-wing aircraft. (c) Flap settings. Except when necessary for training...

14 CFR 91.126 - Operating on or in the vicinity of an airport in Class G airspace.

Code of Federal Regulations, 2013 CFR

2013-01-01

..., DEPARTMENT OF TRANSPORTATION (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT... parachute must avoid the flow of fixed-wing aircraft. (c) Flap settings. Except when necessary for training...

Autonomous Flight Rules Concept: User Implementation Costs and Strategies

NASA Technical Reports Server (NTRS)

Cotton, William B.; Hilb, Robert

2014-01-01

The costs to implement Autonomous Flight Rules (AFR) were examined for estimates in acquisition, installation, training and operations. The user categories were airlines, fractional operators, general aviation and unmanned aircraft systems. Transition strategies to minimize costs while maximizing operational benefits were also analyzed. The primary cost category was found to be the avionics acquisition. Cost ranges for AFR equipment were given to reflect the uncertainty of the certification level for the equipment and the extent of existing compatible avionics in the aircraft to be modified.

Efficient probabilistic inference in generic neural networks trained with non-probabilistic feedback.

PubMed

Orhan, A Emin; Ma, Wei Ji

2017-07-26

Animals perform near-optimal probabilistic inference in a wide range of psychophysical tasks. Probabilistic inference requires trial-to-trial representation of the uncertainties associated with task variables and subsequent use of this representation. Previous work has implemented such computations using neural networks with hand-crafted and task-dependent operations. We show that generic neural networks trained with a simple error-based learning rule perform near-optimal probabilistic inference in nine common psychophysical tasks. In a probabilistic categorization task, error-based learning in a generic network simultaneously explains a monkey's learning curve and the evolution of qualitative aspects of its choice behavior. In all tasks, the number of neurons required for a given level of performance grows sublinearly with the input population size, a substantial improvement on previous implementations of probabilistic inference. The trained networks develop a novel sparsity-based probabilistic population code. Our results suggest that probabilistic inference emerges naturally in generic neural networks trained with error-based learning rules.Behavioural tasks often require probability distributions to be inferred about task specific variables. Here, the authors demonstrate that generic neural networks can be trained using a simple error-based learning rule to perform such probabilistic computations efficiently without any need for task specific operations.

IOTA Simple Rules in Differentiating between Benign and Malignant Adnexal Masses by Non-expert Examiners.

PubMed

Tinnangwattana, Dangcheewan; Vichak-Ururote, Linlada; Tontivuthikul, Paponrad; Charoenratana, Cholaros; Lerthiranwong, Thitikarn; Tongsong, Theera

2015-01-01

To evaluate the diagnostic performance of IOTA simple rules in predicting malignant adnexal tumors by non-expert examiners. Five obstetric/gynecologic residents, who had never performed gynecologic ultrasound examination by themselves before, were trained for IOTA simple rules by an experienced examiner. One trained resident performed ultrasound examinations including IOTA simple rules on 100 women, who were scheduled for surgery due to ovarian masses, within 24 hours of surgery. The gold standard diagnosis was based on pathological or operative findings. The five-trained residents performed IOTA simple rules on 30 patients for evaluation of inter-observer variability. A total of 100 patients underwent ultrasound examination for the IOTA simple rules. Of them, IOTA simple rules could be applied in 94 (94%) masses including 71 (71.0%) benign masses and 29 (29.0%) malignant masses. The diagnostic performance of IOTA simple rules showed sensitivity of 89.3% (95%CI, 77.8%; 100.7%), specificity 83.3% (95%CI, 74.3%; 92.3%). Inter-observer variability was analyzed using Cohen's kappa coefficient. Kappa indices of the four pairs of raters are 0.713-0.884 (0.722, 0.827, 0.713, and 0.884). IOTA simple rules have high diagnostic performance in discriminating adnexal masses even when are applied by non-expert sonographers, though a training course may be required. Nevertheless, they should be further tested by a greater number of general practitioners before widely use.

Deriving adaptive operating rules of hydropower reservoirs using time-varying parameters generated by the EnKF

NASA Astrophysics Data System (ADS)

Feng, Maoyuan; Liu, Pan; Guo, Shenglian; Shi, Liangsheng; Deng, Chao; Ming, Bo

2017-08-01

Operating rules have been used widely to decide reservoir operations because of their capacity for coping with uncertain inflow. However, stationary operating rules lack adaptability; thus, under changing environmental conditions, they cause inefficient reservoir operation. This paper derives adaptive operating rules based on time-varying parameters generated using the ensemble Kalman filter (EnKF). A deterministic optimization model is established to obtain optimal water releases, which are further taken as observations of the reservoir simulation model. The EnKF is formulated to update the operating rules sequentially, providing a series of time-varying parameters. To identify the index that dominates the variations of the operating rules, three hydrologic factors are selected: the reservoir inflow, ratio of future inflow to current available water, and available water. Finally, adaptive operating rules are derived by fitting the time-varying parameters with the identified dominant hydrologic factor. China's Three Gorges Reservoir was selected as a case study. Results show that (1) the EnKF has the capability of capturing the variations of the operating rules, (2) reservoir inflow is the factor that dominates the variations of the operating rules, and (3) the derived adaptive operating rules are effective in improving hydropower benefits compared with stationary operating rules. The insightful findings of this study could be used to help adapt reservoir operations to mitigate the effects of changing environmental conditions.

49 CFR 236.567 - Restrictions imposed when device fails and/or is cut out en route.

Code of Federal Regulations, 2011 CFR

2011-10-01

... GOVERNING THE INSTALLATION, INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Rules and Instructions... restricted speed or if an automatic block signal system is in operation according to signal indication but...

14 CFR 135.433 - Maintenance and preventive maintenance training program.

Code of Federal Regulations, 2010 CFR

2010-01-01

... OPERATIONS OPERATING REQUIREMENTS: COMMUTER AND ON DEMAND OPERATIONS AND RULES GOVERNING PERSONS ON BOARD... personnel) who determines the adequacy of work done is fully informed about procedures and techniques and new equipment in use and is competent to perform that person's duties. ...

Training "Rule-of-(E)": Further Investigation of a Previously Successful Intervention for a Spelling Rule in Developmental Mixed Dysgraphia

ERIC Educational Resources Information Center

Kohnen, Saskia; Nickels, Lyndsey; Coltheart, Max

2010-01-01

This paper reports a single case treatment study conducted with R.F.L., a young man with developmental mixed dysgraphia. The intervention focused on teaching spelling rules and was a replication of a previous successful study. The results of the present study provided further insights into the mechanism that operates to update faulty lexical…

49 CFR 213.307 - Class of track: operating speed limits.

Code of Federal Regulations, 2011 CFR

2011-10-01

... operating speed for trains 1 is— Class 6 track 110 m.p.h. Class 7 track 125 m.p.h. Class 8 track 160 m.p.h. 2 Class 9 track 200 m.p.h. 1 Freight may be transported at passenger train speeds if the following... 150 m.p.h. are authorized by this part only in conjunction with a rule of particular applicability...

Modelling of Reservoir Operations using Fuzzy Logic and ANNs

NASA Astrophysics Data System (ADS)

Van De Giesen, N.; Coerver, B.; Rutten, M.

2015-12-01

Today, almost 40.000 large reservoirs, containing approximately 6.000 km3 of water and inundating an area of almost 400.000 km2, can be found on earth. Since these reservoirs have a storage capacity of almost one-sixth of the global annual river discharge they have a large impact on the timing, volume and peaks of river discharges. Global Hydrological Models (GHM) are thus significantly influenced by these anthropogenic changes in river flows. We developed a parametrically parsimonious method to extract operational rules based on historical reservoir storage and inflow time-series. Managing a reservoir is an imprecise and vague undertaking. Operators always face uncertainties about inflows, evaporation, seepage losses and various water demands to be met. They often base their decisions on experience and on available information, like reservoir storage and the previous periods inflow. We modeled this decision-making process through a combination of fuzzy logic and artificial neural networks in an Adaptive-Network-based Fuzzy Inference System (ANFIS). In a sensitivity analysis, we compared results for reservoirs in Vietnam, Central Asia and the USA. ANFIS can indeed capture reservoirs operations adequately when fed with a historical monthly time-series of inflows and storage. It was shown that using ANFIS, operational rules of existing reservoirs can be derived without much prior knowledge about the reservoirs. Their validity was tested by comparing actual and simulated releases with each other. For the eleven reservoirs modelled, the normalised outflow, <0,1>, was predicted with a MSE of 0.002 to 0.044. The rules can be incorporated into GHMs. After a network for a specific reservoir has been trained, the inflow calculated by the hydrological model can be combined with the release and initial storage to calculate the storage for the next time-step using a mass balance. Subsequently, the release can be predicted one time-step ahead using the inflow and storage.

Event-related potentials reveal the relations between feature representations at different levels of abstraction.

PubMed

Hannah, Samuel D; Shedden, Judith M; Brooks, Lee R; Grundy, John G

2016-11-01

In this paper, we use behavioural methods and event-related potentials (ERPs) to explore the relations between informational and instantiated features, as well as the relation between feature abstraction and rule type. Participants are trained to categorize two species of fictitious animals and then identify perceptually novel exemplars. Critically, two groups are given a perfectly predictive counting rule that, according to Hannah and Brooks (2009. Featuring familiarity: How a familiar feature instantiation influences categorization. Canadian Journal of Experimental Psychology/Revue Canadienne de Psychologie Expérimentale, 63, 263-275. Retrieved from http://doi.org/10.1037/a0017919), should orient them to using abstract informational features when categorizing the novel transfer items. A third group is taught a feature list rule, which should orient them to using detailed instantiated features. One counting-rule group were taught their rule before any exposure to the actual stimuli, and the other immediately after training, having learned the instantiations first. The feature-list group were also taught their rule after training. The ERP results suggest that at test, the two counting-rule groups processed items differently, despite their identical rule. This not only supports the distinction that informational and instantiated features are qualitatively different feature representations, but also implies that rules can readily operate over concrete inputs, in contradiction to traditional approaches that assume that rules necessarily act on abstract inputs.

Fast Modeling of Binding Affinities by Means of Superposing Significant Interaction Rules (SSIR) Method

PubMed Central

Besalú, Emili

2016-01-01

The Superposing Significant Interaction Rules (SSIR) method is described. It is a general combinatorial and symbolic procedure able to rank compounds belonging to combinatorial analogue series. The procedure generates structure-activity relationship (SAR) models and also serves as an inverse SAR tool. The method is fast and can deal with large databases. SSIR operates from statistical significances calculated from the available library of compounds and according to the previously attached molecular labels of interest or non-interest. The required symbolic codification allows dealing with almost any combinatorial data set, even in a confidential manner, if desired. The application example categorizes molecules as binding or non-binding, and consensus ranking SAR models are generated from training and two distinct cross-validation methods: leave-one-out and balanced leave-two-out (BL2O), the latter being suited for the treatment of binary properties. PMID:27240346

14 CFR 135.335 - Approval of aircraft simulators and other training devices.

Code of Federal Regulations, 2010 CFR

2010-01-01

... OPERATIONS OPERATING REQUIREMENTS: COMMUTER AND ON DEMAND OPERATIONS AND RULES GOVERNING PERSONS ON BOARD... following requirements: (1) It must be specifically approved for— (i) The certificate holder; and (ii) The..., functional, and other character- istics that are required for approval. (3) Additionally, for aircraft...

30 CFR 48.6 - Experienced miner training.

Code of Federal Regulations, 2010 CFR

2010-07-01

.... (b) Experienced miners must complete the training prescribed in this section before beginning work... to work environment. The course shall include a visit and tour of the mine. The methods of mining... responsibilities of such supervisors and miners' representatives; and an introduction to the operator's rules and...

20 CFR 638.538 - Disciplinary procedures and appeals.

Code of Federal Regulations, 2010 CFR

2010-04-01

... Section 638.538 Employees' Benefits EMPLOYMENT AND TRAINING ADMINISTRATION, DEPARTMENT OF LABOR JOB CORPS PROGRAM UNDER TITLE IV-B OF THE JOB TRAINING PARTNERSHIP ACT Center Operations § 638.538 Disciplinary... behavior, in accordance with procedures developed by the Job Corps Director. Such rules shall be...

A Cognitive Architecture for Human Performance Process Model Research

DTIC Science & Technology

1992-11-01

individually defined, updatable world representation which is a description of the world as the operator knows it. It contains rules for decisions, an...operate it), and rules of engagement (knowledge about the operator’s expected behavior). The HPP model works in the following way. Information enters...based models depict the problem-solving processes of experts. The experts’ knowledge is represented in symbol structures, along with rules for

Deep learning based state recognition of substation switches

NASA Astrophysics Data System (ADS)

Wang, Jin

2018-06-01

Different from the traditional method which recognize the state of substation switches based on the running rules of electrical power system, this work proposes a novel convolutional neuron network-based state recognition approach of substation switches. Inspired by the theory of transfer learning, we first establish a convolutional neuron network model trained on the large-scale image set ILSVRC2012, then the restricted Boltzmann machine is employed to replace the full connected layer of the convolutional neuron network and trained on our small image dataset of 110kV substation switches to get a stronger model. Experiments conducted on our image dataset of 110kV substation switches show that, the proposed approach can be applicable to the substation to reduce the running cost and implement the real unattended operation.

The research of selection model based on LOD in multi-scale display of electronic map

NASA Astrophysics Data System (ADS)

Zhang, Jinming; You, Xiong; Liu, Yingzhen

2008-10-01

This paper proposes a selection model based on LOD to aid the display of electronic map. The ratio of display scale to map scale is regarded as a LOD operator. The categorization rule, classification rule, elementary rule and spatial geometry character rule of LOD operator setting are also concluded.

The neural representation of the gender of faces in the primate visual system: A computer modeling study.

PubMed

Minot, Thomas; Dury, Hannah L; Eguchi, Akihiro; Humphreys, Glyn W; Stringer, Simon M

2017-03-01

We use an established neural network model of the primate visual system to show how neurons might learn to encode the gender of faces. The model consists of a hierarchy of 4 competitive neuronal layers with associatively modifiable feedforward synaptic connections between successive layers. During training, the network was presented with many realistic images of male and female faces, during which the synaptic connections are modified using biologically plausible local associative learning rules. After training, we found that different subsets of output neurons have learned to respond exclusively to either male or female faces. With the inclusion of short range excitation within each neuronal layer to implement a self-organizing map architecture, neurons representing either male or female faces were clustered together in the output layer. This learning process is entirely unsupervised, as the gender of the face images is not explicitly labeled and provided to the network as a supervisory training signal. These simulations are extended to training the network on rotating faces. It is found that by using a trace learning rule incorporating a temporal memory trace of recent neuronal activity, neurons responding selectively to either male or female faces were also able to learn to respond invariantly over different views of the faces. This kind of trace learning has been previously shown to operate within the primate visual system by neurophysiological and psychophysical studies. The computer simulations described here predict that similar neurons encoding the gender of faces will be present within the primate visual system. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Atmospheric Downscaling using Genetic Programming

NASA Astrophysics Data System (ADS)

Zerenner, Tanja; Venema, Victor; Simmer, Clemens

2013-04-01

Coupling models for the different components of the Soil-Vegetation-Atmosphere-System requires up-and downscaling procedures. Subject of our work is the downscaling scheme used to derive high resolution forcing data for land-surface and subsurface models from coarser atmospheric model output. The current downscaling scheme [Schomburg et. al. 2010, 2012] combines a bi-quadratic spline interpolation, deterministic rules and autoregressive noise. For the development of the scheme, training and validation data sets have been created by carrying out high-resolution runs of the atmospheric model. The deterministic rules in this scheme are partly based on known physical relations and partly determined by an automated search for linear relationships between the high resolution fields of the atmospheric model output and high resolution data on surface characteristics. Up to now deterministic rules are available for downscaling surface pressure and partially, depending on the prevailing weather conditions, for near surface temperature and radiation. Aim of our work is to improve those rules and to find deterministic rules for the remaining variables, which require downscaling, e.g. precipitation or near surface specifc humidity. To accomplish that, we broaden the search by allowing for interdependencies between different atmospheric parameters, non-linear relations, non-local and time-lagged relations. To cope with the vast number of possible solutions, we use genetic programming, a method from machine learning, which is based on the principles of natural evolution. We are currently working with GPLAB, a Genetic Programming toolbox for Matlab. At first we have tested the GP system to retrieve the known physical rule for downscaling surface pressure, i.e. the hydrostatic equation, from our training data. We have found this to be a simple task to the GP system. Furthermore we have improved accuracy and efficiency of the GP solution by implementing constant variation and optimization as genetic operators. Next we have worked on an improvement of the downscaling rule for the two-meter-temperature. We have added an if-function with four input arguments to the function set. Since this has shown to increase bloat we have additionally modified our fitness function by including penalty terms for both the size of the solutions and the number intron nodes, i.e program parts that are never evaluated. Starting from the known downscaling rule for the two-meter temperature, which linearly exploits the orography anomalies allowed or disallowed by a certain temperature gradient, our GP system has been able to find an improvement. The rule produced by the GP clearly shows a better performance concerning the reproduced small-scale variability.

Assessing the operation rules of a reservoir system based on a detailed modelling-chain

NASA Astrophysics Data System (ADS)

Bruwier, M.; Erpicum, S.; Pirotton, M.; Archambeau, P.; Dewals, B.

2014-09-01

According to available climate change scenarios for Belgium, drier summers and wetter winters are expected. In this study, we focus on two muti-purpose reservoirs located in the Vesdre catchment, which is part of the Meuse basin. The current operation rules of the reservoirs are first analysed. Next, the impacts of two climate change scenarios are assessed and enhanced operation rules are proposed to mitigate these impacts. For this purpose, an integrated model of the catchment was used. It includes a hydrological model, one-dimensional and two-dimensional hydraulic models of the river and its main tributaries, a model of the reservoir system and a flood damage model. Five performance indicators of the reservoir system have been defined, reflecting its ability to provide sufficient drinking, to control floods, to produce hydropower and to reduce low-flow condition. As shown by the results, enhanced operation rules may improve the drinking water potential and the low-flow augmentation while the existing operation rules are efficient for flood control and for hydropower production.

Assessing the operation rules of a reservoir system based on a detailed modelling chain

NASA Astrophysics Data System (ADS)

Bruwier, M.; Erpicum, S.; Pirotton, M.; Archambeau, P.; Dewals, B. J.

2015-03-01

According to available climate change scenarios for Belgium, drier summers and wetter winters are expected. In this study, we focus on two multi-purpose reservoirs located in the Vesdre catchment, which is part of the Meuse basin. The current operation rules of the reservoirs are first analysed. Next, the impacts of two climate change scenarios are assessed and enhanced operation rules are proposed to mitigate these impacts. For this purpose, an integrated model of the catchment was used. It includes a hydrological model, one-dimensional and two-dimensional hydraulic models of the river and its main tributaries, a model of the reservoir system and a flood damage model. Five performance indicators of the reservoir system have been defined, reflecting its ability to provide sufficient drinking water, to control floods, to produce hydropower and to reduce low-flow conditions. As shown by the results, enhanced operation rules may improve the drinking water potential and the low-flow augmentation while the existing operation rules are efficient for flood control and for hydropower production.

14 CFR 135.331 - Crewmember emergency training.

Code of Federal Regulations, 2010 CFR

2010-01-01

... REQUIREMENTS: COMMUTER AND ON DEMAND OPERATIONS AND RULES GOVERNING PERSONS ON BOARD SUCH AIRCRAFT Training... of crew and passenger oxygen. (6) Removal of life rafts from the aircraft, inflation of the life rafts, use of life lines, and boarding of passengers and crew, if applicable. (7) Donning and inflation...

78 FR 16051 - Vehicle/Track Interaction Safety Standards; High-Speed and High Cant Deficiency Operations

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-13

...FRA is amending the Track Safety Standards and Passenger Equipment Safety Standards to promote the safe interaction of rail vehicles with the track over which they operate under a variety of conditions at speeds up to 220 m.p.h. The final rule revises standards for track geometry and safety limits for vehicle response to track conditions, enhances vehicle/track qualification procedures, and adds flexibility for permitting high cant deficiency train operations through curves at conventional speeds. The rule accounts for a range of vehicle types that are currently in operation, as well as vehicle types that may likely be used in future high-speed or high cant deficiency rail operations, or both. The rule is based on the results of simulation studies designed to identify track geometry irregularities associated with unsafe wheel/rail forces and accelerations, thorough reviews of vehicle qualification and revenue service test data, and consideration of international practices.

Predicting the threshold of pulse-train electrical stimuli using a stochastic auditory nerve model: the effects of stimulus noise.

PubMed

Xu, Yifang; Collins, Leslie M

2004-04-01

The incorporation of low levels of noise into an electrical stimulus has been shown to improve auditory thresholds in some human subjects (Zeng et al., 2000). In this paper, thresholds for noise-modulated pulse-train stimuli are predicted utilizing a stochastic neural-behavioral model of ensemble fiber responses to bi-phasic stimuli. The neural refractory effect is described using a Markov model for a noise-free pulse-train stimulus and a closed-form solution for the steady-state neural response is provided. For noise-modulated pulse-train stimuli, a recursive method using the conditional probability is utilized to track the neural responses to each successive pulse. A neural spike count rule has been presented for both threshold and intensity discrimination under the assumption that auditory perception occurs via integration over a relatively long time period (Bruce et al., 1999). An alternative approach originates from the hypothesis of the multilook model (Viemeister and Wakefield, 1991), which argues that auditory perception is based on several shorter time integrations and may suggest an NofM model for prediction of pulse-train threshold. This motivates analyzing the neural response to each individual pulse within a pulse train, which is considered to be the brief look. A logarithmic rule is hypothesized for pulse-train threshold. Predictions from the multilook model are shown to match trends in psychophysical data for noise-free stimuli that are not always matched by the long-time integration rule. Theoretical predictions indicate that threshold decreases as noise variance increases. Theoretical models of the neural response to pulse-train stimuli not only reduce calculational overhead but also facilitate utilization of signal detection theory and are easily extended to multichannel psychophysical tasks.

49 CFR 240.129 - Criteria for monitoring operational performance of certified engineers.

Code of Federal Regulations, 2010 CFR

2010-10-01

... railroad's rules and practices for the safe operation of locomotives and trains; (2) Be designed so that... service. (c) The procedures shall: (1) Be designed to determine that the person possesses and routinely... operational performance monitoring will be conducted; (3) Be designed so that the locomotive engineer is...

Linear discriminant analysis with misallocation in training samples

NASA Technical Reports Server (NTRS)

Chhikara, R. (Principal Investigator); Mckeon, J.

1982-01-01

Linear discriminant analysis for a two-class case is studied in the presence of misallocation in training samples. A general appraoch to modeling of mislocation is formulated, and the mean vectors and covariance matrices of the mixture distributions are derived. The asymptotic distribution of the discriminant boundary is obtained and the asymptotic first two moments of the two types of error rate given. Certain numerical results for the error rates are presented by considering the random and two non-random misallocation models. It is shown that when the allocation procedure for training samples is objectively formulated, the effect of misallocation on the error rates of the Bayes linear discriminant rule can almost be eliminated. If, however, this is not possible, the use of Fisher rule may be preferred over the Bayes rule.

MANPRINT Methods Monograph: Aiding the Development of Training Constraints

DTIC Science & Technology

1989-06-01

the performance of the trained soldiers who op# rate , maintain, and support their hardware and software. The Arm:. must assume that all trained operator...combined into the same system. Although HARDMAN experts who must also deal with composite systems have been faced with the same challenge, no attempt has...yet been made to predict composite system training based on an additive rule which considers characteristics implied by each subsystem. Instead, HARDMAN

UAV Trajectory Modeling Using Neural Networks

NASA Technical Reports Server (NTRS)

Xue, Min

2017-01-01

Large amount of small Unmanned Aerial Vehicles (sUAVs) are projected to operate in the near future. Potential sUAV applications include, but not limited to, search and rescue, inspection and surveillance, aerial photography and video, precision agriculture, and parcel delivery. sUAVs are expected to operate in the uncontrolled Class G airspace, which is at or below 500 feet above ground level (AGL), where many static and dynamic constraints exist, such as ground properties and terrains, restricted areas, various winds, manned helicopters, and conflict avoidance among sUAVs. How to enable safe, efficient, and massive sUAV operations at the low altitude airspace remains a great challenge. NASA's Unmanned aircraft system Traffic Management (UTM) research initiative works on establishing infrastructure and developing policies, requirement, and rules to enable safe and efficient sUAVs' operations. To achieve this goal, it is important to gain insights of future UTM traffic operations through simulations, where the accurate trajectory model plays an extremely important role. On the other hand, like what happens in current aviation development, trajectory modeling should also serve as the foundation for any advanced concepts and tools in UTM. Accurate models of sUAV dynamics and control systems are very important considering the requirement of the meter level precision in UTM operations. The vehicle dynamics are relatively easy to derive and model, however, vehicle control systems remain unknown as they are usually kept by manufactures as a part of intellectual properties. That brings challenges to trajectory modeling for sUAVs. How to model the vehicle's trajectories with unknown control system? This work proposes to use a neural network to model a vehicle's trajectory. The neural network is first trained to learn the vehicle's responses at numerous conditions. Once being fully trained, given current vehicle states, winds, and desired future trajectory, the neural network should be able to predict the vehicle's future states at next time step. A complete 4-D trajectory are then generated step by step using the trained neural network. Experiments in this work show that the neural network can approximate the sUAV's model and predict the trajectory accurately.

Learning abstract visual concepts via probabilistic program induction in a Language of Thought.

PubMed

Overlan, Matthew C; Jacobs, Robert A; Piantadosi, Steven T

2017-11-01

The ability to learn abstract concepts is a powerful component of human cognition. It has been argued that variable binding is the key element enabling this ability, but the computational aspects of variable binding remain poorly understood. Here, we address this shortcoming by formalizing the Hierarchical Language of Thought (HLOT) model of rule learning. Given a set of data items, the model uses Bayesian inference to infer a probability distribution over stochastic programs that implement variable binding. Because the model makes use of symbolic variables as well as Bayesian inference and programs with stochastic primitives, it combines many of the advantages of both symbolic and statistical approaches to cognitive modeling. To evaluate the model, we conducted an experiment in which human subjects viewed training items and then judged which test items belong to the same concept as the training items. We found that the HLOT model provides a close match to human generalization patterns, significantly outperforming two variants of the Generalized Context Model, one variant based on string similarity and the other based on visual similarity using features from a deep convolutional neural network. Additional results suggest that variable binding happens automatically, implying that binding operations do not add complexity to peoples' hypothesized rules. Overall, this work demonstrates that a cognitive model combining symbolic variables with Bayesian inference and stochastic program primitives provides a new perspective for understanding people's patterns of generalization. Copyright © 2017 Elsevier B.V. All rights reserved.

Retrosynthetic Reaction Prediction Using Neural Sequence-to-Sequence Models

PubMed Central

2017-01-01

We describe a fully data driven model that learns to perform a retrosynthetic reaction prediction task, which is treated as a sequence-to-sequence mapping problem. The end-to-end trained model has an encoder–decoder architecture that consists of two recurrent neural networks, which has previously shown great success in solving other sequence-to-sequence prediction tasks such as machine translation. The model is trained on 50,000 experimental reaction examples from the United States patent literature, which span 10 broad reaction types that are commonly used by medicinal chemists. We find that our model performs comparably with a rule-based expert system baseline model, and also overcomes certain limitations associated with rule-based expert systems and with any machine learning approach that contains a rule-based expert system component. Our model provides an important first step toward solving the challenging problem of computational retrosynthetic analysis. PMID:29104927

78 FR 3828 - Microloan Operating Loans

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-17

... DEPARTMENT OF AGRICULTURE Farm Service Agency 7 CFR Parts 761 and 764 RIN 0560-AI17 Microloan Operating Loans AGENCY: Farm Service Agency, USDA. ACTION: Final rule. SUMMARY: The Farm Service Agency (FSA... education, on-the-job training, or farming experience; have an acceptable credit history; and have adequate...

14 CFR 91.1101 - Pilots: Initial, transition, and upgrade ground training.

Code of Federal Regulations, 2014 CFR

2014-01-01

... consumption and cruise control; (9) Flight planning; (10) Each normal and emergency procedure; and (11) The..., DEPARTMENT OF TRANSPORTATION (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT... manager's flight locating procedures; (2) Principles and methods for determining weight and balance, and...

14 CFR 91.1101 - Pilots: Initial, transition, and upgrade ground training.

Code of Federal Regulations, 2013 CFR

2013-01-01

... consumption and cruise control; (9) Flight planning; (10) Each normal and emergency procedure; and (11) The..., DEPARTMENT OF TRANSPORTATION (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT... manager's flight locating procedures; (2) Principles and methods for determining weight and balance, and...

14 CFR 91.1101 - Pilots: Initial, transition, and upgrade ground training.

Code of Federal Regulations, 2012 CFR

2012-01-01

... consumption and cruise control; (9) Flight planning; (10) Each normal and emergency procedure; and (11) The..., DEPARTMENT OF TRANSPORTATION (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT... manager's flight locating procedures; (2) Principles and methods for determining weight and balance, and...

77 FR 60376 - Sunshine Act Notice

Federal Register 2010, 2011, 2012, 2013, 2014

2012-10-03

... Implications of Eminent Domain Abuse briefing Update on the Sex Trafficking: A Gender-Based Violation of Civil... III. Management and Operations Chief of Regional Programs' report OGC Training: Ethics Rules Relating...

49 CFR 232.109 - Dynamic brake requirements.

Code of Federal Regulations, 2010 CFR

2010-10-01

... system that includes dynamic brakes shall adopt and comply with written operating rules governing safe... verifiable data and research. (k) A railroad operating a train with a brake system that includes dynamic... 49 Transportation 4 2010-10-01 2010-10-01 false Dynamic brake requirements. 232.109 Section 232...

49 CFR 218.37 - Flag protection.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 4 2010-10-01 2010-10-01 false Flag protection. 218.37 Section 218.37..., DEPARTMENT OF TRANSPORTATION RAILROAD OPERATING PRACTICES Protection of Trains and Locomotives § 218.37 Flag protection. (a) After August 1, 1977, each railroad must have in effect an operating rule which complies with...

Advancing reservoir operation description in physically based hydrological models

NASA Astrophysics Data System (ADS)

Anghileri, Daniela; Giudici, Federico; Castelletti, Andrea; Burlando, Paolo

2016-04-01

Last decades have seen significant advances in our capacity of characterizing and reproducing hydrological processes within physically based models. Yet, when the human component is considered (e.g. reservoirs, water distribution systems), the associated decisions are generally modeled with very simplistic rules, which might underperform in reproducing the actual operators' behaviour on a daily or sub-daily basis. For example, reservoir operations are usually described by a target-level rule curve, which represents the level that the reservoir should track during normal operating conditions. The associated release decision is determined by the current state of the reservoir relative to the rule curve. This modeling approach can reasonably reproduce the seasonal water volume shift due to reservoir operation. Still, it cannot capture more complex decision making processes in response, e.g., to the fluctuations of energy prices and demands, the temporal unavailability of power plants or varying amount of snow accumulated in the basin. In this work, we link a physically explicit hydrological model with detailed hydropower behavioural models describing the decision making process by the dam operator. In particular, we consider two categories of behavioural models: explicit or rule-based behavioural models, where reservoir operating rules are empirically inferred from observational data, and implicit or optimization based behavioural models, where, following a normative economic approach, the decision maker is represented as a rational agent maximising a utility function. We compare these two alternate modelling approaches on the real-world water system of Lake Como catchment in the Italian Alps. The water system is characterized by the presence of 18 artificial hydropower reservoirs generating almost 13% of the Italian hydropower production. Results show to which extent the hydrological regime in the catchment is affected by different behavioural models and reservoir operating strategies.

Multicentre external validation of IOTA prediction models and RMI by operators with varied training

PubMed Central

Sayasneh, A; Wynants, L; Preisler, J; Kaijser, J; Johnson, S; Stalder, C; Husicka, R; Abdallah, Y; Raslan, F; Drought, A; Smith, A A; Ghaem-Maghami, S; Epstein, E; Van Calster, B; Timmerman, D; Bourne, T

2013-01-01

Background: Correct characterisation of ovarian tumours is critical to optimise patient care. The purpose of this study is to evaluate the diagnostic performance of the International Ovarian Tumour Analysis (IOTA) logistic regression model (LR2), ultrasound Simple Rules (SR), the Risk of Malignancy Index (RMI) and subjective assessment (SA) for preoperative characterisation of adnexal masses, when ultrasonography is performed by examiners with different background training and experience. Methods: A 2-year prospective multicentre cross-sectional study. Thirty-five level II ultrasound examiners contributed in three UK hospitals. Transvaginal ultrasonography was performed using a standardised approach. The final outcome was the surgical findings and histological diagnosis. To characterise the adnexal masses, the six-variable prediction model (LR2) with a cutoff of 0.1, the RMI with cutoff of 200, ten SR (five rules for malignancy and five rules for benignity) and SA were applied. The area under the curves (AUCs) for performance of LR2 and RMI were calculated. Diagnostic performance measures for all models assessed were sensitivity, specificity, positive and negative likelihood ratios (LR+ and LR−), and the diagnostic odds ratio (DOR). Results: Nine-hundred and sixty-two women with adnexal masses underwent transvaginal ultrasonography, whereas 255 had surgery. Prevalence of malignancy was 29% (49 primary invasive epithelial ovarian cancers, 18 borderline ovarian tumours, and 7 metastatic tumours). The AUCs for LR2 and RMI for all masses were 0.94 (95% confidence interval (CI): 0.89–0.97) and 0.90 (95% CI: 0.83–0.94), respectively. In premenopausal women, LR2−RMI difference was 0.09 (95% CI: 0.03–0.15) compared with −0.02 (95% CI: −0.08 to 0.04) in postmenopausal women. For all masses, the DORs for LR2, RMI, SR+SA (using SA when SR inapplicable), SR+MA (assuming malignancy when SR inapplicable), and SA were 62 (95% CI: 27–142), 43 (95% CI: 19–97), 109 (95% CI: 44–274), 66 (95% CI: 27–158), and 70 (95% CI: 30–163), respectively. Conclusion: Overall, the test performance of IOTA prediction models and rules as well as the RMI was maintained in examiners with varying levels of training and experience. PMID:23674083

Selection of appropriate training and validation set chemicals for modelling dermal permeability by U-optimal design.

PubMed

Xu, G; Hughes-Oliver, J M; Brooks, J D; Yeatts, J L; Baynes, R E

2013-01-01

Quantitative structure-activity relationship (QSAR) models are being used increasingly in skin permeation studies. The main idea of QSAR modelling is to quantify the relationship between biological activities and chemical properties, and thus to predict the activity of chemical solutes. As a key step, the selection of a representative and structurally diverse training set is critical to the prediction power of a QSAR model. Early QSAR models selected training sets in a subjective way and solutes in the training set were relatively homogenous. More recently, statistical methods such as D-optimal design or space-filling design have been applied but such methods are not always ideal. This paper describes a comprehensive procedure to select training sets from a large candidate set of 4534 solutes. A newly proposed 'Baynes' rule', which is a modification of Lipinski's 'rule of five', was used to screen out solutes that were not qualified for the study. U-optimality was used as the selection criterion. A principal component analysis showed that the selected training set was representative of the chemical space. Gas chromatograph amenability was verified. A model built using the training set was shown to have greater predictive power than a model built using a previous dataset [1].

Intelligent control for modeling of real-time reservoir operation, part II: artificial neural network with operating rule curves

NASA Astrophysics Data System (ADS)

Chang, Ya-Ting; Chang, Li-Chiu; Chang, Fi-John

2005-04-01

To bridge the gap between academic research and actual operation, we propose an intelligent control system for reservoir operation. The methodology includes two major processes, the knowledge acquired and implemented, and the inference system. In this study, a genetic algorithm (GA) and a fuzzy rule base (FRB) are used to extract knowledge based on the historical inflow data with a design objective function and on the operating rule curves respectively. The adaptive network-based fuzzy inference system (ANFIS) is then used to implement the knowledge, to create the fuzzy inference system, and then to estimate the optimal reservoir operation. To investigate its applicability and practicability, the Shihmen reservoir, Taiwan, is used as a case study. For the purpose of comparison, a simulation of the currently used M-5 operating rule curve is also performed. The results demonstrate that (1) the GA is an efficient way to search the optimal input-output patterns, (2) the FRB can extract the knowledge from the operating rule curves, and (3) the ANFIS models built on different types of knowledge can produce much better performance than the traditional M-5 curves in real-time reservoir operation. Moreover, we show that the model can be more intelligent for reservoir operation if more information (or knowledge) is involved.

Derivation of optimal joint operating rules for multi-purpose multi-reservoir water-supply system

NASA Astrophysics Data System (ADS)

Tan, Qiao-feng; Wang, Xu; Wang, Hao; Wang, Chao; Lei, Xiao-hui; Xiong, Yi-song; Zhang, Wei

2017-08-01

The derivation of joint operating policy is a challenging task for a multi-purpose multi-reservoir system. This study proposed an aggregation-decomposition model to guide the joint operation of multi-purpose multi-reservoir system, including: (1) an aggregated model based on the improved hedging rule to ensure the long-term water-supply operating benefit; (2) a decomposed model to allocate the limited release to individual reservoirs for the purpose of maximizing the total profit of the facing period; and (3) a double-layer simulation-based optimization model to obtain the optimal time-varying hedging rules using the non-dominated sorting genetic algorithm II, whose objectives were to minimize maximum water deficit and maximize water supply reliability. The water-supply system of Li River in Guangxi Province, China, was selected for the case study. The results show that the operating policy proposed in this study is better than conventional operating rules and aggregated standard operating policy for both water supply and hydropower generation due to the use of hedging mechanism and effective coordination among multiple objectives.

Training and Operations Integrated Calendar Scheduler - TROPICS

DOE Office of Scientific and Technical Information (OSTI.GOV)

J.E. Oppenlander; A.J. Levy; V.A. Arbige

2003-01-27

TROPICS is a rule-based scheduling system that optimizes the training experience for students in a power (note this change should be everywhere, i.e. Not reactor) plant environment. The problem is complicated by the condition that plant resources and users' time must be simultaneously scheduled to make best use of both. The training facility is highly constrained in how it is used, and, as in many similar environments, subject to dynamic change with little or no advance notice. The flexibility required extends to changes resulting from students' actions such as absences. Even though the problem is highly constrained by plant usagemore » and student objectives, the large number of possible schedules is a concern. TROPICS employs a control strategy for rule firing to prune the possibility tree and avoid combinatorial explosion. The application has been in use since 1996, first as a prototype for testing and then in production. Training Coordinators have a philosophical aspect to teaching students that has made the rule-based approach much more verifiable and satisfying to the domain experts than other forms of capturing expertise.« less

Building v/s Exploring Models: Comparing Learning of Evolutionary Processes through Agent-based Modeling

NASA Astrophysics Data System (ADS)

Wagh, Aditi

Two strands of work motivate the three studies in this dissertation. Evolutionary change can be viewed as a computational complex system in which a small set of rules operating at the individual level result in different population level outcomes under different conditions. Extensive research has documented students' difficulties with learning about evolutionary change (Rosengren et al., 2012), particularly in terms of levels slippage (Wilensky & Resnick, 1999). Second, though building and using computational models is becoming increasingly common in K-12 science education, we know little about how these two modalities compare. This dissertation adopts agent-based modeling as a representational system to compare these modalities in the conceptual context of micro-evolutionary processes. Drawing on interviews, Study 1 examines middle-school students' productive ways of reasoning about micro-evolutionary processes to find that the specific framing of traits plays a key role in whether slippage explanations are cued. Study 2, which was conducted in 2 schools with about 150 students, forms the crux of the dissertation. It compares learning processes and outcomes when students build their own models or explore a pre-built model. Analysis of Camtasia videos of student pairs reveals that builders' and explorers' ways of accessing rules, and sense-making of observed trends are of a different character. Builders notice rules through available blocks-based primitives, often bypassing their enactment while explorers attend to rules primarily through the enactment. Moreover, builders' sense-making of observed trends is more rule-driven while explorers' is more enactment-driven. Pre and posttests reveal that builders manifest a greater facility with accessing rules, providing explanations manifesting targeted assembly. Explorers use rules to construct explanations manifesting non-targeted assembly. Interviews reveal varying degrees of shifts away from slippage in both modalities, with students who built models not incorporating slippage explanations in responses. Study 3 compares these modalities with a control using traditional activities. Pre and posttests reveal that the two modalities manifested greater facility with accessing and assembling rules than the control. The dissertation offers implications for the design of learning environments for evolutionary change, design of the two modalities based on their strengths and weaknesses, and teacher training for the same.

Win-stay and win-shift lever-press strategies in an appetitively reinforced task for rats.

PubMed

Reed, Phil

2016-12-01

Two experiments examined acquisition of win-stay, win-shift, lose-stay, and lose-shift rules by which hungry rats could earn food reinforcement. In Experiment 1, two groups of rats were trained in a two-lever operant task that required them to follow either a win-stay/lose-shift or a win-shift/lose-stay contingency. The rates of acquisition of the individual rules within each contingency differed: lose-shift and lose-stay rules were acquired faster than win-stay and win-shift rules. Contrary to a number of previous reports, the win-shift rule was acquired less rapidly than any of the other rules. In Experiment 2, the four rules were taught separately, but subjects still acquired the win-shift rule more slowly than any of the other rules.

System diagnostic builder

NASA Technical Reports Server (NTRS)

Nieten, Joseph L.; Burke, Roger

1992-01-01

The System Diagnostic Builder (SDB) is an automated software verification and validation tool using state-of-the-art Artificial Intelligence (AI) technologies. The SDB is used extensively by project BURKE at NASA-JSC as one component of a software re-engineering toolkit. The SDB is applicable to any government or commercial organization which performs verification and validation tasks. The SDB has an X-window interface, which allows the user to 'train' a set of rules for use in a rule-based evaluator. The interface has a window that allows the user to plot up to five data parameters (attributes) at a time. Using these plots and a mouse, the user can identify and classify a particular behavior of the subject software. Once the user has identified the general behavior patterns of the software, he can train a set of rules to represent his knowledge of that behavior. The training process builds rules and fuzzy sets to use in the evaluator. The fuzzy sets classify those data points not clearly identified as a particular classification. Once an initial set of rules is trained, each additional data set given to the SDB will be used by a machine learning mechanism to refine the rules and fuzzy sets. This is a passive process and, therefore, it does not require any additional operator time. The evaluation component of the SDB can be used to validate a single software system using some number of different data sets, such as a simulator. Moreover, it can be used to validate software systems which have been re-engineered from one language and design methodology to a totally new implementation.

Revisiting the rotating call schedule in less than 80 hours per week.

PubMed

Roses, Robert E; Foley, Paul J; Paulson, Emily C; Pray, Lori; Kelz, Rachel R; Williams, Noel N; Morris, Jon B

2009-01-01

The Accreditation Council for Graduate Medical Education (ACGME) work-hour restrictions have prompted many surgical training programs to adopt a night-float resident coverage system (NF). Dissatisfaction with NF prompted us to transition to a rotating junior resident call model (Q4) with 24-hour call shifts at the outset of the 2007-2008 academic year. We performed a prospective study to determine the influence of this transition on resident education, morale, and quality of life, as well as on ACGME work rule compliance and American Board of Surgery In-Training Examination (ABSITE) scores. Residents were surveyed after 1 year of NF and again 1 year after the introduction of Q4. Responses to a series of statements about the influence of the call model (NF or Q4) on educational opportunities and morale were solicited. The survey used a 5-point Likert response scale (1 = complete disagreement to 5 = complete agreement). Median values of participant responses were calculated and compared using the Wilcoxon rank-sum test. Compliance with ACGME work rules, ABSITE scores, and operative case logs from the 2006-2007 and 2007-2008 academic years were also compared. Residents were significantly more enthusiastic about Q4 compared with NF, particularly when asked about the influence these systems had on morale (median response = 4.0 [Q4] compared with 2.0 [NF]; p = 0.001) and engagement of residents by the teaching faculty (median response = 4.0 [Q4] compared with 1.0 [NF]; p = 0.001). Case logs revealed a similar operative experience for first-year residents irrespective of the call schedule (p = 0.51). Excellent compliance with ACGME work rules was maintained as reflected by the percentage of monthly 80-hour violations per resident months worked (3% [Q4] compared with 0.7% [NF]). No difference was observed in the ABSITE scores of first-year residents (a mean percentile point increase of 1 was found after the introduction of Q4). Educational opportunities, compliance with ACGME work rules, and ABSITE scores can be preserved despite a transition from NF to Q4. Residents greatly prefer a rotating call schedule.

Autonomous Flight Rules - A Concept for Self-Separation in U.S. Domestic Airspace

NASA Technical Reports Server (NTRS)

Wing, David J.; Cotton, William B.

2011-01-01

Autonomous Flight Rules (AFR) are proposed as a new set of operating regulations in which aircraft navigate on tracks of their choice while self-separating from traffic and weather. AFR would exist alongside Instrument and Visual Flight Rules (IFR and VFR) as one of three available flight options for any appropriately trained and qualified operator with the necessary certified equipment. Historically, ground-based separation services evolved by necessity as aircraft began operating in the clouds and were unable to see each other. Today, technologies for global navigation, airborne surveillance, and onboard computing enable the functions of traffic conflict management to be fully integrated with navigation procedures onboard the aircraft. By self-separating, aircraft can operate with more flexibility and fewer restrictions than are required when using ground-based separation. The AFR concept is described in detail and provides practical means by which self-separating aircraft could share the same airspace as IFR and VFR aircraft without disrupting the ongoing processes of Air Traffic Control.

A Study of the Optimal Planning Model for Reservoir Sustainable Management- A Case Study of Shihmen Reservoir

NASA Astrophysics Data System (ADS)

Chen, Y. Y.; Ho, C. C.; Chang, L. C.

2017-12-01

The reservoir management in Taiwan faces lots of challenge. Massive sediment caused by landslide were flushed into reservoir, which will decrease capacity, rise the turbidity, and increase supply risk. Sediment usually accompanies nutrition that will cause eutrophication problem. Moreover, the unevenly distribution of rainfall cause water supply instability. Hence, how to ensure sustainable use of reservoirs has become an important task in reservoir management. The purpose of the study is developing an optimal planning model for reservoir sustainable management to find out an optimal operation rules of reservoir flood control and sediment sluicing. The model applies Genetic Algorithms to combine with the artificial neural network of hydraulic analysis and reservoir sediment movement. The main objective of operation rules in this study is to prevent reservoir outflow caused downstream overflow, minimum the gap between initial and last water level of reservoir, and maximum sluicing sediment efficiency. A case of Shihmen reservoir was used to explore the different between optimal operating rule and the current operation of the reservoir. The results indicate optimal operating rules tended to open desilting tunnel early and extend open duration during flood discharge period. The results also show the sluicing sediment efficiency of optimal operating rule is 36%, 44%, 54% during Typhoon Jangmi, Typhoon Fung-Wong, and Typhoon Sinlaku respectively. The results demonstrate the optimal operation rules do play a role in extending the service life of Shihmen reservoir and protecting the safety of downstream. The study introduces a low cost strategy, alteration of operation reservoir rules, into reservoir sustainable management instead of pump dredger in order to improve the problem of elimination of reservoir sediment and high cost.

Tele-transmission of EEG recordings.

PubMed

Lemesle, M; Kubis, N; Sauleau, P; N'Guyen The Tich, S; Touzery-de Villepin, A

2015-03-01

EEG recordings can be sent for remote interpretation. This article aims to define the tele-EEG procedures and technical guidelines. Tele-EEG is a complete medical act that needs to be carried out with the same quality requirements as a local one in terms of indications, formulation of the medical request and medical interpretation. It adheres to the same quality requirements for its human resources and materials. It must be part of a medical organization (technical and medical network) and follow all rules and guidelines of good medical practices. The financial model of this organization must include costs related to performing the EEG recording, operating and maintenance of the tele-EEG network and medical fees of the physician interpreting the EEG recording. Implementing this organization must be detailed in a convention between all parties involved: physicians, management of the healthcare structure, and the company providing the tele-EEG service. This convention will set rules for network operation and finance, and also the continuous training of all staff members. The tele-EEG system must respect all rules for safety and confidentiality, and ensure the traceability and storing of all requests and reports. Under these conditions, tele-EEG can optimize the use of human resources and competencies in its zone of utilization and enhance the organization of care management. Copyright © 2015. Published by Elsevier SAS.

On the effects of adaptive reservoir operating rules in hydrological physically-based models

NASA Astrophysics Data System (ADS)

Giudici, Federico; Anghileri, Daniela; Castelletti, Andrea; Burlando, Paolo

2017-04-01

Recent years have seen a significant increase of the human influence on the natural systems both at the global and local scale. Accurately modeling the human component and its interaction with the natural environment is key to characterize the real system dynamics and anticipate future potential changes to the hydrological regimes. Modern distributed, physically-based hydrological models are able to describe hydrological processes with high level of detail and high spatiotemporal resolution. Yet, they lack in sophistication for the behavior component and human decisions are usually described by very simplistic rules, which might underperform in reproducing the catchment dynamics. In the case of water reservoir operators, these simplistic rules usually consist of target-level rule curves, which represent the average historical level trajectory. Whilst these rules can reasonably reproduce the average seasonal water volume shifts due to the reservoirs' operation, they cannot properly represent peculiar conditions, which influence the actual reservoirs' operation, e.g., variations in energy price or water demand, dry or wet meteorological conditions. Moreover, target-level rule curves are not suitable to explore the water system response to climate and socio economic changing contexts, because they assume a business-as-usual operation. In this work, we quantitatively assess how the inclusion of adaptive reservoirs' operating rules into physically-based hydrological models contribute to the proper representation of the hydrological regime at the catchment scale. In particular, we contrast target-level rule curves and detailed optimization-based behavioral models. We, first, perform the comparison on past observational records, showing that target-level rule curves underperform in representing the hydrological regime over multiple time scales (e.g., weekly, seasonal, inter-annual). Then, we compare how future hydrological changes are affected by the two modeling approaches by considering different future scenarios comprising climate change projections of precipitation and temperature and projections of electricity prices. We perform this comparative assessment on the real-world water system of Lake Como catchment in the Italian Alps, which is characterized by the massive presence of artificial hydropower reservoirs heavily altering the natural hydrological regime. The results show how different behavioral model approaches affect the system representation in terms of hydropower performance, reservoirs dynamics and hydrological regime under different future scenarios.

An optimal sample data usage strategy to minimize overfitting and underfitting effects in regression tree models based on remotely-sensed data

USGS Publications Warehouse

Gu, Yingxin; Wylie, Bruce K.; Boyte, Stephen; Picotte, Joshua J.; Howard, Danny; Smith, Kelcy; Nelson, Kurtis

2016-01-01

Regression tree models have been widely used for remote sensing-based ecosystem mapping. Improper use of the sample data (model training and testing data) may cause overfitting and underfitting effects in the model. The goal of this study is to develop an optimal sampling data usage strategy for any dataset and identify an appropriate number of rules in the regression tree model that will improve its accuracy and robustness. Landsat 8 data and Moderate-Resolution Imaging Spectroradiometer-scaled Normalized Difference Vegetation Index (NDVI) were used to develop regression tree models. A Python procedure was designed to generate random replications of model parameter options across a range of model development data sizes and rule number constraints. The mean absolute difference (MAD) between the predicted and actual NDVI (scaled NDVI, value from 0–200) and its variability across the different randomized replications were calculated to assess the accuracy and stability of the models. In our case study, a six-rule regression tree model developed from 80% of the sample data had the lowest MAD (MADtraining = 2.5 and MADtesting = 2.4), which was suggested as the optimal model. This study demonstrates how the training data and rule number selections impact model accuracy and provides important guidance for future remote-sensing-based ecosystem modeling.

An intelligent training system for space shuttle flight controllers

NASA Technical Reports Server (NTRS)

Loftin, R. Bowen; Wang, Lui; Baffes, Paul; Hua, Grace

1988-01-01

An autonomous intelligent training system which integrates expert system technology with training/teaching methodologies is described. The system was designed to train Mission Control Center (MCC) Flight Dynamics Officers (FDOs) to deploy a certain type of satellite from the Space Shuttle. The Payload-assist module Deploys/Intelligent Computer-Aided Training (PD/ICAT) system consists of five components: a user interface, a domain expert, a training session manager, a trainee model, and a training scenario generator. The interface provides the trainee with information of the characteristics of the current training session and with on-line help. The domain expert (DeplEx for Deploy Expert) contains the rules and procedural knowledge needed by the FDO to carry out the satellite deploy. The DeplEx also contains mal-rules which permit the identification and diagnosis of common errors made by the trainee. The training session manager (TSM) examines the actions of the trainee and compares them with the actions of DeplEx in order to determine appropriate responses. A trainee model is developed for each individual using the system. The model includes a history of the trainee's interactions with the training system and provides evaluative data on the trainee's current skill level. A training scenario generator (TSG) designs appropriate training exercises for each trainee based on the trainee model and the training goals. All of the expert system components of PD/ICAT communicate via a common blackboard. The PD/ICAT is currently being tested. Ultimately, this project will serve as a vehicle for developing a general architecture for intelligent training systems together with a software environment for creating such systems.

An intelligent training system for space shuttle flight controllers

NASA Technical Reports Server (NTRS)

Loftin, R. Bowen; Wang, Lui; Baffles, Paul; Hua, Grace

1988-01-01

An autonomous intelligent training system which integrates expert system technology with training/teaching methodologies is described. The system was designed to train Mission Control Center (MCC) Flight Dynamics Officers (FDOs) to deploy a certain type of satellite from the Space Shuttle. The Payload-assist module Deploys/Intelligent Computer-Aided Training (PD/ICAT) system consists of five components: a user interface, a domain expert, a training session manager, a trainee model, and a training scenario generator. The interface provides the trainee with information of the characteristics of the current training session and with on-line help. The domain expert (Dep1Ex for Deploy Expert) contains the rules and procedural knowledge needed by the FDO to carry out the satellite deploy. The Dep1Ex also contains mal-rules which permit the identification and diagnosis of common errors made by the trainee. The training session manager (TSM) examines the actions of the trainee and compares them with the actions of Dep1Ex in order to determine appropriate responses. A trainee model is developed for each individual using the system. The model includes a history of the trainee's interactions with the training system and provides evaluative data on the trainee's current skill level. A training scenario generator (TSG) designs appropriate training exercises for each trainee based on the trainee model and the training goals. All of the expert system components of PD/ICAT communicate via a common blackboard. The PD/ICAT is currently being tested. Ultimately, this project will serve as a vehicle for developing a general architecture for intelligent training systems together with a software environment for creating such systems.

Bug Distribution and Pattern Classification.

ERIC Educational Resources Information Center

Tatsuoka, Kikumi K.; Tatsuoka, Maurice M.

The study examines the rule space model, a probabilistic model capable of measuring cognitive skill acquisition and of diagnosing erroneous rules of operation in a procedural domain. The model involves two important components: (1) determination of a set of bug distributions (bug density functions representing clusters around the rules); and (2)…

76 FR 36864 - Special Conditions: Gulfstream Model GVI Airplane; Operation Without Normal Electric Power

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-23

... DEPARTMENT OF TRANSPORTATION Federal Aviation Administration 14 CFR Part 25 [Docket No. NM444; Special Conditions No. 25-435-SC] Special Conditions: Gulfstream Model GVI Airplane; Operation Without... rules (VFR) conditions for at least five minutes after loss of all normal electrical power. This rule...

49 CFR 236.2 - Grounds.

Code of Federal Regulations, 2010 CFR

2010-10-01

..., single-break, signal control circuits using a grounded common, and alternating current power distribution... TRANSPORTATION RULES, STANDARDS, AND INSTRUCTIONS GOVERNING THE INSTALLATION, INSPECTION, MAINTENANCE, AND REPAIR... General § 236.2 Grounds. Each circuit, the functioning of which affects the safety of train operations...

Hybrid modeling of nitrate fate in large catchments using fuzzy-rules

NASA Astrophysics Data System (ADS)

van der Heijden, Sven; Haberlandt, Uwe

2010-05-01

Especially for nutrient balance simulations, physically based ecohydrological modeling needs an abundance of measured data and model parameters, which for large catchments all too often are not available in sufficient spatial or temporal resolution or are simply unknown. For efficient large-scale studies it is thus beneficial to have methods at one's disposal which are parsimonious concerning the number of model parameters and the necessary input data. One such method is fuzzy-rule based modeling, which compared to other machine-learning techniques has the advantages to produce models (the fuzzy-rules) which are physically interpretable to a certain extent, and to allow the explicit introduction of expert knowledge through pre-defined rules. The study focuses on the application of fuzzy-rule based modeling for nitrate simulation in large catchments, in particular concerning decision support. Fuzzy-rule based modeling enables the generation of simple, efficient, easily understandable models with nevertheless satisfactory accuracy for problems of decision support. The chosen approach encompasses a hybrid metamodeling, which includes the generation of fuzzy-rules with data originating from physically based models as well as a coupling with a physically based water balance model. For the generation of the needed training data and also as coupled water balance model the ecohydrological model SWAT is employed. The conceptual model divides the nitrate pathway into three parts. The first fuzzy-module calculates nitrate leaching with the percolating water from soil surface to groundwater, the second module simulates groundwater passage, and the final module replaces the in-stream processes. The aim of this modularization is to create flexibility for using each of the modules on its own, for changing or completely replacing it. For fuzzy-rule based modeling this can explicitly mean that the re-training of one of the modules with newly available data will be possible without problem, while the module assembly does not have to be modified. Apart from the concept of hybrid metamodeling first results are presented for the fuzzy-module for nitrate passage through the unsaturated zone.

A rule-based, dose-finding design for use in stroke rehabilitation research: methodological development.

PubMed

Colucci, E; Clark, A; Lang, C E; Pomeroy, V M

2017-12-01

Dose-optimisation studies as precursors to clinical trials are rare in stroke rehabilitation. To develop a rule-based, dose-finding design for stroke rehabilitation research. 3+3 rule-based, dose-finding study. Dose escalation/de-escalation was undertaken according to preset rules and a mathematical sequence (modified Fibonacci sequence). The target starting daily dose was 50 repetitions for the first cohort. Adherence was recorded by an electronic counter. At the end of the 2-week training period, the adherence record indicated dose tolerability (adherence to target dose) and the outcome measure indicated dose benefit (10% increase in motor function). The preset increment/decrease and checking rules were then applied to set the dose for the subsequent cohort. The process was repeated until preset stopping rules were met. Participants had a mean age of 68 (range 48 to 81) years, and were a mean of 70 (range 9 to 289) months post stroke with moderate upper limb paresis. A custom-built model of exercise-based training to enhance ability to open the paretic hand. Repetitions per minute of extension/flexion of paretic digits against resistance. Usability of the preset rules and whether the maximally tolerated dose was identifiable. Five cohorts of three participants were involved. Discernibly different doses were set for each subsequent cohort (i.e. 50, 100, 167, 251 and 209 repetitions/day). The maximally tolerated dose for the model training task was 209 repetitions/day. This dose-finding design is a feasible method for use in stroke rehabilitation research. Copyright © 2017 Chartered Society of Physiotherapy. All rights reserved.

System and method for embedding emotion in logic systems

NASA Technical Reports Server (NTRS)

Curtis, Steven A. (Inventor)

2012-01-01

A system, method, and computer readable-media for creating a stable synthetic neural system. The method includes training an intellectual choice-driven synthetic neural system (SNS), training an emotional rule-driven SNS by generating emotions from rules, incorporating the rule-driven SNS into the choice-driven SNS through an evolvable interface, and balancing the emotional SNS and the intellectual SNS to achieve stability in a nontrivial autonomous environment with a Stability Algorithm for Neural Entities (SANE). Generating emotions from rules can include coding the rules into the rule-driven SNS in a self-consistent way. Training the emotional rule-driven SNS can occur during a training stage in parallel with training the choice-driven SNS. The training stage can include a self assessment loop which measures performance characteristics of the rule-driven SNS against core genetic code. The method uses a stability threshold to measure stability of the incorporated rule-driven SNS and choice-driven SNS using SANE.

Summary of the Italian inter-society recommendations for radiation protection optimization in interventional radiology.

PubMed

Compagnone, Gaetano; Padovani, Renato; D'Avanzo, Maria Antonietta; Grande, Sveva; Campanella, Francesco; Rosi, Antonella

2018-05-01

A Working Group coordinated by the Italian National Institute of Health (Istituto Superiore di Sanità) and the National Workers Compensation Authority (Istituto Nazionale per l'Assicurazione contro gli Infortuni sul Lavoro, INAIL) and consisting of 11 Italian scientific/professional societies involved in the fluoroscopically guided interventional practices has been established to define recommendations for the optimization of patients and staff radiation protection in interventional radiology. A summary of these recommendations is here reported. A multidisciplinary approach was used to establish the Working Group by involving radiologists, interventional radiologists, neuroradiologists, interventional cardiologists, occupational health specialists, medical physicists, radiation protection experts, radiographers and nurses. The Group operated as a "Consensus Conference". Three main topics have been addressed: patient radiation protection (summarized in ten "golden rules"); staff radiation protection (summarized in ten "golden rules"); and education/training of interventional radiology professionals. In the "golden rules", practical and operational recommendations were provided to help the professionals in optimizing dose delivered to patients and reducing their own exposure. Operative indications dealt also with continuing education and training, and recommendations on professional accreditation and certification. The "Consensus Conference" was the methodology adopted for the development of these recommendations. Involvement of all professionals is a winning approach to improve practical implementation of the recommendations, thus getting a real impact on the optimization of the interventional radiology practices.

Deduction of reservoir operating rules for application in global hydrological models

NASA Astrophysics Data System (ADS)

Coerver, Hubertus M.; Rutten, Martine M.; van de Giesen, Nick C.

2018-01-01

A big challenge in constructing global hydrological models is the inclusion of anthropogenic impacts on the water cycle, such as caused by dams. Dam operators make decisions based on experience and often uncertain information. In this study information generally available to dam operators, like inflow into the reservoir and storage levels, was used to derive fuzzy rules describing the way a reservoir is operated. Using an artificial neural network capable of mimicking fuzzy logic, called the ANFIS adaptive-network-based fuzzy inference system, fuzzy rules linking inflow and storage with reservoir release were determined for 11 reservoirs in central Asia, the US and Vietnam. By varying the input variables of the neural network, different configurations of fuzzy rules were created and tested. It was found that the release from relatively large reservoirs was significantly dependent on information concerning recent storage levels, while release from smaller reservoirs was more dependent on reservoir inflows. Subsequently, the derived rules were used to simulate reservoir release with an average Nash-Sutcliffe coefficient of 0.81.

Rule Extraction Based on Extreme Learning Machine and an Improved Ant-Miner Algorithm for Transient Stability Assessment.

PubMed

Li, Yang; Li, Guoqing; Wang, Zhenhao

2015-01-01

In order to overcome the problems of poor understandability of the pattern recognition-based transient stability assessment (PRTSA) methods, a new rule extraction method based on extreme learning machine (ELM) and an improved Ant-miner (IAM) algorithm is presented in this paper. First, the basic principles of ELM and Ant-miner algorithm are respectively introduced. Then, based on the selected optimal feature subset, an example sample set is generated by the trained ELM-based PRTSA model. And finally, a set of classification rules are obtained by IAM algorithm to replace the original ELM network. The novelty of this proposal is that transient stability rules are extracted from an example sample set generated by the trained ELM-based transient stability assessment model by using IAM algorithm. The effectiveness of the proposed method is shown by the application results on the New England 39-bus power system and a practical power system--the southern power system of Hebei province.

Operations Nomenclature [Annexes

NASA Technical Reports Server (NTRS)

Shannon, Yvette Y.

2011-01-01

The purpose of Operations Nomenclature (OpNom) is to document methods for denoting all hardware and software and associated data referenced by operations products produced by the International Space Station (ISS) operations community. This includes Operations Data File (ODF) procedures, ground and onboard displays, mission rules, commands, messages and advisories, planning products, etc. This document applies to all agencies and individuals participating in or contributing to ISS mission operations. Mission operations include ground checkout, training, and simulations, as well as real-time activities. The document also applies to all operations documentation (paper or electronic media) and other products that refer to ISS-related equipment or activities.

Optimizing Reservoir Operation to Adapt to the Climate Change

NASA Astrophysics Data System (ADS)

Madadgar, S.; Jung, I.; Moradkhani, H.

2010-12-01

Climate change and upcoming variation in flood timing necessitates the adaptation of current rule curves developed for operation of water reservoirs as to reduce the potential damage from either flood or draught events. This study attempts to optimize the current rule curves of Cougar Dam on McKenzie River in Oregon addressing some possible climate conditions in 21th century. The objective is to minimize the failure of operation to meet either designated demands or flood limit at a downstream checkpoint. A simulation/optimization model including the standard operation policy and a global optimization method, tunes the current rule curve upon 8 GCMs and 2 greenhouse gases emission scenarios. The Precipitation Runoff Modeling System (PRMS) is used as the hydrology model to project the streamflow for the period of 2000-2100 using downscaled precipitation and temperature forcing from 8 GCMs and two emission scenarios. An ensemble of rule curves, each associated with an individual scenario, is obtained by optimizing the reservoir operation. The simulation of reservoir operation, for all the scenarios and the expected value of the ensemble, is conducted and performance assessment using statistical indices including reliability, resilience, vulnerability and sustainability is made.

Development and evaluation of a prototype in-flight instrument flight rules (IFR) procedures trainer

NASA Technical Reports Server (NTRS)

Aaron, J. B., Jr.; Morris, G. G.

1981-01-01

An in-flight instrument flight rules (IFR) procedures trainer capable of providing simulated indications of instrument flight in a typical general aviation aircraft independent of ground based navigation aids was developed. The IFR navaid related instruments and circuits from an ATC 610J table top simulator were installed in a Cessna 172 aircraft and connected to its electrical power and pitot static systems. The benefits expected from this hybridization concept include increased safety by reducing the number of general aviation aircraft conducting IFR training flights in congested terminal areas, and reduced fuel use and instruction costs by lessening the need to fly to and from navaid equipped airports and by increased efficiency of the required in-flight training. Technical feasibility was demonstrated and the operational feasibility of the concept was evaluated. Results indicated that the in-flight simulator is an effective training device for teaching IFR procedural skills.

49 CFR 37.93 - One car per train rule.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 1 2010-10-01 2010-10-01 false One car per train rule. 37.93 Section 37.93... DISABILITIES (ADA) Acquisition of Accessible Vehicles By Public Entities § 37.93 One car per train rule. (a) The definition of accessible for purposes of meeting the one car per train rule is spelled out in the...

49 CFR 37.93 - One car per train rule.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 49 Transportation 1 2013-10-01 2013-10-01 false One car per train rule. 37.93 Section 37.93... DISABILITIES (ADA) Acquisition of Accessible Vehicles By Public Entities § 37.93 One car per train rule. (a) The definition of accessible for purposes of meeting the one car per train rule is spelled out in the...

49 CFR 37.93 - One car per train rule.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 49 Transportation 1 2014-10-01 2014-10-01 false One car per train rule. 37.93 Section 37.93... DISABILITIES (ADA) Acquisition of Accessible Vehicles By Public Entities § 37.93 One car per train rule. (a) The definition of accessible for purposes of meeting the one car per train rule is spelled out in the...

49 CFR 37.93 - One car per train rule.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 49 Transportation 1 2012-10-01 2012-10-01 false One car per train rule. 37.93 Section 37.93... DISABILITIES (ADA) Acquisition of Accessible Vehicles By Public Entities § 37.93 One car per train rule. (a) The definition of accessible for purposes of meeting the one car per train rule is spelled out in the...

49 CFR 37.93 - One car per train rule.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 49 Transportation 1 2011-10-01 2011-10-01 false One car per train rule. 37.93 Section 37.93... DISABILITIES (ADA) Acquisition of Accessible Vehicles By Public Entities § 37.93 One car per train rule. (a) The definition of accessible for purposes of meeting the one car per train rule is spelled out in the...

A fuzzy hill-climbing algorithm for the development of a compact associative classifier

NASA Astrophysics Data System (ADS)

Mitra, Soumyaroop; Lam, Sarah S.

2012-02-01

Classification, a data mining technique, has widespread applications including medical diagnosis, targeted marketing, and others. Knowledge discovery from databases in the form of association rules is one of the important data mining tasks. An integrated approach, classification based on association rules, has drawn the attention of the data mining community over the last decade. While attention has been mainly focused on increasing classifier accuracies, not much efforts have been devoted towards building interpretable and less complex models. This paper discusses the development of a compact associative classification model using a hill-climbing approach and fuzzy sets. The proposed methodology builds the rule-base by selecting rules which contribute towards increasing training accuracy, thus balancing classification accuracy with the number of classification association rules. The results indicated that the proposed associative classification model can achieve competitive accuracies on benchmark datasets with continuous attributes and lend better interpretability, when compared with other rule-based systems.

75 FR 2597 - Positive Train Control Systems

Federal Register 2010, 2011, 2012, 2013, 2014

2010-01-15

... requirements for PTC system standard design and functionality, the associated submissions for FRA PTC system..., notwithstanding enforcement of railroad operating rules designed to prevent them. As early as 1970, following its... workers continued as a result of the absence of effective enforcement systems designed to compensate for...

14 CFR 141.95 - Graduation certificate.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 14 Aeronautics and Space 3 2013-01-01 2013-01-01 false Graduation certificate. 141.95 Section 141...) SCHOOLS AND OTHER CERTIFICATED AGENCIES PILOT SCHOOLS Operating Rules § 141.95 Graduation certificate. (a... graduation certificate to each student who completes its approved course of training. (b) The graduation...

14 CFR 141.95 - Graduation certificate.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 14 Aeronautics and Space 3 2014-01-01 2014-01-01 false Graduation certificate. 141.95 Section 141...) SCHOOLS AND OTHER CERTIFICATED AGENCIES PILOT SCHOOLS Operating Rules § 141.95 Graduation certificate. (a... graduation certificate to each student who completes its approved course of training. (b) The graduation...

14 CFR 141.95 - Graduation certificate.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 3 2010-01-01 2010-01-01 false Graduation certificate. 141.95 Section 141...) SCHOOLS AND OTHER CERTIFICATED AGENCIES PILOT SCHOOLS Operating Rules § 141.95 Graduation certificate. (a... graduation certificate to each student who completes its approved course of training. (b) The graduation...

14 CFR 141.95 - Graduation certificate.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 3 2012-01-01 2012-01-01 false Graduation certificate. 141.95 Section 141...) SCHOOLS AND OTHER CERTIFICATED AGENCIES PILOT SCHOOLS Operating Rules § 141.95 Graduation certificate. (a... graduation certificate to each student who completes its approved course of training. (b) The graduation...

14 CFR 141.95 - Graduation certificate.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 3 2011-01-01 2011-01-01 false Graduation certificate. 141.95 Section 141...) SCHOOLS AND OTHER CERTIFICATED AGENCIES PILOT SCHOOLS Operating Rules § 141.95 Graduation certificate. (a... graduation certificate to each student who completes its approved course of training. (b) The graduation...

76 FR 18294 - Proposed Agency Information Collection Activities; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2011-04-01

... learns the condition of operating rules and practices with respect to trains and instructions provided by... Existing On-Track Roadway Maintenance Machines Conforming with Paragraph (a) of This Section. 214.507... stencils. Maintenance Machine (RMM). 214.511--Clearly Identifiable 644 railroads...... 3,700 identified 5...

Design of Instruction. Training Information Paper, 1.

ERIC Educational Resources Information Center

Jones, Sheila

Current research in psycholinguistics has included studies of factors influencing effective verbal communication--the effect of sequences of words and operations within an instruction; effects of instruction and self-instruction on performance; and the presentation of complex interrelated rules such as those found in legal documents, regulations,…

14 CFR 135.291 - Applicability.

Code of Federal Regulations, 2014 CFR

2014-01-01

... AND ON DEMAND OPERATIONS AND RULES GOVERNING PERSONS ON BOARD SUCH AIRCRAFT Crewmember Testing... checks required for pilot and flight attendant crewmembers and for the approval of check pilots in... chapter who meet the requirements of §§ 135.337 and 135.339 to conduct training, testing, and checking...

14 CFR 135.291 - Applicability.

Code of Federal Regulations, 2013 CFR

2013-01-01

... AND ON DEMAND OPERATIONS AND RULES GOVERNING PERSONS ON BOARD SUCH AIRCRAFT Crewmember Testing... checks required for pilot and flight attendant crewmembers and for the approval of check pilots in... chapter who meet the requirements of §§ 135.337 and 135.339 to conduct training, testing, and checking...

14 CFR 135.291 - Applicability.

Code of Federal Regulations, 2012 CFR

2012-01-01

... AND ON DEMAND OPERATIONS AND RULES GOVERNING PERSONS ON BOARD SUCH AIRCRAFT Crewmember Testing... checks required for pilot and flight attendant crewmembers and for the approval of check pilots in... chapter who meet the requirements of §§ 135.337 and 135.339 to conduct training, testing, and checking...

14 CFR 135.291 - Applicability.

Code of Federal Regulations, 2011 CFR

2011-01-01

... AND ON DEMAND OPERATIONS AND RULES GOVERNING PERSONS ON BOARD SUCH AIRCRAFT Crewmember Testing... checks required for pilot and flight attendant crewmembers and for the approval of check pilots in... chapter who meet the requirements of §§ 135.337 and 135.339 to conduct training, testing, and checking...

14 CFR 135.291 - Applicability.

Code of Federal Regulations, 2010 CFR

2010-01-01

... AND ON DEMAND OPERATIONS AND RULES GOVERNING PERSONS ON BOARD SUCH AIRCRAFT Crewmember Testing... checks required for pilot and flight attendant crewmembers and for the approval of check pilots in... chapter who meet the requirements of §§ 135.337 and 135.339 to conduct training, testing, and checking...

Pilot interaction with automated airborne decision making systems

NASA Technical Reports Server (NTRS)

Rouse, W. B.; Hammer, J. M.; Mitchell, C. M.; Morris, N. M.; Lewis, C. M.; Yoon, W. C.

1985-01-01

Progress was made in the three following areas. In the rule-based modeling area, two papers related to identification and significane testing of rule-based models were presented. In the area of operator aiding, research focused on aiding operators in novel failure situations; a discrete control modeling approach to aiding PLANT operators was developed; and a set of guidelines were developed for implementing automation. In the area of flight simulator hardware and software, the hardware will be completed within two months and initial simulation software will then be integrated and tested.

Model-based Systems Engineering: Creation and Implementation of Model Validation Rules for MOS 2.0

NASA Technical Reports Server (NTRS)

Schmidt, Conrad K.

2013-01-01

Model-based Systems Engineering (MBSE) is an emerging modeling application that is used to enhance the system development process. MBSE allows for the centralization of project and system information that would otherwise be stored in extraneous locations, yielding better communication, expedited document generation and increased knowledge capture. Based on MBSE concepts and the employment of the Systems Modeling Language (SysML), extremely large and complex systems can be modeled from conceptual design through all system lifecycles. The Operations Revitalization Initiative (OpsRev) seeks to leverage MBSE to modernize the aging Advanced Multi-Mission Operations Systems (AMMOS) into the Mission Operations System 2.0 (MOS 2.0). The MOS 2.0 will be delivered in a series of conceptual and design models and documents built using the modeling tool MagicDraw. To ensure model completeness and cohesiveness, it is imperative that the MOS 2.0 models adhere to the specifications, patterns and profiles of the Mission Service Architecture Framework, thus leading to the use of validation rules. This paper outlines the process by which validation rules are identified, designed, implemented and tested. Ultimately, these rules provide the ability to maintain model correctness and synchronization in a simple, quick and effective manner, thus allowing the continuation of project and system progress.

Training self-assessment and task-selection skills to foster self-regulated learning: Do trained skills transfer across domains?

PubMed

Raaijmakers, Steven F; Baars, Martine; Paas, Fred; van Merriënboer, Jeroen J G; van Gog, Tamara

2018-01-01

Students' ability to accurately self-assess their performance and select a suitable subsequent learning task in response is imperative for effective self-regulated learning. Video modeling examples have proven effective for training self-assessment and task-selection skills, and-importantly-such training fostered self-regulated learning outcomes. It is unclear, however, whether trained skills would transfer across domains. We investigated whether skills acquired from training with either a specific, algorithmic task-selection rule or a more general heuristic task-selection rule in biology would transfer to self-regulated learning in math. A manipulation check performed after the training confirmed that both algorithmic and heuristic training improved task-selection skills on the biology problems compared with the control condition. However, we found no evidence that students subsequently applied the acquired skills during self-regulated learning in math. Future research should investigate how to support transfer of task-selection skills across domains.

Training self‐assessment and task‐selection skills to foster self‐regulated learning: Do trained skills transfer across domains?

PubMed Central

Baars, Martine; Paas, Fred; van Merriënboer, Jeroen J. G.; van Gog, Tamara

2018-01-01

Summary Students' ability to accurately self‐assess their performance and select a suitable subsequent learning task in response is imperative for effective self‐regulated learning. Video modeling examples have proven effective for training self‐assessment and task‐selection skills, and—importantly—such training fostered self‐regulated learning outcomes. It is unclear, however, whether trained skills would transfer across domains. We investigated whether skills acquired from training with either a specific, algorithmic task‐selection rule or a more general heuristic task‐selection rule in biology would transfer to self‐regulated learning in math. A manipulation check performed after the training confirmed that both algorithmic and heuristic training improved task‐selection skills on the biology problems compared with the control condition. However, we found no evidence that students subsequently applied the acquired skills during self‐regulated learning in math. Future research should investigate how to support transfer of task‐selection skills across domains. PMID:29610547

Assessment of Matrix Multiplication Learning with a Rule-Based Analytical Model--"A Bayesian Network Representation"

ERIC Educational Resources Information Center

Zhang, Zhidong

2016-01-01

This study explored an alternative assessment procedure to examine learning trajectories of matrix multiplication. It took rule-based analytical and cognitive task analysis methods specifically to break down operation rules for a given matrix multiplication. Based on the analysis results, a hierarchical Bayesian network, an assessment model,…

76 FR 16851 - Notice of Intent To Rule on Passenger Facility Charge (PFC) Application 11-11-C-00-BUR, To Impose...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-25

... Act of 1990 (Title IX of the Omnibus Budget Reconciliation Act of 1990, Public Law 101-508) and Part... operators and off-airport hotel vans; pedestrian crosswalk across Empire Avenue to connect the train station...

Evaluating the performance of a fault detection and diagnostic system for vapor compression equipment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Breuker, M.S.; Braun, J.E.

This paper presents a detailed evaluation of the performance of a statistical, rule-based fault detection and diagnostic (FDD) technique presented by Rossi and Braun (1997). Steady-state and transient tests were performed on a simple rooftop air conditioner over a range of conditions and fault levels. The steady-state data without faults were used to train models that predict outputs for normal operation. The transient data with faults were used to evaluate FDD performance. The effect of a number of design variables on FDD sensitivity for different faults was evaluated and two prototype systems were specified for more complete evaluation. Good performancemore » was achieved in detecting and diagnosing five faults using only six temperatures (2 input and 4 output) and linear models. The performance improved by about a factor of two when ten measurements (three input and seven output) and higher order models were used. This approach for evaluating and optimizing the performance of the statistical, rule-based FDD technique could be used as a design and evaluation tool when applying this FDD method to other packaged air-conditioning systems. Furthermore, the approach could also be modified to evaluate the performance of other FDD methods.« less

Transition sum rules in the shell model

NASA Astrophysics Data System (ADS)

Lu, Yi; Johnson, Calvin W.

2018-03-01

An important characterization of electromagnetic and weak transitions in atomic nuclei are sum rules. We focus on the non-energy-weighted sum rule (NEWSR), or total strength, and the energy-weighted sum rule (EWSR); the ratio of the EWSR to the NEWSR is the centroid or average energy of transition strengths from an nuclear initial state to all allowed final states. These sum rules can be expressed as expectation values of operators, which in the case of the EWSR is a double commutator. While most prior applications of the double commutator have been to special cases, we derive general formulas for matrix elements of both operators in a shell model framework (occupation space), given the input matrix elements for the nuclear Hamiltonian and for the transition operator. With these new formulas, we easily evaluate centroids of transition strength functions, with no need to calculate daughter states. We apply this simple tool to a number of nuclides and demonstrate the sum rules follow smooth secular behavior as a function of initial energy, as well as compare the electric dipole (E 1 ) sum rule against the famous Thomas-Reiche-Kuhn version. We also find surprising systematic behaviors for ground-state electric quadrupole (E 2 ) centroids in the s d shell.

PSOLA: A Heuristic Land-Use Allocation Model Using Patch-Level Operations and Knowledge-Informed Rules.

PubMed

Liu, Yaolin; Peng, Jinjin; Jiao, Limin; Liu, Yanfang

2016-01-01

Optimizing land-use allocation is important to regional sustainable development, as it promotes the social equality of public services, increases the economic benefits of land-use activities, and reduces the ecological risk of land-use planning. Most land-use optimization models allocate land-use using cell-level operations that fragment land-use patches. These models do not cooperate well with land-use planning knowledge, leading to irrational land-use patterns. This study focuses on building a heuristic land-use allocation model (PSOLA) using particle swarm optimization. The model allocates land-use with patch-level operations to avoid fragmentation. The patch-level operations include a patch-edge operator, a patch-size operator, and a patch-compactness operator that constrain the size and shape of land-use patches. The model is also integrated with knowledge-informed rules to provide auxiliary knowledge of land-use planning during optimization. The knowledge-informed rules consist of suitability, accessibility, land use policy, and stakeholders' preference. To validate the PSOLA model, a case study was performed in Gaoqiao Town in Zhejiang Province, China. The results demonstrate that the PSOLA model outperforms a basic PSO (Particle Swarm Optimization) in the terms of the social, economic, ecological, and overall benefits by 3.60%, 7.10%, 1.53% and 4.06%, respectively, which confirms the effectiveness of our improvements. Furthermore, the model has an open architecture, enabling its extension as a generic tool to support decision making in land-use planning.

PSOLA: A Heuristic Land-Use Allocation Model Using Patch-Level Operations and Knowledge-Informed Rules

PubMed Central

Liu, Yaolin; Peng, Jinjin; Jiao, Limin; Liu, Yanfang

2016-01-01

Optimizing land-use allocation is important to regional sustainable development, as it promotes the social equality of public services, increases the economic benefits of land-use activities, and reduces the ecological risk of land-use planning. Most land-use optimization models allocate land-use using cell-level operations that fragment land-use patches. These models do not cooperate well with land-use planning knowledge, leading to irrational land-use patterns. This study focuses on building a heuristic land-use allocation model (PSOLA) using particle swarm optimization. The model allocates land-use with patch-level operations to avoid fragmentation. The patch-level operations include a patch-edge operator, a patch-size operator, and a patch-compactness operator that constrain the size and shape of land-use patches. The model is also integrated with knowledge-informed rules to provide auxiliary knowledge of land-use planning during optimization. The knowledge-informed rules consist of suitability, accessibility, land use policy, and stakeholders’ preference. To validate the PSOLA model, a case study was performed in Gaoqiao Town in Zhejiang Province, China. The results demonstrate that the PSOLA model outperforms a basic PSO (Particle Swarm Optimization) in the terms of the social, economic, ecological, and overall benefits by 3.60%, 7.10%, 1.53% and 4.06%, respectively, which confirms the effectiveness of our improvements. Furthermore, the model has an open architecture, enabling its extension as a generic tool to support decision making in land-use planning. PMID:27322619

Higher Education: New Models, New Rules

ERIC Educational Resources Information Center

Soares, Louis; Eaton, Judith S.; Smith, Burck

2013-01-01

The Internet enables new models. In the commercial world, for example, we have eBay, Amazon.com, and Netflix. These new models operate with a different set of rules than do traditional models. New models are emerging in higher education as well--for example, competency-based programs. In addition, courses that are being provided from outside the…

Development of an intelligent surgical training system for Thoracentesis.

PubMed

Nakawala, Hirenkumar; Ferrigno, Giancarlo; De Momi, Elena

2018-01-01

Surgical training improves patient care, helps to reduce surgical risks, increases surgeon's confidence, and thus enhances overall patient safety. Current surgical training systems are more focused on developing technical skills, e.g. dexterity, of the surgeons while lacking the aspects of context-awareness and intra-operative real-time guidance. Context-aware intelligent training systems interpret the current surgical situation and help surgeons to train on surgical tasks. As a prototypical scenario, we chose Thoracentesis procedure in this work. We designed the context-aware software framework using the surgical process model encompassing ontology and production rules, based on the procedure descriptions obtained through textbooks and interviews, and ontology-based and marker-based object recognition, where the system tracked and recognised surgical instruments and materials in surgeon's hands and recognised surgical instruments on the surgical stand. The ontology was validated using annotated surgical videos, where the system identified "Anaesthesia" and "Aspiration" phase with 100% relative frequency and "Penetration" phase with 65% relative frequency. The system tracked surgical swab and 50mL syringe with approximately 88.23% and 100% accuracy in surgeon's hands and recognised surgical instruments with approximately 90% accuracy on the surgical stand. Surgical workflow training with the proposed system showed equivalent results as the traditional mentor-based training regime, thus this work is a step forward a new tool for context awareness and decision-making during surgical training. Copyright © 2017 Elsevier B.V. All rights reserved.

Adaptive optimal training of animal behavior

NASA Astrophysics Data System (ADS)

Bak, Ji Hyun; Choi, Jung Yoon; Akrami, Athena; Witten, Ilana; Pillow, Jonathan

Neuroscience experiments often require training animals to perform tasks designed to elicit various sensory, cognitive, and motor behaviors. Training typically involves a series of gradual adjustments of stimulus conditions and rewards in order to bring about learning. However, training protocols are usually hand-designed, and often require weeks or months to achieve a desired level of task performance. Here we combine ideas from reinforcement learning and adaptive optimal experimental design to formulate methods for efficient training of animal behavior. Our work addresses two intriguing problems at once: first, it seeks to infer the learning rules underlying an animal's behavioral changes during training; second, it seeks to exploit these rules to select stimuli that will maximize the rate of learning toward a desired objective. We develop and test these methods using data collected from rats during training on a two-interval sensory discrimination task. We show that we can accurately infer the parameters of a learning algorithm that describes how the animal's internal model of the task evolves over the course of training. We also demonstrate by simulation that our method can provide a substantial speedup over standard training methods.

General purpose architecture for intelligent computer-aided training

NASA Technical Reports Server (NTRS)

Loftin, R. Bowen (Inventor); Wang, Lui (Inventor); Baffes, Paul T. (Inventor); Hua, Grace C. (Inventor)

1994-01-01

An intelligent computer-aided training system having a general modular architecture is provided for use in a wide variety of training tasks and environments. It is comprised of a user interface which permits the trainee to access the same information available in the task environment and serves as a means for the trainee to assert actions to the system; a domain expert which is sufficiently intelligent to use the same information available to the trainee and carry out the task assigned to the trainee; a training session manager for examining the assertions made by the domain expert and by the trainee for evaluating such trainee assertions and providing guidance to the trainee which are appropriate to his acquired skill level; a trainee model which contains a history of the trainee interactions with the system together with summary evaluative data; an intelligent training scenario generator for designing increasingly complex training exercises based on the current skill level contained in the trainee model and on any weaknesses or deficiencies that the trainee has exhibited in previous interactions; and a blackboard that provides a common fact base for communication between the other components of the system. Preferably, the domain expert contains a list of 'mal-rules' which typifies errors that are usually made by novice trainees. Also preferably, the training session manager comprises an intelligent error detection means and an intelligent error handling means. The present invention utilizes a rule-based language having a control structure whereby a specific message passing protocol is utilized with respect to tasks which are procedural or step-by-step in structure. The rules can be activated by the trainee in any order to reach the solution by any valid or correct path.

CARSVM: a class association rule-based classification framework and its application to gene expression data.

PubMed

Kianmehr, Keivan; Alhajj, Reda

2008-09-01

In this study, we aim at building a classification framework, namely the CARSVM model, which integrates association rule mining and support vector machine (SVM). The goal is to benefit from advantages of both, the discriminative knowledge represented by class association rules and the classification power of the SVM algorithm, to construct an efficient and accurate classifier model that improves the interpretability problem of SVM as a traditional machine learning technique and overcomes the efficiency issues of associative classification algorithms. In our proposed framework: instead of using the original training set, a set of rule-based feature vectors, which are generated based on the discriminative ability of class association rules over the training samples, are presented to the learning component of the SVM algorithm. We show that rule-based feature vectors present a high-qualified source of discrimination knowledge that can impact substantially the prediction power of SVM and associative classification techniques. They provide users with more conveniences in terms of understandability and interpretability as well. We have used four datasets from UCI ML repository to evaluate the performance of the developed system in comparison with five well-known existing classification methods. Because of the importance and popularity of gene expression analysis as real world application of the classification model, we present an extension of CARSVM combined with feature selection to be applied to gene expression data. Then, we describe how this combination will provide biologists with an efficient and understandable classifier model. The reported test results and their biological interpretation demonstrate the applicability, efficiency and effectiveness of the proposed model. From the results, it can be concluded that a considerable increase in classification accuracy can be obtained when the rule-based feature vectors are integrated in the learning process of the SVM algorithm. In the context of applicability, according to the results obtained from gene expression analysis, we can conclude that the CARSVM system can be utilized in a variety of real world applications with some adjustments.

For Spacious Skies: Self-Separation with "Autonomous Flight Rules" in US Domestic Airspace

NASA Technical Reports Server (NTRS)

Wing, David J.; Cotton, William B.

2011-01-01

Autonomous Flight Rules (AFR) are proposed as a new set of operating regulations in which aircraft navigate on tracks of their choice while self-separating from traffic and weather. AFR would exist alongside Instrument and Visual Flight Rules (IFR and VFR) as one of three available flight options for any appropriately trained and qualified operator with the necessary certified equipment. Historically, ground-based separation services evolved by necessity as aircraft began operating in the clouds and were unable to see each other. Today, technologies for global precision navigation, emerging airborne surveillance, and onboard computing enable traffic conflict management to be fully integrated with navigation procedures onboard the aircraft. By self-separating, aircraft can operate with more flexibility and fewer flight restrictions than are required when using ground-based separation. The AFR concept proposes a practical means in which self-separating aircraft could share the same airspace as IFR and VFR aircraft without disrupting the ongoing processes of Air Traffic Control. The paper discusses the context and motivation for implementing self-separation in US domestic airspace. It presents a historical perspective on separation, the proposed way forward in AFR, the rationale behind mixed operations, and the expected benefits of AFR for the airspace user community.

20 CFR 638.512 - Sexual behavior and harassment.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 20 Employees' Benefits 3 2010-04-01 2010-04-01 false Sexual behavior and harassment. 638.512... establish rules concerning sexual behavior and harassment. See also §§ 638.539(g) and 638.813(a) of this... PROGRAM UNDER TITLE IV-B OF THE JOB TRAINING PARTNERSHIP ACT Center Operations § 638.512 Sexual behavior...

Heating, Ventilation, Air Conditioning. Resource Manual for Custodial Training Course #3.

ERIC Educational Resources Information Center

Florida State Dept. of Education, Tallahassee. School Plant Management Section.

Intended as a manual to provide school custodians with some understanding of basic functions of heating, ventilating, and air conditioning equipment for safe, efficient operation. Contains general rules and specifications for providing custodians with a more complete awareness of their equipment and the field of "Climate Control" within the…

20 CFR 638.512 - Sexual behavior and harassment.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 20 Employees' Benefits 3 2012-04-01 2012-04-01 false Sexual behavior and harassment. 638.512... PROGRAM UNDER TITLE IV-B OF THE JOB TRAINING PARTNERSHIP ACT Center Operations § 638.512 Sexual behavior... establish rules concerning sexual behavior and harassment. See also §§ 638.539(g) and 638.813(a) of this...

20 CFR 638.512 - Sexual behavior and harassment.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 20 Employees' Benefits 3 2011-04-01 2011-04-01 false Sexual behavior and harassment. 638.512... PROGRAM UNDER TITLE IV-B OF THE JOB TRAINING PARTNERSHIP ACT Center Operations § 638.512 Sexual behavior... establish rules concerning sexual behavior and harassment. See also §§ 638.539(g) and 638.813(a) of this...

A Control Simulation Method of High-Speed Trains on Railway Network with Irregular Influence

NASA Astrophysics Data System (ADS)

Yang, Li-Xing; Li, Xiang; Li, Ke-Ping

2011-09-01

Based on the discrete time method, an effective movement control model is designed for a group of highspeed trains on a rail network. The purpose of the model is to investigate the specific traffic characteristics of high-speed trains under the interruption of stochastic irregular events. In the model, the high-speed rail traffic system is supposed to be equipped with the moving-block signalling system to guarantee maximum traversing capacity of the railway. To keep the safety of trains' movements, some operational strategies are proposed to control the movements of trains in the model, including traction operation, braking operation, and entering-station operation. The numerical simulations show that the designed model can well describe the movements of high-speed trains on the rail network. The research results can provide the useful information not only for investigating the propagation features of relevant delays under the irregular disturbance but also for rerouting and rescheduling trains on the rail network.

The NEEMO Project: A Report on how NASA Utilizes the "Aquarius" Undersea Habitat as an Analog for Long-Duration Space Flight

NASA Technical Reports Server (NTRS)

Reagan, Marc; Todd, William

2003-01-01

NEEMO is the NASA Extreme Environment Mission Operations, a cooperative project between NASA and the National Oceanic and Atmospheric Administration (NOAA). NEEMO was created and is managed by the Mission Operations Directorate at the Johnson Space Center in Houston, Texas. On the NOAA side, the National Undersea Research Center (NURC) in Key Largo, FL, with the help of the University of North Carolina at Wilmington, manages and operates the Aquarius Program. NEEMO was developed by astronaut training specialists to utilize an undersea research habitat as a multi-objective mission analog for long-duration space flight. Each mission was designed to expose astronauts to extreme environments for training purposes and to research crew behavior, habitability, and space analog life sciences. All of this was done much in the model of a space mission utilizing specific crew procedures, mission rules and timelines. Objectives of the missions were very diverse and contained many of the typical space mission type activities such as EV As (also known as extra vehicular activities), in-habitat science and research, and educational, public outreach, and media events. Five missions, dubbed NEEMO 1-5, were conducted between October 2001 and July 2003, the longest of which (NEEMO 5) lasted 14 days.

Generalized DSS shell for developing simulation and optimization hydro-economic models of complex water resources systems

NASA Astrophysics Data System (ADS)

Pulido-Velazquez, Manuel; Lopez-Nicolas, Antonio; Harou, Julien J.; Andreu, Joaquin

2013-04-01

Hydrologic-economic models allow integrated analysis of water supply, demand and infrastructure management at the river basin scale. These models simultaneously analyze engineering, hydrology and economic aspects of water resources management. Two new tools have been designed to develop models within this approach: a simulation tool (SIM_GAMS), for models in which water is allocated each month based on supply priorities to competing uses and system operating rules, and an optimization tool (OPT_GAMS), in which water resources are allocated optimally following economic criteria. The characterization of the water resource network system requires a connectivity matrix representing the topology of the elements, generated using HydroPlatform. HydroPlatform, an open-source software platform for network (node-link) models, allows to store, display and export all information needed to characterize the system. Two generic non-linear models have been programmed in GAMS to use the inputs from HydroPlatform in simulation and optimization models. The simulation model allocates water resources on a monthly basis, according to different targets (demands, storage, environmental flows, hydropower production, etc.), priorities and other system operating rules (such as reservoir operating rules). The optimization model's objective function is designed so that the system meets operational targets (ranked according to priorities) each month while following system operating rules. This function is analogous to the one used in the simulation module of the DSS AQUATOOL. Each element of the system has its own contribution to the objective function through unit cost coefficients that preserve the relative priority rank and the system operating rules. The model incorporates groundwater and stream-aquifer interaction (allowing conjunctive use simulation) with a wide range of modeling options, from lumped and analytical approaches to parameter-distributed models (eigenvalue approach). Such functionality is not typically included in other water DSS. Based on the resulting water resources allocation, the model calculates operating and water scarcity costs caused by supply deficits based on economic demand functions for each demand node. The optimization model allocates the available resource over time based on economic criteria (net benefits from demand curves and cost functions), minimizing the total water scarcity and operating cost of water use. This approach provides solutions that optimize the economic efficiency (as total net benefit) in water resources management over the optimization period. Both models must be used together in water resource planning and management. The optimization model provides an initial insight on economically efficient solutions, from which different operating rules can be further developed and tested using the simulation model. The hydro-economic simulation model allows assessing economic impacts of alternative policies or operating criteria, avoiding the perfect foresight issues associated with the optimization. The tools have been applied to the Jucar river basin (Spain) in order to assess the economic results corresponding to the current modus operandi of the system and compare them with the solution from the optimization that maximizes economic efficiency. Acknowledgments: The study has been partially supported by the European Community 7th Framework Project (GENESIS project, n. 226536) and the Plan Nacional I+D+I 2008-2011 of the Spanish Ministry of Science and Innovation (CGL2009-13238-C02-01 and CGL2009-13238-C02-02).

Classification capacity of a modular neural network implementing neurally inspired architecture and training rules.

PubMed

Poirazi, Panayiota; Neocleous, Costas; Pattichis, Costantinos S; Schizas, Christos N

2004-05-01

A three-layer neural network (NN) with novel adaptive architecture has been developed. The hidden layer of the network consists of slabs of single neuron models, where neurons within a slab--but not between slabs--have the same type of activation function. The network activation functions in all three layers have adaptable parameters. The network was trained using a biologically inspired, guided-annealing learning rule on a variety of medical data. Good training/testing classification performance was obtained on all data sets tested. The performance achieved was comparable to that of SVM classifiers. It was shown that the adaptive network architecture, inspired from the modular organization often encountered in the mammalian cerebral cortex, can benefit classification performance.

A reinforcement learning-based architecture for fuzzy logic control

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1992-01-01

This paper introduces a new method for learning to refine a rule-based fuzzy logic controller. A reinforcement learning technique is used in conjunction with a multilayer neural network model of a fuzzy controller. The approximate reasoning based intelligent control (ARIC) architecture proposed here learns by updating its prediction of the physical system's behavior and fine tunes a control knowledge base. Its theory is related to Sutton's temporal difference (TD) method. Because ARIC has the advantage of using the control knowledge of an experienced operator and fine tuning it through the process of learning, it learns faster than systems that train networks from scratch. The approach is applied to a cart-pole balancing system.

Operator priming and generalization of practice in adults' simple arithmetic.

PubMed

Chen, Yalin; Campbell, Jamie I D

2016-04-01

There is a renewed debate about whether educated adults solve simple addition problems (e.g., 2 + 3) by direct fact retrieval or by fast, automatic counting-based procedures. Recent research testing adults' simple addition and multiplication showed that a 150-ms preview of the operator (+ or ×) facilitated addition, but not multiplication, suggesting that a general addition procedure was primed by the + sign. In Experiment 1 (n = 36), we applied this operator-priming paradigm to rule-based problems (0 + N = N, 1 × N = N, 0 × N = 0) and 1 + N problems with N ranging from 0 to 9. For the rule-based problems, we found both operator-preview facilitation and generalization of practice (e.g., practicing 0 + 3 sped up unpracticed 0 + 8), the latter being a signature of procedure use; however, we also found operator-preview facilitation for 1 + N in the absence of generalization, which implies the 1 + N problems were solved by fact retrieval but nonetheless were facilitated by an operator preview. Thus, the operator preview effect does not discriminate procedure use from fact retrieval. Experiment 2 (n = 36) investigated whether a population with advanced mathematical training-engineering and computer science students-would show generalization of practice for nonrule-based simple addition problems (e.g., 1 + 4, 4 + 7). The 0 + N problems again presented generalization, whereas no nonzero problem type did; but all nonzero problems sped up when the identical problems were retested, as predicted by item-specific fact retrieval. The results pose a strong challenge to the generality of the proposal that skilled adults' simple addition is based on fast procedural algorithms, and instead support a fact-retrieval model of fast addition performance. (c) 2016 APA, all rights reserved).

Energy-weighted sum rules connecting ΔZ = 2 nuclei within the SO(8) model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Štefánik, Dušan; Šimkovic, Fedor; Faessler, Amand

2013-12-30

Energy-weighted sum rules associated with ΔZ = 2 nuclei are obtained for the Fermi and the Gamow-Teller operators within the SO(8) model. It is found that there is a dominance of contribution of a single state of the intermediate nucleus to the sum rule. The results confirm founding obtained within the SO(5) model that the energy-weighted sum rules of ΔZ = 2 nuclei are governed by the residual interactions of nuclear Hamiltonian. A short discussion concerning some aspects of energy weighted sum rules in the case of realistic nuclei is included.

Adaptive model training system and method

DOEpatents

Bickford, Randall L; Palnitkar, Rahul M; Lee, Vo

2014-04-15

An adaptive model training system and method for filtering asset operating data values acquired from a monitored asset for selectively choosing asset operating data values that meet at least one predefined criterion of good data quality while rejecting asset operating data values that fail to meet at least the one predefined criterion of good data quality; and recalibrating a previously trained or calibrated model having a learned scope of normal operation of the asset by utilizing the asset operating data values that meet at least the one predefined criterion of good data quality for adjusting the learned scope of normal operation of the asset for defining a recalibrated model having the adjusted learned scope of normal operation of the asset.

Adaptive model training system and method

DOEpatents

Bickford, Randall L; Palnitkar, Rahul M

2014-11-18

An adaptive model training system and method for filtering asset operating data values acquired from a monitored asset for selectively choosing asset operating data values that meet at least one predefined criterion of good data quality while rejecting asset operating data values that fail to meet at least the one predefined criterion of good data quality; and recalibrating a previously trained or calibrated model having a learned scope of normal operation of the asset by utilizing the asset operating data values that meet at least the one predefined criterion of good data quality for adjusting the learned scope of normal operation of the asset for defining a recalibrated model having the adjusted learned scope of normal operation of the asset.

Transition sum rules in the shell model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lu, Yi; Johnson, Calvin W.

An important characterization of electromagnetic and weak transitions in atomic nuclei are sum rules. We focus on the non-energy-weighted sum rule (NEWSR), or total strength, and the energy- weighted sum rule (EWSR); the ratio of the EWSR to the NEWSR is the centroid or average energy of transition strengths from an nuclear initial state to all allowed final states. These sum rules can be expressed as expectation values of operators, in the case of the EWSR a double commutator. While most prior applications of the double-commutator have been to special cases, we derive general formulas for matrix elements of bothmore » operators in a shell model framework (occupation space), given the input matrix elements for the nuclear Hamiltonian and for the transition operator. With these new formulas, we easily evaluate centroids of transition strength functions, with no need to calculate daughter states. We then apply this simple tool to a number of nuclides, and demonstrate the sum rules follow smooth secular behavior as a function of initial energy, as well as compare the electric dipole (E1) sum rule against the famous Thomas-Reiche-Kuhn version. We also find surprising systematic behaviors for ground state electric quadrupole (E2) centroids in the $sd$-shell.« less

Transition sum rules in the shell model

DOE PAGES

Lu, Yi; Johnson, Calvin W.

2018-03-29

An important characterization of electromagnetic and weak transitions in atomic nuclei are sum rules. We focus on the non-energy-weighted sum rule (NEWSR), or total strength, and the energy- weighted sum rule (EWSR); the ratio of the EWSR to the NEWSR is the centroid or average energy of transition strengths from an nuclear initial state to all allowed final states. These sum rules can be expressed as expectation values of operators, in the case of the EWSR a double commutator. While most prior applications of the double-commutator have been to special cases, we derive general formulas for matrix elements of bothmore » operators in a shell model framework (occupation space), given the input matrix elements for the nuclear Hamiltonian and for the transition operator. With these new formulas, we easily evaluate centroids of transition strength functions, with no need to calculate daughter states. We then apply this simple tool to a number of nuclides, and demonstrate the sum rules follow smooth secular behavior as a function of initial energy, as well as compare the electric dipole (E1) sum rule against the famous Thomas-Reiche-Kuhn version. We also find surprising systematic behaviors for ground state electric quadrupole (E2) centroids in the $sd$-shell.« less

Rule-governed behavior: teaching a preliminary repertoire of rule-following to children with autism.

PubMed

Tarbox, Jonathan; Zuckerman, Carrie K; Bishop, Michele R; Olive, Melissa L; O'Hora, Denis P

2011-01-01

Rule-governed behavior is generally considered an integral component of complex verbal repertoires but has rarely been the subject of empirical research. In particular, little or no previous research has attempted to establish rule-governed behavior in individuals who do not already display the repertoire. This study consists of two experiments that evaluated multiple exemplar training procedures for teaching a simple component skill, which may be necessary for developing a repertoire of rule-governed behavior. In both experiments, children with autism were taught to respond to simple rules that specified antecedents and the behaviors that should occur in their presence. In the first study, participants were taught to respond to rules containing "if/then" statements, where the antecedent was specified before the behavior. The second experiment was a replication and extension of the first. It involved a variation on the manner in which rules were presented. Both experiments eventually demonstrated generalization to novel rules for all participants; however variations to the standard procedure were required for several participants. Results suggest that rule-following can be analyzed and taught as generalized operant behavior and implications for future research are discussed.

New rules for visual selection: Isolating procedural attention.

PubMed

Ramamurthy, Mahalakshmi; Blaser, Erik

2017-02-01

High performance in well-practiced, everyday tasks-driving, sports, gaming-suggests a kind of procedural attention that can allocate processing resources to behaviorally relevant information in an unsupervised manner. Here we show that training can lead to a new, automatic attentional selection rule that operates in the absence of bottom-up, salience-driven triggers and willful top-down selection. Taking advantage of the fact that attention modulates motion aftereffects, observers were presented with a bivectorial display with overlapping, iso-salient red and green dot fields moving to the right and left, respectively, while distracted by a demanding auditory two-back memory task. Before training, since the motion vectors canceled each other out, no net motion aftereffect (MAE) was found. However, after 3 days (0.5 hr/day) of training, during which observers practiced selectively attending to the red, rightward field, a significant net MAE was observed-even when top-down selection was again distracted. Further experiments showed that these results were not due to perceptual learning, and that the new rule targeted the motion, and not the color of the target dot field, and global, not local, motion signals; thus, the new rule was: "select the rightward field." This study builds on recent work on selection history-driven and reward-driven biases, but uses a novel paradigm where the allocation of visual processing resources are measured passively, offline, and when the observer's ability to execute top-down selection is defeated.

Motion direction discrimination training reduces perceived motion repulsion.

PubMed

Jia, Ke; Li, Sheng

2017-04-01

Participants often exaggerate the perceived angular separation between two simultaneously presented motion stimuli, which is referred to as motion repulsion. The overestimation helps participants differentiate between the two superimposed motion directions, yet it causes the impairment of direction perception. Since direction perception can be refined through perceptual training, we here attempted to investigate whether the training of a direction discrimination task changes the amount of motion repulsion. Our results showed a direction-specific learning effect, which was accompanied by a reduced amount of motion repulsion both for the trained and the untrained directions. The reduction of the motion repulsion disappeared when the participants were trained on a luminance discrimination task (control experiment 1) or a speed discrimination task (control experiment 2), ruling out any possible interpretation in terms of adaptation or training-induced attentional bias. Furthermore, training with a direction discrimination task along a direction 150° away from both directions in the transparent stimulus (control experiment 3) also had little effect on the amount of motion repulsion, ruling out the contribution of task learning. The changed motion repulsion observed in the main experiment was consistent with the prediction of the recurrent model of perceptual learning. Therefore, our findings demonstrate that training in direction discrimination can benefit the precise direction perception of the transparent stimulus and provide new evidence for the recurrent model of perceptual learning.

Two-dimensional lattice Boltzmann model for magnetohydrodynamics.

PubMed

Schaffenberger, Werner; Hanslmeier, Arnold

2002-10-01

We present a lattice Boltzmann model for the simulation of two-dimensional magnetohydro dynamic (MHD) flows. The model is an extension of a hydrodynamic lattice Boltzman model with 9 velocities on a square lattice resulting in a model with 17 velocities. Earlier lattice Boltzmann models for two-dimensional MHD used a bidirectional streaming rule. However, the use of such a bidirectional streaming rule is not necessary. In our model, the standard streaming rule is used, allowing smaller viscosities. To control the viscosity and the resistivity independently, a matrix collision operator is used. The model is then applied to the Hartmann flow, giving reasonable results.

The numerical modelling and process simulation for the fault diagnosis of rotary kiln incinerator.

PubMed

Roh, S D; Kim, S W; Cho, W S

2001-10-01

The numerical modelling and process simulation for the fault diagnosis of rotary kiln incinerator were accomplished. In the numerical modelling, two models applied to the modelling within the kiln are the combustion chamber model including the mass and energy balance equations for two combustion chambers and 3D thermal model. The combustion chamber model predicts temperature within the kiln, flue gas composition, flux and heat of combustion. Using the combustion chamber model and 3D thermal model, the production-rules for the process simulation can be obtained through interrelation analysis between control and operation variables. The process simulation of the kiln is operated with the production-rules for automatic operation. The process simulation aims to provide fundamental solutions to the problems in incineration process by introducing an online expert control system to provide an integrity in process control and management. Knowledge-based expert control systems use symbolic logic and heuristic rules to find solutions for various types of problems. It was implemented to be a hybrid intelligent expert control system by mutually connecting with the process control systems which has the capability of process diagnosis, analysis and control.

Combined Economic and Hydrologic Modeling to Support Collaborative Decision Making Processes

NASA Astrophysics Data System (ADS)

Sheer, D. P.

2008-12-01

For more than a decade, the core concept of the author's efforts in support of collaborative decision making has been a combination of hydrologic simulation and multi-objective optimization. The modeling has generally been used to support collaborative decision making processes. The OASIS model developed by HydroLogics Inc. solves a multi-objective optimization at each time step using a mixed integer linear program (MILP). The MILP can be configured to include any user defined objective, including but not limited too economic objectives. For example, an estimated marginal value for water for crops and M&I use were included in the objective function to drive trades in a model of the lower Rio Grande. The formulation of the MILP, constraints and objectives, in any time step is conditional: it changes based on the value of state variables and dynamic external forcing functions, such as rainfall, hydrology, market prices, arrival of migratory fish, water temperature, etc. It therefore acts as a dynamic short term multi-objective economic optimization for each time step. MILP is capable of solving a general problem that includes a very realistic representation of the physical system characteristics in addition to the normal multi-objective optimization objectives and constraints included in economic models. In all of these models, the short term objective function is a surrogate for achieving long term multi-objective results. The long term performance for any alternative (especially including operating strategies) is evaluated by simulation. An operating rule is the combination of conditions, parameters, constraints and objectives used to determine the formulation of the short term optimization in each time step. Heuristic wrappers for the simulation program have been developed improve the parameters of an operating rule, and are initiating research on a wrapper that will allow us to employ a genetic algorithm to improve the form of the rule (conditions, constraints, and short term objectives) as well. In the models operating rules represent different models of human behavior, and the objective of the modeling is to find rules for human behavior that perform well in terms of long term human objectives. The conceptual model used to represent human behavior incorporates economic multi-objective optimization for surrogate objectives, and rules that set those objectives based on current conditions and accounting for uncertainty, at least implicitly. The author asserts that real world operating rules follow this form and have evolved because they have been perceived as successful in the past. Thus, the modeling efforts focus on human behavior in much the same way that economic models focus on human behavior. This paper illustrates the above concepts with real world examples.

40 CFR 60.2665 - What if all the qualified operators are temporarily not accessible?

Code of Federal Regulations, 2014 CFR

2014-07-01

... (CONTINUED) AIR PROGRAMS (CONTINUED) STANDARDS OF PERFORMANCE FOR NEW STATIONARY SOURCES Emissions Guidelines and Compliance Times for Commercial and Industrial Solid Waste Incineration Units Model Rule-Operator... accessible and that you are resuming operation. Model Rule—Emission Limitations and Operating Limits ...

40 CFR 60.2665 - What if all the qualified operators are temporarily not accessible?

Code of Federal Regulations, 2013 CFR

2013-07-01

... (CONTINUED) AIR PROGRAMS (CONTINUED) STANDARDS OF PERFORMANCE FOR NEW STATIONARY SOURCES Emissions Guidelines and Compliance Times for Commercial and Industrial Solid Waste Incineration Units Model Rule-Operator... accessible and that you are resuming operation. Model Rule—Emission Limitations and Operating Limits ...

Estimating irrigation water demand using an improved method and optimizing reservoir operation for water supply and hydropower generation: a case study of the Xinfengjiang reservoir in southern China

USGS Publications Warehouse

Wu, Yiping; Chen, Ji

2013-01-01

The ever-increasing demand for water due to growth of population and socioeconomic development in the past several decades has posed a worldwide threat to water supply security and to the environmental health of rivers. This study aims to derive reservoir operating rules through establishing a multi-objective optimization model for the Xinfengjiang (XFJ) reservoir in the East River Basin in southern China to minimize water supply deficit and maximize hydropower generation. Additionally, to enhance the estimation of irrigation water demand from the downstream agricultural area of the XFJ reservoir, a conventional method for calculating crop water demand is improved using hydrological model simulation results. Although the optimal reservoir operating rules are derived for the XFJ reservoir with three priority scenarios (water supply only, hydropower generation only, and equal priority), the river environmental health is set as the basic demand no matter which scenario is adopted. The results show that the new rules derived under the three scenarios can improve the reservoir operation for both water supply and hydropower generation when comparing to the historical performance. Moreover, these alternative reservoir operating policies provide the flexibility for the reservoir authority to choose the most appropriate one. Although changing the current operating rules may influence its hydropower-oriented functions, the new rules can be significant to cope with the increasingly prominent water shortage and degradation in the aquatic environment. Overall, our results and methods (improved estimation of irrigation water demand and formulation of the reservoir optimization model) can be useful for local watershed managers and valuable for other researchers worldwide.

Complexity, Training Paradigm Design, and the Contribution of Memory Subsystems to Grammar Learning

PubMed Central

Ettlinger, Marc; Wong, Patrick C. M.

2016-01-01

Although there is variability in nonnative grammar learning outcomes, the contributions of training paradigm design and memory subsystems are not well understood. To examine this, we presented learners with an artificial grammar that formed words via simple and complex morphophonological rules. Across three experiments, we manipulated training paradigm design and measured subjects' declarative, procedural, and working memory subsystems. Experiment 1 demonstrated that passive, exposure-based training boosted learning of both simple and complex grammatical rules, relative to no training. Additionally, procedural memory correlated with simple rule learning, whereas declarative memory correlated with complex rule learning. Experiment 2 showed that presenting corrective feedback during the test phase did not improve learning. Experiment 3 revealed that structuring the order of training so that subjects are first exposed to the simple rule and then the complex improved learning. The cumulative findings shed light on the contributions of grammatical complexity, training paradigm design, and domain-general memory subsystems in determining grammar learning success. PMID:27391085

Numerical Simulation of Nonperiodic Rail Operation Diagram Characteristics

PubMed Central

Qian, Yongsheng; Wang, Bingbing; Zeng, Junwei; Wang, Xin

2014-01-01

This paper succeeded in utilizing cellular automata (CA) model to simulate the process of the train operation under the four-aspect color light system and getting the nonperiodic diagram of the mixed passenger and freight tracks. Generally speaking, the concerned models could simulate well the situation of wagon in preventing trains from colliding when parking and restarting and of the real-time changes the situation of train speeds and displacement and get hold of the current train states in their departures and arrivals. Finally the model gets the train diagram that simulates the train operation in different ratios of the van and analyzes some parameter characters in the process of train running, such as time, speed, through capacity, interval departing time, and departing numbers. PMID:25435863

Enhancing water supply through reservoir reoperation

NASA Astrophysics Data System (ADS)

Rajagopal, S.; Sterle, K. M.; Jose, L.; Coors, S.; Pohll, G.; Singletary, L.

2017-12-01

Snowmelt is a significant contributor to water supply in western U.S. which is stored in reservoirs for use during peak summer demand. The reservoirs were built to satisfy multiple objectives, but primarily to either enhance water supply and/or for flood mitigation. The operating rules for these water supply reservoirs are based on historical assumptions of stationarity of climate, assuming peak snowmelt occurs after April 1 and hence have to let water pass through if it arrived earlier. Using the Truckee River which originates in the eastern Sierra Nevada, has seven reservoirs and is shared between California and Nevada as an example, we show enhanced water storage by altering reservoir operating rules. These results are based on a coupled hydrology (Ground-Surface water Flow, GSFLOW) and water management model (RIverware) developed for the river system. All the reservoirs in the system benefit from altering the reservoir rules, but some benefit more than others. Prosser Creek reservoir for example, historically averaged 76% of capacity, which was lowered to 46% of capacity in the future as climate warms and shifts snowmelt to earlier days of the year. This reduction in storage can be mitigated by altering the reservoir operation rules and the reservoir storage increases to 64-76% of capacity. There are limitations to altering operating rules as reservoirs operated primarily for flood control are required to maintain lower storage to absorb a flood pulse, yet using modeling we show that there are water supply benefits to adopting a more flexible rules of operation. In the future, due to changing climate we anticipate the reservoirs in the western U.S. which were typically capturing spring- summer snowmelt will have to be managed more actively as the water stored in the snowpack becomes more variable. This study presents a framework for understanding, modeling and quantifying the consequences of such a shift in hydrology and water management.

14 CFR 125.296 - Training, testing, and checking conducted by training centers: Special rules.

Code of Federal Regulations, 2010 CFR

2010-01-01

... AIRCRAFT Flight Crewmember Requirements § 125.296 Training, testing, and checking conducted by training centers: Special rules. A crewmember who has successfully completed training, testing, or checking in... 14 Aeronautics and Space 3 2010-01-01 2010-01-01 false Training, testing, and checking conducted...

14 CFR 125.296 - Training, testing, and checking conducted by training centers: Special rules.

Code of Federal Regulations, 2012 CFR

2012-01-01

... AIRCRAFT Flight Crewmember Requirements § 125.296 Training, testing, and checking conducted by training centers: Special rules. A crewmember who has successfully completed training, testing, or checking in... 14 Aeronautics and Space 3 2012-01-01 2012-01-01 false Training, testing, and checking conducted...

14 CFR 125.296 - Training, testing, and checking conducted by training centers: Special rules.

Code of Federal Regulations, 2011 CFR

2011-01-01

... AIRCRAFT Flight Crewmember Requirements § 125.296 Training, testing, and checking conducted by training centers: Special rules. A crewmember who has successfully completed training, testing, or checking in... 14 Aeronautics and Space 3 2011-01-01 2011-01-01 false Training, testing, and checking conducted...

14 CFR 125.296 - Training, testing, and checking conducted by training centers: Special rules.

Code of Federal Regulations, 2014 CFR

2014-01-01

... AIRCRAFT Flight Crewmember Requirements § 125.296 Training, testing, and checking conducted by training centers: Special rules. A crewmember who has successfully completed training, testing, or checking in... 14 Aeronautics and Space 3 2014-01-01 2014-01-01 false Training, testing, and checking conducted...

14 CFR 125.296 - Training, testing, and checking conducted by training centers: Special rules.

Code of Federal Regulations, 2013 CFR

2013-01-01

... AIRCRAFT Flight Crewmember Requirements § 125.296 Training, testing, and checking conducted by training centers: Special rules. A crewmember who has successfully completed training, testing, or checking in... 14 Aeronautics and Space 3 2013-01-01 2013-01-01 false Training, testing, and checking conducted...

Analysis of SWO Fundamentals Exam Scores

DTIC Science & Technology

2011-03-01

24 h. Department ..............................................................................25 i. Class Year...the-Job Training OOD U /W Officer of the Deck Underway OOM Order of Merit OPTEMPO Operational Tempo ROR Rules of the Road SWO Surface Warfare...included a series of tests for each segment. Following attainment of Officer of the Deck Underway (OOD U /W) and upon their Commanding Officer’s (COs

A Computer Program You Can Use: Edging and Trimmer Trainer

Treesearch

Philip A. Araman; D. Earl Kline; Matthew F. Winn

1996-01-01

We present a computerized training tool designed to help hardwood sawmill edger and trim saw operators improve their processing performance. It can also be used by managers to understand the affects of processing decisions such as limiting wane beyond standard grading rule restrictions. The program helps users understand the relationships between lumber grade, surface...

An improved cellular automata model for train operation simulation with dynamic acceleration

NASA Astrophysics Data System (ADS)

Li, Wen-Jun; Nie, Lei

2018-03-01

Urban rail transit plays an important role in the urban public traffic because of its advantages of fast speed, large transport capacity, high safety, reliability and low pollution. This study proposes an improved cellular automaton (CA) model by considering the dynamic characteristic of the train acceleration to analyze the energy consumption and train running time. Constructing an effective model for calculating energy consumption to aid train operation improvement is the basis for studying and analyzing energy-saving measures for urban rail transit system operation.

Operator Training: Who Is Responsible?

ERIC Educational Resources Information Center

Wubbena, Robert L.

1979-01-01

Summarized are the findings of a study to identify and correct water pollution control operator training deficiencies. Several models are presented to aid in developing a coordinated delivery system for operator training and certification. (CS)

Improved GART neural network model for pattern classification and rule extraction with application to power systems.

PubMed

Yap, Keem Siah; Lim, Chee Peng; Au, Mau Teng

2011-12-01

Generalized adaptive resonance theory (GART) is a neural network model that is capable of online learning and is effective in tackling pattern classification tasks. In this paper, we propose an improved GART model (IGART), and demonstrate its applicability to power systems. IGART enhances the dynamics of GART in several aspects, which include the use of the Laplacian likelihood function, a new vigilance function, a new match-tracking mechanism, an ordering algorithm for determining the sequence of training data, and a rule extraction capability to elicit if-then rules from the network. To assess the effectiveness of IGART and to compare its performances with those from other methods, three datasets that are related to power systems are employed. The experimental results demonstrate the usefulness of IGART with the rule extraction capability in undertaking classification problems in power systems engineering.

Logistics of Trainsets Creation with the Use of Simulation Models

NASA Astrophysics Data System (ADS)

Sedláček, Michal; Pavelka, Hynek

2016-12-01

This paper focuses on rail transport in following the train formation operational processes problem using computer simulations. The problem has been solved using SIMUL8 and applied to specific train formation station in the Czech Republic. The paper describes a proposal simulation model of the train formation work. Experimental modeling with an assessment of achievements and design solution for optimizing of the train formation operational process is also presented.

Phonological Concept Learning.

PubMed

Moreton, Elliott; Pater, Joe; Pertsova, Katya

2017-01-01

Linguistic and non-linguistic pattern learning have been studied separately, but we argue for a comparative approach. Analogous inductive problems arise in phonological and visual pattern learning. Evidence from three experiments shows that human learners can solve them in analogous ways, and that human performance in both cases can be captured by the same models. We test GMECCS (Gradual Maximum Entropy with a Conjunctive Constraint Schema), an implementation of the Configural Cue Model (Gluck & Bower, ) in a Maximum Entropy phonotactic-learning framework (Goldwater & Johnson, ; Hayes & Wilson, ) with a single free parameter, against the alternative hypothesis that learners seek featurally simple algebraic rules ("rule-seeking"). We study the full typology of patterns introduced by Shepard, Hovland, and Jenkins () ("SHJ"), instantiated as both phonotactic patterns and visual analogs, using unsupervised training. Unlike SHJ, Experiments 1 and 2 found that both phonotactic and visual patterns that depended on fewer features could be more difficult than those that depended on more features, as predicted by GMECCS but not by rule-seeking. GMECCS also correctly predicted performance differences between stimulus subclasses within each pattern. A third experiment tried supervised training (which can facilitate rule-seeking in visual learning) to elicit simple rule-seeking phonotactic learning, but cue-based behavior persisted. We conclude that similar cue-based cognitive processes are available for phonological and visual concept learning, and hence that studying either kind of learning can lead to significant insights about the other. Copyright © 2015 Cognitive Science Society, Inc.

Train Control and Operations

DOT National Transportation Integrated Search

1971-06-01

ATO (automatic train operation) and ATC (automatic train control) systems are evaluated relative to available technology and cost-benefit. The technological evaluation shows that suitable mathematical models of the dynamics of long trains are require...

14 CFR 91.161 - Special awareness training required for pilots flying under visual flight rules within a 60...

Code of Federal Regulations, 2010 CFR

2010-01-01

... pilots flying under visual flight rules within a 60-nautical mile radius of the Washington, DC VOR/DME... Rules Visual Flight Rules § 91.161 Special awareness training required for pilots flying under visual...-nautical mile radius of the Washington, DC VOR/DME under visual flight rules (VFR). Except as provided...

Rule-based simulation models

NASA Technical Reports Server (NTRS)

Nieten, Joseph L.; Seraphine, Kathleen M.

1991-01-01

Procedural modeling systems, rule based modeling systems, and a method for converting a procedural model to a rule based model are described. Simulation models are used to represent real time engineering systems. A real time system can be represented by a set of equations or functions connected so that they perform in the same manner as the actual system. Most modeling system languages are based on FORTRAN or some other procedural language. Therefore, they must be enhanced with a reaction capability. Rule based systems are reactive by definition. Once the engineering system has been decomposed into a set of calculations using only basic algebraic unary operations, a knowledge network of calculations and functions can be constructed. The knowledge network required by a rule based system can be generated by a knowledge acquisition tool or a source level compiler. The compiler would take an existing model source file, a syntax template, and a symbol table and generate the knowledge network. Thus, existing procedural models can be translated and executed by a rule based system. Neural models can be provide the high capacity data manipulation required by the most complex real time models.

Belief Function Based Decision Fusion for Decentralized Target Classification in Wireless Sensor Networks

PubMed Central

Zhang, Wenyu; Zhang, Zhenjiang

2015-01-01

Decision fusion in sensor networks enables sensors to improve classification accuracy while reducing the energy consumption and bandwidth demand for data transmission. In this paper, we focus on the decentralized multi-class classification fusion problem in wireless sensor networks (WSNs) and a new simple but effective decision fusion rule based on belief function theory is proposed. Unlike existing belief function based decision fusion schemes, the proposed approach is compatible with any type of classifier because the basic belief assignments (BBAs) of each sensor are constructed on the basis of the classifier’s training output confusion matrix and real-time observations. We also derive explicit global BBA in the fusion center under Dempster’s combinational rule, making the decision making operation in the fusion center greatly simplified. Also, sending the whole BBA structure to the fusion center is avoided. Experimental results demonstrate that the proposed fusion rule has better performance in fusion accuracy compared with the naïve Bayes rule and weighted majority voting rule. PMID:26295399

Operating room scheduling using hybrid clustering priority rule and genetic algorithm

NASA Astrophysics Data System (ADS)

Santoso, Linda Wahyuni; Sinawan, Aisyah Ashrinawati; Wijaya, Andi Rahadiyan; Sudiarso, Andi; Masruroh, Nur Aini; Herliansyah, Muhammad Kusumawan

2017-11-01

Operating room is a bottleneck resource in most hospitals so that operating room scheduling system will influence the whole performance of the hospitals. This research develops a mathematical model of operating room scheduling for elective patients which considers patient priority with limit number of surgeons, operating rooms, and nurse team. Clustering analysis was conducted to the data of surgery durations using hierarchical and non-hierarchical methods. The priority rule of each resulting cluster was determined using Shortest Processing Time method. Genetic Algorithm was used to generate daily operating room schedule which resulted in the lowest values of patient waiting time and nurse overtime. The computational results show that this proposed model reduced patient waiting time by approximately 32.22% and nurse overtime by approximately 32.74% when compared to actual schedule.

Assessing Continuous Operator Workload With a Hybrid Scaffolded Neuroergonomic Modeling Approach.

PubMed

Borghetti, Brett J; Giametta, Joseph J; Rusnock, Christina F

2017-02-01

We aimed to predict operator workload from neurological data using statistical learning methods to fit neurological-to-state-assessment models. Adaptive systems require real-time mental workload assessment to perform dynamic task allocations or operator augmentation as workload issues arise. Neuroergonomic measures have great potential for informing adaptive systems, and we combine these measures with models of task demand as well as information about critical events and performance to clarify the inherent ambiguity of interpretation. We use machine learning algorithms on electroencephalogram (EEG) input to infer operator workload based upon Improved Performance Research Integration Tool workload model estimates. Cross-participant models predict workload of other participants, statistically distinguishing between 62% of the workload changes. Machine learning models trained from Monte Carlo resampled workload profiles can be used in place of deterministic workload profiles for cross-participant modeling without incurring a significant decrease in machine learning model performance, suggesting that stochastic models can be used when limited training data are available. We employed a novel temporary scaffold of simulation-generated workload profile truth data during the model-fitting process. A continuous workload profile serves as the target to train our statistical machine learning models. Once trained, the workload profile scaffolding is removed and the trained model is used directly on neurophysiological data in future operator state assessments. These modeling techniques demonstrate how to use neuroergonomic methods to develop operator state assessments, which can be employed in adaptive systems.

Precise-spike-driven synaptic plasticity: learning hetero-association of spatiotemporal spike patterns.

PubMed

Yu, Qiang; Tang, Huajin; Tan, Kay Chen; Li, Haizhou

2013-01-01

A new learning rule (Precise-Spike-Driven (PSD) Synaptic Plasticity) is proposed for processing and memorizing spatiotemporal patterns. PSD is a supervised learning rule that is analytically derived from the traditional Widrow-Hoff rule and can be used to train neurons to associate an input spatiotemporal spike pattern with a desired spike train. Synaptic adaptation is driven by the error between the desired and the actual output spikes, with positive errors causing long-term potentiation and negative errors causing long-term depression. The amount of modification is proportional to an eligibility trace that is triggered by afferent spikes. The PSD rule is both computationally efficient and biologically plausible. The properties of this learning rule are investigated extensively through experimental simulations, including its learning performance, its generality to different neuron models, its robustness against noisy conditions, its memory capacity, and the effects of its learning parameters. Experimental results show that the PSD rule is capable of spatiotemporal pattern classification, and can even outperform a well studied benchmark algorithm with the proposed relative confidence criterion. The PSD rule is further validated on a practical example of an optical character recognition problem. The results again show that it can achieve a good recognition performance with a proper encoding. Finally, a detailed discussion is provided about the PSD rule and several related algorithms including tempotron, SPAN, Chronotron and ReSuMe.

Precise-Spike-Driven Synaptic Plasticity: Learning Hetero-Association of Spatiotemporal Spike Patterns

PubMed Central

Yu, Qiang; Tang, Huajin; Tan, Kay Chen; Li, Haizhou

2013-01-01

A new learning rule (Precise-Spike-Driven (PSD) Synaptic Plasticity) is proposed for processing and memorizing spatiotemporal patterns. PSD is a supervised learning rule that is analytically derived from the traditional Widrow-Hoff rule and can be used to train neurons to associate an input spatiotemporal spike pattern with a desired spike train. Synaptic adaptation is driven by the error between the desired and the actual output spikes, with positive errors causing long-term potentiation and negative errors causing long-term depression. The amount of modification is proportional to an eligibility trace that is triggered by afferent spikes. The PSD rule is both computationally efficient and biologically plausible. The properties of this learning rule are investigated extensively through experimental simulations, including its learning performance, its generality to different neuron models, its robustness against noisy conditions, its memory capacity, and the effects of its learning parameters. Experimental results show that the PSD rule is capable of spatiotemporal pattern classification, and can even outperform a well studied benchmark algorithm with the proposed relative confidence criterion. The PSD rule is further validated on a practical example of an optical character recognition problem. The results again show that it can achieve a good recognition performance with a proper encoding. Finally, a detailed discussion is provided about the PSD rule and several related algorithms including tempotron, SPAN, Chronotron and ReSuMe. PMID:24223789

A Study on Contingency Learning in Introductory Physics Concepts

NASA Astrophysics Data System (ADS)

Scaife, Thomas M.

Instructors of physics often use examples to illustrate new or complex physical concepts to students. For any particular concept, there are an infinite number of examples, thus presenting instructors with a difficult question whenever they wish to use one in their teaching: which example will most effectively illustrate the concept so that student learning is maximized? The choice is typically made by an intuitive assumption about which exact example will result in the most lucid illustration and the greatest student improvement. By questioning 583 students in four experiments, I examined a more principled approach to example selection. By controlling the manner in which physical dimensions vary, the parameter space of each concept can be divided into a discrete number of example categories. The effects of training with members of each of category was explored in two different physical contexts: projectile motion and torque. In the first context, students were shown two trajectories and asked to determine which represented the longer time of flight. Height, range, and time of flight were the physical dimensions that were used to categorize the examples. In the second context, students were shown a balance-scale with loads of differing masses placed at differing positions along either side of the balance-arm. Mass, lever-arm length, and torque were the physical dimensions used to categorize these examples. For both contexts, examples were chosen so that one or two independent dimensions were varied. After receiving training with examples from specific categories, students were tested with questions from all question categories. Successful training or instruction can be measured either as producing correct, expert-like behavior (as observed through answers to the questions) or as explicitly instilling an understanding of the underlying rule that governs a physical phenomenon. A student's behavior might not be consistent with their explicit rule, so following the investigation of their behavior, students were asked what rule they used when answering questions. Although the self-reported rules might not be congruent with their behavior, training with specific examples might affect how students explicitly think about physics problems. In addition to exploring the effectiveness of various training examples, the results were also compared to a cognitive theory of causality: the contingency model. Physical concepts can often be expressed in terms of causal relations (e.g., a net force causes an object to accelerate), and a large body of work has found that people make many decisions that are consistent with causal reasoning. The contingency model, in particular, explains how certain statistical regularities in the co-occurrence of two events can be interpreted by individuals as causal relations, and was chosen primarily because it of its robust results and simple, parsimonious form. The empirical results demonstrate that different categories of training examples did affect student answers differently. Furthermore, these effects were mostly consistent with the predictions made by the contingency model. When rule use was explored, the self-reported rules were consistent with contingency model predictions, but indicated that examples alone were insufficient to teach complex functional relationships between physical dimensions, such as torque.

Automated time activity classification based on global positioning system (GPS) tracking data

PubMed Central

2011-01-01

Background Air pollution epidemiological studies are increasingly using global positioning system (GPS) to collect time-location data because they offer continuous tracking, high temporal resolution, and minimum reporting burden for participants. However, substantial uncertainties in the processing and classifying of raw GPS data create challenges for reliably characterizing time activity patterns. We developed and evaluated models to classify people's major time activity patterns from continuous GPS tracking data. Methods We developed and evaluated two automated models to classify major time activity patterns (i.e., indoor, outdoor static, outdoor walking, and in-vehicle travel) based on GPS time activity data collected under free living conditions for 47 participants (N = 131 person-days) from the Harbor Communities Time Location Study (HCTLS) in 2008 and supplemental GPS data collected from three UC-Irvine research staff (N = 21 person-days) in 2010. Time activity patterns used for model development were manually classified by research staff using information from participant GPS recordings, activity logs, and follow-up interviews. We evaluated two models: (a) a rule-based model that developed user-defined rules based on time, speed, and spatial location, and (b) a random forest decision tree model. Results Indoor, outdoor static, outdoor walking and in-vehicle travel activities accounted for 82.7%, 6.1%, 3.2% and 7.2% of manually-classified time activities in the HCTLS dataset, respectively. The rule-based model classified indoor and in-vehicle travel periods reasonably well (Indoor: sensitivity > 91%, specificity > 80%, and precision > 96%; in-vehicle travel: sensitivity > 71%, specificity > 99%, and precision > 88%), but the performance was moderate for outdoor static and outdoor walking predictions. No striking differences in performance were observed between the rule-based and the random forest models. The random forest model was fast and easy to execute, but was likely less robust than the rule-based model under the condition of biased or poor quality training data. Conclusions Our models can successfully identify indoor and in-vehicle travel points from the raw GPS data, but challenges remain in developing models to distinguish outdoor static points and walking. Accurate training data are essential in developing reliable models in classifying time-activity patterns. PMID:22082316

Automated time activity classification based on global positioning system (GPS) tracking data.

PubMed

Wu, Jun; Jiang, Chengsheng; Houston, Douglas; Baker, Dean; Delfino, Ralph

2011-11-14

Air pollution epidemiological studies are increasingly using global positioning system (GPS) to collect time-location data because they offer continuous tracking, high temporal resolution, and minimum reporting burden for participants. However, substantial uncertainties in the processing and classifying of raw GPS data create challenges for reliably characterizing time activity patterns. We developed and evaluated models to classify people's major time activity patterns from continuous GPS tracking data. We developed and evaluated two automated models to classify major time activity patterns (i.e., indoor, outdoor static, outdoor walking, and in-vehicle travel) based on GPS time activity data collected under free living conditions for 47 participants (N = 131 person-days) from the Harbor Communities Time Location Study (HCTLS) in 2008 and supplemental GPS data collected from three UC-Irvine research staff (N = 21 person-days) in 2010. Time activity patterns used for model development were manually classified by research staff using information from participant GPS recordings, activity logs, and follow-up interviews. We evaluated two models: (a) a rule-based model that developed user-defined rules based on time, speed, and spatial location, and (b) a random forest decision tree model. Indoor, outdoor static, outdoor walking and in-vehicle travel activities accounted for 82.7%, 6.1%, 3.2% and 7.2% of manually-classified time activities in the HCTLS dataset, respectively. The rule-based model classified indoor and in-vehicle travel periods reasonably well (Indoor: sensitivity > 91%, specificity > 80%, and precision > 96%; in-vehicle travel: sensitivity > 71%, specificity > 99%, and precision > 88%), but the performance was moderate for outdoor static and outdoor walking predictions. No striking differences in performance were observed between the rule-based and the random forest models. The random forest model was fast and easy to execute, but was likely less robust than the rule-based model under the condition of biased or poor quality training data. Our models can successfully identify indoor and in-vehicle travel points from the raw GPS data, but challenges remain in developing models to distinguish outdoor static points and walking. Accurate training data are essential in developing reliable models in classifying time-activity patterns.

Aberrant learning in Parkinson's disease: A neurocomputational study on bradykinesia.

PubMed

Ursino, Mauro; Baston, Chiara

2018-05-22

Parkinson's disease (PD) is a neurodegenerative disorder characterized by a progressive decline in motor functions, such as bradykinesia, caused by the pathological denervation of nigrostriatal dopaminergic neurons within the basal ganglia (BG). It is acknowledged that dopamine (DA) directly affects the modulatory role of BG towards the cortex. However, a growing body of literature is suggesting that DA-induced aberrant synaptic plasticity could play a role in the core symptoms of PD, thus recalling for a "reconceptualization" of the pathophysiology. The aim of this work was to investigate DA-driven aberrant learning as a concurrent cause of bradykinesia, using a comprehensive, biologically inspired neurocomputational model of action selection in the BG. The model includes the three main pathways operating in the BG circuitry, that is the direct, indirect and hyperdirect pathways, and use a two-term Hebb rule to train synapses in the striatum, based on previous history of rewards and punishments. Levodopa pharmacodynamics is also incorporated. Through model simulations of the Alternate Finger Tapping motor task, we assessed the role of aberrant learning on bradykinesia. The results show that training under drug medication (levodopa) provides not only immediate but also delayed benefit lasting in time. Conversely, if performed in conditions of vanishing levodopa efficacy, training may result in dysfunctional corticostriatal synaptic plasticity, further worsening motor performances in PD subjects. This suggests that bradykinesia may result from the concurrent effects of low DA levels and dysfunctional plasticity and that training can be exploited in medicated subjects to improve levodopa treatment. © 2018 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

25 CFR 542.23 - What are the minimum internal control standards for surveillance for Tier A gaming operations?

Code of Federal Regulations, 2010 CFR

2010-04-01

... trained in the use of the equipment, knowledge of the games, and house rules. (f) Each camera required by... device, the game board, and the activities of the employees responsible for drawing, calling, and entering the balls drawn or numbers selected. (j) Card games. The surveillance system shall record the...

25 CFR 542.23 - What are the minimum internal control standards for surveillance for Tier A gaming operations?

Code of Federal Regulations, 2011 CFR

2011-04-01

... trained in the use of the equipment, knowledge of the games, and house rules. (f) Each camera required by... device, the game board, and the activities of the employees responsible for drawing, calling, and entering the balls drawn or numbers selected. (j) Card games. The surveillance system shall record the...

25 CFR 542.23 - What are the minimum internal control standards for surveillance for Tier A gaming operations?

Code of Federal Regulations, 2014 CFR

2014-04-01

... trained in the use of the equipment, knowledge of the games, and house rules. (f) Each camera required by... device, the game board, and the activities of the employees responsible for drawing, calling, and entering the balls drawn or numbers selected. (j) Card games. The surveillance system shall record the...

25 CFR 542.23 - What are the minimum internal control standards for surveillance for Tier A gaming operations?

Code of Federal Regulations, 2012 CFR

2012-04-01

... trained in the use of the equipment, knowledge of the games, and house rules. (f) Each camera required by... device, the game board, and the activities of the employees responsible for drawing, calling, and entering the balls drawn or numbers selected. (j) Card games. The surveillance system shall record the...

25 CFR 542.23 - What are the minimum internal control standards for surveillance for Tier A gaming operations?

Code of Federal Regulations, 2013 CFR

2013-04-01

... trained in the use of the equipment, knowledge of the games, and house rules. (f) Each camera required by... device, the game board, and the activities of the employees responsible for drawing, calling, and entering the balls drawn or numbers selected. (j) Card games. The surveillance system shall record the...

Environmental Compliance and Pollution Prevention Training Manual for Campus-Based Organizations--Operational and Facility Maintenance Personnel.

ERIC Educational Resources Information Center

New York State Dept. of Environmental Conservation, Albany.

This manual was designed to be used as part of the Workshop on Environmental Compliance and Pollution Prevention for campus-based facilities. It contains basic information on New York state and federal laws, rules, and regulations for protecting the environment. The information presented is a summary with emphasis on those items believed to be…

User's guide to UGRS: the Ultimate Grading and Remanufacturing System (version 5.0).

Treesearch

John Moody; Charles J. Gatchell; Elizabeth S. Walker; Powsiri Klinkhachorn

1998-01-01

The Ultimate Grading and Remanufacturing System (UGRS) is the latest generation of advanced computer programs for lumber grading. It is designed to be a training and research tool that allows grading of lumber according to 1998 NHLA rules and remanufacturing for maximum dollar value. A 32-bit application that runs under all Microsoft Windows operating systems, UGRS...

Optimization study on multiple train formation scheme of urban rail transit

NASA Astrophysics Data System (ADS)

Xia, Xiaomei; Ding, Yong; Wen, Xin

2018-05-01

The new organization method, represented by the mixed operation of multi-marshalling trains, can adapt to the characteristics of the uneven distribution of passenger flow, but the research on this aspect is still not perfect enough. This paper introduced the passenger sharing rate and congestion penalty coefficient with different train formations. On this basis, this paper established an optimization model with the minimum passenger cost and operation cost as objective, and operation frequency and passenger demand as constraint. The ideal point method is used to solve this model. Compared with the fixed marshalling operation model, the overall cost of this scheme saves 9.24% and 4.43% respectively. This result not only validates the validity of the model, but also illustrate the advantages of the multiple train formations scheme.

Short optical pulse generation at 40 GHz with a bulk electro-absorption modulator packaged device

NASA Astrophysics Data System (ADS)

Langlois, Patrick; Moore, Ronald; Prosyk, Kelvin; O'Keefe, Sean; Oosterom, Jill A.; Betty, Ian; Foster, Robert; Greenspan, Jonathan; Singh, Priti

2003-12-01

Short optical pulse generation at 40GHz and 1540nm wavelength is achieved using fully packaged bulk quaternary electro-absorption modulator modules. Experimental results obtained with broadband and narrowband optimized packaged modules are presented and compared against empirical model predictions. Pulse duty cycle, extinction ratio and chirp are studied as a function of sinusoidal drive voltage and detuning between operating wavelength and modulator absorption band edge. Design rules and performance trade-offs are discussed. Low-chirp pulses with a FWHM of ~12ps and sub-4ps at a rate of 40GHz are demonstrated. Optical time-domain demultiplexing of a 40GHz to a 10GHz pulse train is also demonstrated with better than 20dB extinction ratio.

Models Used by the Military Services to Develop Budgets for Activities Associated with Operational Readiness

DTIC Science & Technology

2012-02-01

Operating Tempo and Training ($19.0 billion) Facilities ($18.1 billion) Maintenance ($11.3 billion) Not Modeled ($26.3 billion) Miscellaneous...Adebayo Adedeji, Daniel Frisk, and Derek Trunkey of CBO’s National Secur supervision of Matthew Goldberg and David Mosher. CBO staff members Elizabeth...rs M ce F ciliti e Op nt M aintng Direct Costs for Unit Operating Tempo and Training ng Indirect Costs for Unit Operating Tempo and Training odel

Validation of the train energy and dynamics simulator (TEDS).

DOT National Transportation Integrated Search

2015-01-01

FRA has developed Train Energy and Dynamics Simulator (TEDS) based upon a longitudinal train dynamics and operations : simulation model which allows users to conduct safety and risk evaluations, incident investigations, studies of train operations, :...

High Resolution Map of Water Supply and Demand for North East United States

NASA Astrophysics Data System (ADS)

Ehsani, N.; Vorosmarty, C. J.; Fekete, B. M.

2012-12-01

Accurate estimates of water supply and demand are crucial elements in water resources management and modeling. As part of our NSF-funded EaSM effort to build a Northeast Regional Earth System Model (NE-RESM) as a framework to improve our understanding and capacity to forecast the implications of planning decisions on the region's environment, ecosystem services, energy and economic systems through the 21st century, we are producing a high resolution map (3' x 3' lat/long) of estimated water supply and use for the north east region of United States. Focusing on water demand, results from this study enables us to quantify how demand sources affect the hydrology and thermal-chemical water pollution across the region. In an attempt to generate this 3-minute resolution map in which each grid cell has a specific estimated monthly domestic, agriculture, thermoelectric and industrial water use. Estimated Use of Water in the United States in 2005 (Kenny et al., 2009) is being coupled to high resolution land cover and land use, irrigation, power plant and population data sets. In addition to water demands, we tried to improve estimates of water supply from the WBM model by improving the way it controls discharge from reservoirs. Reservoirs are key characteristics of the modern hydrologic system, with a particular impact on altering the natural stream flow, thermal characteristics, and biogeochemical fluxes of rivers. Depending on dam characteristics, watershed characteristics and the purpose of building a dam, each reservoir has a specific optimum operating rule. It means that literally 84,000 dams in the National Inventory of Dams potentially follow 84,000 different sets of rules for storing and releasing water which must somehow be accounted for in our modeling exercise. In reality, there is no comprehensive observational dataset depicting these operating rules. Thus, we will simulate these rules. Our perspective is not to find the optimum operating rule per se but to find composite behaviors that are consistent with the nominal use of each reservoir and their impacts on observed stream gage behaviors. We decided to use Artificial Neural Networks (ANN) in this context. We see as an important advantage of ANN, its ability to detect complex nonlinear relations between input and output data, which makes it a valuable tool for time series prediction and fitness approximation. High quality, measured parameters are available throughout the United States; thus, we are able to use measured data to train and test ANN and operate reservoirs in a way that simulates real world reservoirs' behavior more accurately. By using economics, population, land cover and climate change estimates for 21st century, we are seeking to forecast in a systematic manner all major facets of future water supply and use in north east United States which will enable us to identify locations prone to water stress due to urban and domestic or agriculture and irrigation water demand, quantify change in chemical and thermal pollution of rivers and availability of water for power generation.

The value of EHR-based assessment of physician competency: An investigative effort with internal medicine physicians.

PubMed

Venta, Kimberly; Baker, Erin; Fidopiastis, Cali; Stanney, Kay

2017-12-01

The purpose of this study was to investigate the potential of developing an EHR-based model of physician competency, named the Skill Deficiency Evaluation Toolkit for Eliminating Competency-loss Trends (Skill-DETECT), which presents the opportunity to use EHR-based models to inform selection of Continued Medical Education (CME) opportunities specifically targeted at maintaining proficiency. The IBM Explorys platform provided outpatient Electronic Health Records (EHRs) representing 76 physicians with over 5000 patients combined. These data were used to develop the Skill-DETECT model, a predictive hybrid model composed of a rule-based model, logistic regression model, and a thresholding model, which predicts cognitive clinical skill deficiencies in internal medicine physicians. A three-phase approach was then used to statistically validate the model performance. Subject Matter Expert (SME) panel reviews resulted in a 100% overall approval rate of the rule based model. Area under the receiver-operating characteristic curves calculated for each logistic regression curve resulted in values between 0.76 and 0.92, which indicated exceptional performance. Normality, skewness, and kurtosis were determined and confirmed that the distribution of values output from the thresholding model were unimodal and peaked, which confirmed effectiveness and generalizability. The validation has confirmed that the Skill-DETECT model has a strong ability to evaluate EHR data and support the identification of internal medicine cognitive clinical skills that are deficient or are of higher likelihood of becoming deficient and thus require remediation, which will allow both physician and medical organizations to fine tune training efforts. Copyright © 2017 Elsevier B.V. All rights reserved.

Bayesian population decoding of spiking neurons.

PubMed

Gerwinn, Sebastian; Macke, Jakob; Bethge, Matthias

2009-01-01

The timing of action potentials in spiking neurons depends on the temporal dynamics of their inputs and contains information about temporal fluctuations in the stimulus. Leaky integrate-and-fire neurons constitute a popular class of encoding models, in which spike times depend directly on the temporal structure of the inputs. However, optimal decoding rules for these models have only been studied explicitly in the noiseless case. Here, we study decoding rules for probabilistic inference of a continuous stimulus from the spike times of a population of leaky integrate-and-fire neurons with threshold noise. We derive three algorithms for approximating the posterior distribution over stimuli as a function of the observed spike trains. In addition to a reconstruction of the stimulus we thus obtain an estimate of the uncertainty as well. Furthermore, we derive a 'spike-by-spike' online decoding scheme that recursively updates the posterior with the arrival of each new spike. We use these decoding rules to reconstruct time-varying stimuli represented by a Gaussian process from spike trains of single neurons as well as neural populations.

Validation of Mission Plans Through Simulation

NASA Astrophysics Data System (ADS)

St-Pierre, J.; Melanson, P.; Brunet, C.; Crabtree, D.

2002-01-01

The purpose of a spacecraft mission planning system is to automatically generate safe and optimized mission plans for a single spacecraft, or more functioning in unison. The system verifies user input syntax, conformance to commanding constraints, absence of duty cycle violations, timing conflicts, state conflicts, etc. Present day constraint-based systems with state-based predictive models use verification rules derived from expert knowledge. A familiar solution found in Mission Operations Centers, is to complement the planning system with a high fidelity spacecraft simulator. Often a dedicated workstation, the simulator is frequently used for operator training and procedure validation, and may be interfaced to actual control stations with command and telemetry links. While there are distinct advantages to having a planning system offer realistic operator training using the actual flight control console, physical verification of data transfer across layers and procedure validation, experience has revealed some drawbacks and inefficiencies in ground segment operations: With these considerations, two simulation-based mission plan validation projects are under way at the Canadian Space Agency (CSA): RVMP and ViSION. The tools proposed in these projects will automatically run scenarios and provide execution reports to operations planning personnel, prior to actual command upload. This can provide an important safeguard for system or human errors that can only be detected with high fidelity, interdependent spacecraft models running concurrently. The core element common to these projects is a spacecraft simulator, built with off-the- shelf components such as CAE's Real-Time Object-Based Simulation Environment (ROSE) technology, MathWork's MATLAB/Simulink, and Analytical Graphics' Satellite Tool Kit (STK). To complement these tools, additional components were developed, such as an emulated Spacecraft Test and Operations Language (STOL) interpreter and CCSDS TM/TC encoders and decoders. This paper discusses the use of simulation in the context of space mission planning, describes the projects under way and proposes additional venues of investigation and development.

Intelligent System Development Using a Rough Sets Methodology

NASA Technical Reports Server (NTRS)

Anderson, Gray T.; Shelton, Robert O.

1997-01-01

The purpose of this research was to examine the potential of the rough sets technique for developing intelligent models of complex systems from limited information. Rough sets a simple but promising technology to extract easily understood rules from data. The rough set methodology has been shown to perform well when used with a large set of exemplars, but its performance with sparse data sets is less certain. The difficulty is that rules will be developed based on just a few examples, each of which might have a large amount of noise associated with them. The question then becomes, what is the probability of a useful rule being developed from such limited information? One nice feature of rough sets is that in unusual situations, the technique can give an answer of 'I don't know'. That is, if a case arises that is different from the cases the rough set rules were developed on, the methodology can recognize this and alert human operators of it. It can also be trained to do this when the desired action is unknown because conflicting examples apply to the same set of inputs. This summer's project was to look at combining rough set theory with statistical theory to develop confidence limits in rules developed by rough sets. Often it is important not to make a certain type of mistake (e.g., false positives or false negatives), so the rules must be biased toward preventing a catastrophic error, rather than giving the most likely course of action. A method to determine the best course of action in the light of such constraints was examined. The resulting technique was tested with files containing electrical power line 'signatures' from the space shuttle and with decompression sickness data.

Use of the computational-informational web-GIS system for the development of climatology students' skills in modeling and understanding climate change

NASA Astrophysics Data System (ADS)

Gordova, Yulia; Martynova, Yulia; Shulgina, Tamara

2015-04-01

The current situation with the training of specialists in environmental sciences is complicated by the fact that the very scientific field is experiencing a period of rapid development. Global change has caused the development of measurement techniques and modeling of environmental characteristics, accompanied by the expansion of the conceptual and mathematical apparatus. Understanding and forecasting processes in the Earth system requires extensive use of mathematical modeling and advanced computing technologies. As a rule, available training programs in the environmental sciences disciplines do not have time to adapt to such rapid changes in the domain content. As a result, graduates of faculties do not understand processes and mechanisms of the global change, have only superficial knowledge of mathematical modeling of processes in the environment. They do not have the required skills in numerical modeling, data processing and analysis of observations and computation outputs and are not prepared to work with the meteorological data. For adequate training of future specialists in environmental sciences we propose the following approach, which reflects the new "research" paradigm in education. We believe that the training of such specialists should be done not in an artificial learning environment, but based on actual operating information-computational systems used in environment studies, in the so-called virtual research environment via development of virtual research and learning laboratories. In the report the results of the use of computational-informational web-GIS system "Climate" (http://climate.scert.ru/) as a prototype of such laboratory are discussed. The approach is realized at Tomsk State University to prepare bachelors in meteorology. Student survey shows that their knowledge has become deeper and more systemic after undergoing training in virtual learning laboratory. The scientific team plans to assist any educators to utilize the system in earth science education. This work is partially supported by SB RAS project VIII.80.2.1, RFBR grants 13-05-12034 and 14-05-00502.

On the applicability of STDP-based learning mechanisms to spiking neuron network models

NASA Astrophysics Data System (ADS)

Sboev, A.; Vlasov, D.; Serenko, A.; Rybka, R.; Moloshnikov, I.

2016-11-01

The ways to creating practically effective method for spiking neuron networks learning, that would be appropriate for implementing in neuromorphic hardware and at the same time based on the biologically plausible plasticity rules, namely, on STDP, are discussed. The influence of the amount of correlation between input and output spike trains on the learnability by different STDP rules is evaluated. A usability of alternative combined learning schemes, involving artificial and spiking neuron models is demonstrated on the iris benchmark task and on the practical task of gender recognition.

Optimal Government Subsidies to Universities in the Face of Tuition and Enrollment Constraints

ERIC Educational Resources Information Center

Easton, Stephen T.; Rockerbie, Duane W.

2008-01-01

This paper develops a simple static model of an imperfectly competitive university operating under government-imposed constraints on the ability to raise tuition fees and increase enrollments. The model has particular applicability to Canadian universities. Assuming an average cost pricing rule, rules for adequate government subsidies (operating…

Symmetry rules for the indirect nuclear spin-spin coupling tensor revisited

NASA Astrophysics Data System (ADS)

Buckingham, A. D.; Pyykkö, P.; Robert, J. B.; Wiesenfeld, L.

The symmetry rules of Buckingham and Love (1970), relating the number of independent components of the indirect spin-spin coupling tensor J to the symmetry of the nuclear sites, are shown to require modification if the two nuclei are exchanged by a symmetry operation. In that case, the anti-symmetric part of J does not transform as a second-rank polar tensor under symmetry operations that interchange the coupled nuclei and may be called an anti-tensor. New rules are derived and illustrated by simple molecular models.

Self-organization of head-centered visual responses under ecological training conditions.

PubMed

Mender, Bedeho M W; Stringer, Simon M

2014-01-01

We have studied the development of head-centered visual responses in an unsupervised self-organizing neural network model which was trained under ecological training conditions. Four independent spatio-temporal characteristics of the training stimuli were explored to investigate the feasibility of the self-organization under more ecological conditions. First, the number of head-centered visual training locations was varied over a broad range. Model performance improved as the number of training locations approached the continuous sampling of head-centered space. Second, the model depended on periods of time where visual targets remained stationary in head-centered space while it performed saccades around the scene, and the severity of this constraint was explored by introducing increasing levels of random eye movement and stimulus dynamics. Model performance was robust over a range of randomization. Third, the model was trained on visual scenes where multiple simultaneous targets where always visible. Model self-organization was successful, despite never being exposed to a visual target in isolation. Fourth, the duration of fixations during training were made stochastic. With suitable changes to the learning rule, it self-organized successfully. These findings suggest that the fundamental learning mechanism upon which the model rests is robust to the many forms of stimulus variability under ecological training conditions.

Developing an Intelligent Computer-Aided Trainer

NASA Technical Reports Server (NTRS)

Hua, Grace

1990-01-01

The Payload-assist module Deploys/Intelligent Computer-Aided Training (PD/ICAT) system was developed as a prototype for intelligent tutoring systems with the intention of seeing PD/ICAT evolve and produce a general ICAT architecture and development environment that can be adapted by a wide variety of training tasks. The proposed architecture is composed of a user interface, a domain expert, a training session manager, a trainee model and a training scenario generator. The PD/ICAT prototype was developed in the LISP environment. Although it has been well received by its peers and users, it could not be delivered toe its end users for practical use because of specific hardware and software constraints. To facilitate delivery of PD/ICAT to its users and to prepare for a more widely accepted development and delivery environment for future ICAT applications, we have ported this training system to a UNIX workstation and adopted use of a conventional language, C, and a C-based rule-based language, CLIPS. A rapid conversion of the PD/ICAT expert system to CLIPS was possible because the knowledge was basically represented as a forward chaining rule base. The resulting CLIPS rule base has been tested successfully in other ICATs as well. Therefore, the porting effort has proven to be a positive step toward our ultimate goal of building a general purpose ICAT development environment.

A Study of Hospital Admission Rules During Pediatric Residency Training.

ERIC Educational Resources Information Center

Ferguson, Jane; Alpert, Joel J.

1980-01-01

A survey of U.S. pediatric training programs to determine the role of rules in the hospital admission of pediatric patients is reported. The results support the hypothesis that rules are a widely used teaching tool. The rules relate to such factors as fevers, age, specific diseases, administrative concerns, head traumas, and poisonings. (JMD)

Logical-rule models of classification response times: a synthesis of mental-architecture, random-walk, and decision-bound approaches.

PubMed

Fific, Mario; Little, Daniel R; Nosofsky, Robert M

2010-04-01

We formalize and provide tests of a set of logical-rule models for predicting perceptual classification response times (RTs) and choice probabilities. The models are developed by synthesizing mental-architecture, random-walk, and decision-bound approaches. According to the models, people make independent decisions about the locations of stimuli along a set of component dimensions. Those independent decisions are then combined via logical rules to determine the overall categorization response. The time course of the independent decisions is modeled via random-walk processes operating along individual dimensions. Alternative mental architectures are used as mechanisms for combining the independent decisions to implement the logical rules. We derive fundamental qualitative contrasts for distinguishing among the predictions of the rule models and major alternative models of classification RT. We also use the models to predict detailed RT-distribution data associated with individual stimuli in tasks of speeded perceptual classification. PsycINFO Database Record (c) 2010 APA, all rights reserved.

LIDAR Point Cloud Data Extraction and Establishment of 3D Modeling of Buildings

NASA Astrophysics Data System (ADS)

Zhang, Yujuan; Li, Xiuhai; Wang, Qiang; Liu, Jiang; Liang, Xin; Li, Dan; Ni, Chundi; Liu, Yan

2018-01-01

This paper takes the method of Shepard’s to deal with the original LIDAR point clouds data, and generate regular grid data DSM, filters the ground point cloud and non ground point cloud through double least square method, and obtains the rules of DSM. By using region growing method for the segmentation of DSM rules, the removal of non building point cloud, obtaining the building point cloud information. Uses the Canny operator to extract the image segmentation is needed after the edges of the building, uses Hough transform line detection to extract the edges of buildings rules of operation based on the smooth and uniform. At last, uses E3De3 software to establish the 3D model of buildings.

77 FR 20743 - Protective Force Personnel Medical, Physical Readiness, Training, and Access Authorization Standards

Federal Register 2010, 2011, 2012, 2013, 2014

2012-04-06

...-HQ-2012-0002] RIN 1992-AA40 Protective Force Personnel Medical, Physical Readiness, Training, and... the proposed rule to amend the standards for medical, physical performance, training, and access... proposed rule to revise the standards for medical, physical performance, training, and access...

Adherence to Bergmann's rule by lizards may depend on thermoregulatory mode: support from a nocturnal gecko.

PubMed

Penniket, Sophie; Cree, Alison

2015-06-01

Bergmann's rule predicts an increase in body size with decreasing environmental temperature; however, the converse pattern has been found in the majority of lizards studied to date. For these ectotherms, small body size may provide thermal benefits (rapid heat uptake when basking), which would be highly advantageous in cold environments. Yet such an advantage may not exist in nocturnal lizards (which do not avidly bask), in which Bergmann's rule has not been closely studied. We have examined whether the body size of a primarily nocturnal gecko, Woodworthia "Otago/Southland" changed with elevation and operative temperature (determined using physical copper models). In a laboratory study, we investigated whether thermoregulatory mode (heliothermy or thigmothermy) alters the effect of body size on heating and cooling rates. This gecko followed Bergmann's rule, thereby showing the opposite of the dominant pattern in diurnal lizards. Size at maturity, maximum size of adults and size at birth were larger at higher elevations and at lower operative temperatures. Using physical models, we found that large body size can confer thermal benefits for nocturnal lizards that remain within diurnal retreats. Bergmann's rule should not be dismissed for all lizards. Our results clearly support Bergmann's rule for at least one thigmothermic species, for which large body size may provide thermal benefits. Future studies on Bergmann's rule in lizards should consider thermoregulatory mode. We advocate that this ecogeographic rule be examined in relation to operative temperature measured at field sites. Finally, we predict that climate warming may weaken the relationship between body size and elevation in this gecko.

Poisson-Based Inference for Perturbation Models in Adaptive Spelling Training

ERIC Educational Resources Information Center

Baschera, Gian-Marco; Gross, Markus

2010-01-01

We present an inference algorithm for perturbation models based on Poisson regression. The algorithm is designed to handle unclassified input with multiple errors described by independent mal-rules. This knowledge representation provides an intelligent tutoring system with local and global information about a student, such as error classification…

Broken selection rule in the quantum Rabi model

PubMed Central

Forn-Díaz, P.; Romero, G.; Harmans, C. J. P. M.; Solano, E.; Mooij, J. E.

2016-01-01

Understanding the interaction between light and matter is very relevant for fundamental studies of quantum electrodynamics and for the development of quantum technologies. The quantum Rabi model captures the physics of a single atom interacting with a single photon at all regimes of coupling strength. We report the spectroscopic observation of a resonant transition that breaks a selection rule in the quantum Rabi model, implemented using an LC resonator and an artificial atom, a superconducting qubit. The eigenstates of the system consist of a superposition of bare qubit-resonator states with a relative sign. When the qubit-resonator coupling strength is negligible compared to their own frequencies, the matrix element between excited eigenstates of different sign is very small in presence of a resonator drive, establishing a sign-preserving selection rule. Here, our qubit-resonator system operates in the ultrastrong coupling regime, where the coupling strength is 10% of the resonator frequency, allowing sign-changing transitions to be activated and, therefore, detected. This work shows that sign-changing transitions are an unambiguous, distinctive signature of systems operating in the ultrastrong coupling regime of the quantum Rabi model. These results pave the way to further studies of sign-preserving selection rules in multiqubit and multiphoton models. PMID:27273346

Software For Monitoring A Computer Network

NASA Technical Reports Server (NTRS)

Lee, Young H.

1992-01-01

SNMAT is rule-based expert-system computer program designed to assist personnel in monitoring status of computer network and identifying defective computers, workstations, and other components of network. Also assists in training network operators. Network for SNMAT located at Space Flight Operations Center (SFOC) at NASA's Jet Propulsion Laboratory. Intended to serve as data-reduction system providing windows, menus, and graphs, enabling users to focus on relevant information. SNMAT expected to be adaptable to other computer networks; for example in management of repair, maintenance, and security, or in administration of planning systems, billing systems, or archives.

Nowcasting Cloud Fields for U.S. Air Force Special Operations

DTIC Science & Technology

2017-03-01

application of Bayes’ Rule offers many advantages over Kernel Density Estimation (KDE) and other commonly used statistical post-processing methods...reflectance and probability of cloud. A statistical post-processing technique is applied using Bayesian estimation to train the system from a set of past...nowcasting, low cloud forecasting, cloud reflectance, ISR, Bayesian estimation, statistical post-processing, machine learning 15. NUMBER OF PAGES

Synthesis of Polysyllabic Sequences of Thai Tones Using a Generative Model of Fundamental Frequency Contours

NASA Astrophysics Data System (ADS)

Seresangtakul, Pusadee; Takara, Tomio

In this paper, the distinctive tones of Thai in running speech are studied. We present rules to synthesize F0 contours of Thai tones in running speech by using the generative model of F0 contours. Along with our method, the pitch contours of Thai polysyllabic words, both disyllabic and trisyllabic words, were analyzed. The coarticulation effect of Thai tones in running speech were found. Based on the analysis of the polysyllabic words using this model, rules are derived and applied to synthesize Thai polysyllabic tone sequences. We performed listening tests to evaluate intelligibility of the rules for Thai tones generation. The average intelligibility scores became 98.8%, and 96.6% for disyllabic and trisyllabic words, respectively. From these result, the rule of the tones' generation was shown to be effective. Furthermore, we constructed the connecting rules to synthesize suprasegmental F0 contours using the trisyllable training rules' parameters. The parameters of the first, the third, and the second syllables were selected and assigned to the initial, the ending, and the remaining syllables in a sentence, respectively. Even such a simple rule, the synthesized phrases/senetences were completely identified in listening tests. The MOSs (Mean Opinion Score) was 3.50 while the original and analysis/synthesis samples were 4.82 and 3.59, respectively.

14 CFR 91.189 - Category II and III operations: General operating rules.

Code of Federal Regulations, 2013 CFR

2013-01-01

... pilot who is controlling the aircraft has appropriate instrumentation for the type of flight control... TRANSPORTATION (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Flight Rules Instrument Flight Rules § 91.189 Category II and III operations: General operating rules. (a) No...

14 CFR 91.189 - Category II and III operations: General operating rules.

Code of Federal Regulations, 2012 CFR

2012-01-01

... pilot who is controlling the aircraft has appropriate instrumentation for the type of flight control... TRANSPORTATION (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Flight Rules Instrument Flight Rules § 91.189 Category II and III operations: General operating rules. (a) No...

14 CFR 91.189 - Category II and III operations: General operating rules.

Code of Federal Regulations, 2014 CFR

2014-01-01

... pilot who is controlling the aircraft has appropriate instrumentation for the type of flight control... TRANSPORTATION (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Flight Rules Instrument Flight Rules § 91.189 Category II and III operations: General operating rules. (a) No...

Training telescope operators and support astronomers at Paranal

NASA Astrophysics Data System (ADS)

Boffin, Henri M. J.; Gadotti, Dimitri A.; Anderson, Joe; Pino, Andres; de Wit, Willem-Jan; Girard, Julien H. V.

2016-07-01

The operations model of the Paranal Observatory relies on the work of efficient staff to carry out all the daytime and nighttime tasks. This is highly dependent on adequate training. The Paranal Science Operations department (PSO) has a training group that devises a well-defined and continuously evolving training plan for new staff, in addition to broadening and reinforcing courses for the whole department. This paper presents the training activities for and by PSO, including recent astronomical and quality control training for operators, as well as adaptive optics and interferometry training of all staff. We also present some future plans.

SABER: Airland Combat Training Model Credibility Assessment and Methodology

DTIC Science & Technology

1992-03-01

The three types of weather are good, VFR conditions (visual flight rules); fair , MVFR (marginal VFR), and; poor, IFR conditions (instrument flight rules...categories good, fair and poor represent VFR, MVFR and IFR flight conditions respectively. Darkness can be thought of as an attribute of weather, that... fair , poor, or very poor (VP). The meaning of these values were explained in section 4.3.5. Another value , called impassible (IMP), should be added to

29 CFR 553.226 - Training time.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 29 Labor 3 2011-07-01 2011-07-01 false Training time. 553.226 Section 553.226 Labor Regulations... Enforcement Employees of Public Agencies Tour of Duty and Compensable Hours of Work Rules § 553.226 Training time. (a) The general rules for determining the compensability of training time under the FLSA are set...

Real-time reservoir operation considering non-stationary inflow prediction

NASA Astrophysics Data System (ADS)

Zhao, J.; Xu, W.; Cai, X.; Wang, Z.

2011-12-01

Stationarity of inflow has been a basic assumption for reservoir operation rule design, which is now facing challenges due to climate change and human interferences. This paper proposes a modeling framework to incorporate non-stationary inflow prediction for optimizing the hedging operation rule of large reservoirs with multiple-year flow regulation capacity. A multi-stage optimization model is formulated and a solution algorithm based on the optimality conditions is developed to incorporate non-stationary annual inflow prediction through a rolling, dynamic framework that updates the prediction from period to period and adopt the updated prediction in reservoir operation decision. The prediction model is ARIMA(4,1,0), in which parameter 4 stands for the order of autoregressive, 1 represents a linear trend, and 0 is the order of moving average. The modeling framework and solution algorithm is applied to the Miyun reservoir in China, determining a yearly operating schedule during the period from 1996 to 2009, during which there was a significant declining trend of reservoir inflow. Different operation policy scenarios are modeled, including standard operation policy (SOP, matching the current demand as much as possible), hedging rule (i.e., leaving a certain amount of water for future to avoid large risk of water deficit) with forecast from ARIMA (HR-1), hedging (HR) with perfect forecast (HR-2 ). Compared to the results of these scenarios to that of the actual reservoir operation (AO), the utility of the reservoir operation under HR-1 is 3.0% lower than HR-2, but 3.7% higher than the AO and 14.4% higher than SOP. Note that the utility under AO is 10.3% higher than that under SOP, which shows that a certain level of hedging under some inflow prediction or forecast was used in the real-world operation. Moreover, the impacts of discount rate and forecast uncertainty level on the operation will be discussed.

Simulation of longitudinal dynamics of a freight train operating through a car dumper

NASA Astrophysics Data System (ADS)

Kovalev, R.; Sakalo, A.; Yazykov, V.; Shamdani, A.; Bowey, R.; Wakeling, C.

2016-06-01

A heavy haul train and car dumper model was created to analyse train longitudinal dynamics during dumping. Influence of such factors as performance curve of draft gears, total free slack in couplers, operating mode of train positioner and braking of last two cars of train on the in-train forces was considered.

Optimal operating rules definition in complex water resource systems combining fuzzy logic, expert criteria and stochastic programming

NASA Astrophysics Data System (ADS)

Macian-Sorribes, Hector; Pulido-Velazquez, Manuel

2016-04-01

This contribution presents a methodology for defining optimal seasonal operating rules in multireservoir systems coupling expert criteria and stochastic optimization. Both sources of information are combined using fuzzy logic. The structure of the operating rules is defined based on expert criteria, via a joint expert-technician framework consisting in a series of meetings, workshops and surveys carried out between reservoir managers and modelers. As a result, the decision-making process used by managers can be assessed and expressed using fuzzy logic: fuzzy rule-based systems are employed to represent the operating rules and fuzzy regression procedures are used for forecasting future inflows. Once done that, a stochastic optimization algorithm can be used to define optimal decisions and transform them into fuzzy rules. Finally, the optimal fuzzy rules and the inflow prediction scheme are combined into a Decision Support System for making seasonal forecasts and simulate the effect of different alternatives in response to the initial system state and the foreseen inflows. The approach presented has been applied to the Jucar River Basin (Spain). Reservoir managers explained how the system is operated, taking into account the reservoirs' states at the beginning of the irrigation season and the inflows previewed during that season. According to the information given by them, the Jucar River Basin operating policies were expressed via two fuzzy rule-based (FRB) systems that estimate the amount of water to be allocated to the users and how the reservoir storages should be balanced to guarantee those deliveries. A stochastic optimization model using Stochastic Dual Dynamic Programming (SDDP) was developed to define optimal decisions, which are transformed into optimal operating rules embedding them into the two FRBs previously created. As a benchmark, historical records are used to develop alternative operating rules. A fuzzy linear regression procedure was employed to foresee future inflows depending on present and past hydrological and meteorological variables actually used by the reservoir managers to define likely inflow scenarios. A Decision Support System (DSS) was created coupling the FRB systems and the inflow prediction scheme in order to give the user a set of possible optimal releases in response to the reservoir states at the beginning of the irrigation season and the fuzzy inflow projections made using hydrological and meteorological information. The results show that the optimal DSS created using the FRB operating policies are able to increase the amount of water allocated to the users in 20 to 50 Mm3 per irrigation season with respect to the current policies. Consequently, the mechanism used to define optimal operating rules and transform them into a DSS is able to increase the water deliveries in the Jucar River Basin, combining expert criteria and optimization algorithms in an efficient way. This study has been partially supported by the IMPADAPT project (CGL2013-48424-C2-1-R) with Spanish MINECO (Ministerio de Economía y Competitividad) and FEDER funds. It also has received funding from the European Union's Horizon 2020 research and innovation programme under the IMPREX project (grant agreement no: 641.811).

A detailed comparison of optimality and simplicity in perceptual decision-making

PubMed Central

Shen, Shan; Ma, Wei Ji

2017-01-01

Two prominent ideas in the study of decision-making have been that organisms behave near-optimally, and that they use simple heuristic rules. These principles might be operating in different types of tasks, but this possibility cannot be fully investigated without a direct, rigorous comparison within a single task. Such a comparison was lacking in most previous studies, because a) the optimal decision rule was simple; b) no simple suboptimal rules were considered; c) it was unclear what was optimal, or d) a simple rule could closely approximate the optimal rule. Here, we used a perceptual decision-making task in which the optimal decision rule is well-defined and complex, and makes qualitatively distinct predictions from many simple suboptimal rules. We find that all simple rules tested fail to describe human behavior, that the optimal rule accounts well for the data, and that several complex suboptimal rules are indistinguishable from the optimal one. Moreover, we found evidence that the optimal model is close to the true model: first, the better the trial-to-trial predictions of a suboptimal model agree with those of the optimal model, the better that suboptimal model fits; second, our estimate of the Kullback-Leibler divergence between the optimal model and the true model is not significantly different from zero. When observers receive no feedback, the optimal model still describes behavior best, suggesting that sensory uncertainty is implicitly represented and taken into account. Beyond the task and models studied here, our results have implications for best practices of model comparison. PMID:27177259

DeepSleepNet: A Model for Automatic Sleep Stage Scoring Based on Raw Single-Channel EEG.

PubMed

Supratak, Akara; Dong, Hao; Wu, Chao; Guo, Yike

2017-11-01

This paper proposes a deep learning model, named DeepSleepNet, for automatic sleep stage scoring based on raw single-channel EEG. Most of the existing methods rely on hand-engineered features, which require prior knowledge of sleep analysis. Only a few of them encode the temporal information, such as transition rules, which is important for identifying the next sleep stages, into the extracted features. In the proposed model, we utilize convolutional neural networks to extract time-invariant features, and bidirectional-long short-term memory to learn transition rules among sleep stages automatically from EEG epochs. We implement a two-step training algorithm to train our model efficiently. We evaluated our model using different single-channel EEGs (F4-EOG (left), Fpz-Cz, and Pz-Oz) from two public sleep data sets, that have different properties (e.g., sampling rate) and scoring standards (AASM and R&K). The results showed that our model achieved similar overall accuracy and macro F1-score (MASS: 86.2%-81.7, Sleep-EDF: 82.0%-76.9) compared with the state-of-the-art methods (MASS: 85.9%-80.5, Sleep-EDF: 78.9%-73.7) on both data sets. This demonstrated that, without changing the model architecture and the training algorithm, our model could automatically learn features for sleep stage scoring from different raw single-channel EEGs from different data sets without utilizing any hand-engineered features.

Occupational exposure decisions: can limited data interpretation training help improve accuracy?

PubMed

Logan, Perry; Ramachandran, Gurumurthy; Mulhausen, John; Hewett, Paul

2009-06-01

Accurate exposure assessments are critical for ensuring that potentially hazardous exposures are properly identified and controlled. The availability and accuracy of exposure assessments can determine whether resources are appropriately allocated to engineering and administrative controls, medical surveillance, personal protective equipment and other programs designed to protect workers. A desktop study was performed using videos, task information and sampling data to evaluate the accuracy and potential bias of participants' exposure judgments. Desktop exposure judgments were obtained from occupational hygienists for material handling jobs with small air sampling data sets (0-8 samples) and without the aid of computers. In addition, data interpretation tests (DITs) were administered to participants where they were asked to estimate the 95th percentile of an underlying log-normal exposure distribution from small data sets. Participants were presented with an exposure data interpretation or rule of thumb training which included a simple set of rules for estimating 95th percentiles for small data sets from a log-normal population. DIT was given to each participant before and after the rule of thumb training. Results of each DIT and qualitative and quantitative exposure judgments were compared with a reference judgment obtained through a Bayesian probabilistic analysis of the sampling data to investigate overall judgment accuracy and bias. There were a total of 4386 participant-task-chemical judgments for all data collections: 552 qualitative judgments made without sampling data and 3834 quantitative judgments with sampling data. The DITs and quantitative judgments were significantly better than random chance and much improved by the rule of thumb training. In addition, the rule of thumb training reduced the amount of bias in the DITs and quantitative judgments. The mean DIT % correct scores increased from 47 to 64% after the rule of thumb training (P < 0.001). The accuracy for quantitative desktop judgments increased from 43 to 63% correct after the rule of thumb training (P < 0.001). The rule of thumb training did not significantly impact accuracy for qualitative desktop judgments. The finding that even some simple statistical rules of thumb improve judgment accuracy significantly suggests that hygienists need to routinely use statistical tools while making exposure judgments using monitoring data.

IITET and shadow TT: an innovative approach to training at the point of need

NASA Astrophysics Data System (ADS)

Gross, Andrew; Lopez, Favio; Dirkse, James; Anderson, Darran; Berglie, Stephen; May, Christopher; Harkrider, Susan

2014-06-01

The Image Intensification and Thermal Equipment Training (IITET) project is a joint effort between Night Vision and Electronics Sensors Directorate (NVESD) Modeling and Simulation Division (MSD) and the Army Research Institute (ARI) Fort Benning Research Unit. The IITET effort develops a reusable and extensible training architecture that supports the Army Learning Model and trains Manned-Unmanned Teaming (MUM-T) concepts to Shadow Unmanned Aerial Systems (UAS) payload operators. The training challenge of MUM-T during aviation operations is that UAS payload operators traditionally learn few of the scout-reconnaissance skills and coordination appropriate to MUM-T at the schoolhouse. The IITET effort leveraged the simulation experience and capabilities at NVESD and ARI's research to develop a novel payload operator training approach consistent with the Army Learning Model. Based on the training and system requirements, the team researched and identified candidate capabilities in several distinct technology areas. The training capability will support a variety of training missions as well as a full campaign. Data from these missions will be captured in a fully integrated AAR capability, which will provide objective feedback to the user in near-real-time. IITET will be delivered via a combination of browser and video streaming technologies, eliminating the requirement for a client download and reducing user computer system requirements. The result is a novel UAS Payload Operator training capability, nested within an architecture capable of supporting a wide variety of training needs for air and ground tactical platforms and sensors, and potentially several other areas requiring vignette-based serious games training.

14 CFR 61.71 - Graduates of an approved training program other than under this part: Special rules.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 14 Aeronautics and Space 2 2013-01-01 2013-01-01 false Graduates of an approved training program... GROUND INSTRUCTORS Aircraft Ratings and Pilot Authorizations § 61.71 Graduates of an approved training program other than under this part: Special rules. (a) A person who graduates from an approved training...

14 CFR 61.71 - Graduates of an approved training program other than under this part: Special rules.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 2 2010-01-01 2010-01-01 false Graduates of an approved training program... GROUND INSTRUCTORS Aircraft Ratings and Pilot Authorizations § 61.71 Graduates of an approved training program other than under this part: Special rules. (a) A person who graduates from an approved training...

14 CFR 61.71 - Graduates of an approved training program other than under this part: Special rules.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 2 2011-01-01 2011-01-01 false Graduates of an approved training program... GROUND INSTRUCTORS Aircraft Ratings and Pilot Authorizations § 61.71 Graduates of an approved training program other than under this part: Special rules. (a) A person who graduates from an approved training...

14 CFR 61.71 - Graduates of an approved training program other than under this part: Special rules.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 2 2012-01-01 2012-01-01 false Graduates of an approved training program... GROUND INSTRUCTORS Aircraft Ratings and Pilot Authorizations § 61.71 Graduates of an approved training program other than under this part: Special rules. (a) A person who graduates from an approved training...

14 CFR 61.71 - Graduates of an approved training program other than under this part: Special rules.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 14 Aeronautics and Space 2 2014-01-01 2014-01-01 false Graduates of an approved training program... GROUND INSTRUCTORS Aircraft Ratings and Pilot Authorizations § 61.71 Graduates of an approved training program other than under this part: Special rules. (a) A person who graduates from an approved training...

Advanced Technology Training System on Motor-Operated Valves

NASA Technical Reports Server (NTRS)

Wiederholt, Bradley J.; Widjaja, T. Kiki; Yasutake, Joseph Y.; Isoda, Hachiro

1993-01-01

This paper describes how features from the field of Intelligent Tutoring Systems are applied to the Motor-Operated Valve (MOV) Advanced Technology Training System (ATTS). The MOV ATTS is a training system developed at Galaxy Scientific Corporation for the Central Research Institute of Electric Power Industry in Japan and the Electric Power Research Institute in the United States. The MOV ATTS combines traditional computer-based training approaches with system simulation, integrated expert systems, and student and expert modeling. The primary goal of the MOV ATTS is to reduce human errors that occur during MOV overhaul and repair. The MOV ATTS addresses this goal by providing basic operational information of the MOV, simulating MOV operation, providing troubleshooting practice of MOV failures, and tailoring this training to the needs of each individual student. The MOV ATTS integrates multiple expert models (functional and procedural) to provide advice and feedback to students. The integration also provides expert model validation support to developers. Student modeling is supported by two separate student models: one model registers and updates the student's current knowledge of basic MOV information, while another model logs the student's actions and errors during troubleshooting exercises. These two models are used to provide tailored feedback to the student during the MOV course.

On structuring the rules of a fuzzy controller

NASA Technical Reports Server (NTRS)

Zhou, Jun; Raju, G. V. S.

1993-01-01

Since the pioneering work of Zadeh and Mamdani and Assilian, fuzzy logic control has emerged as one of the most active and fruitful research areas. The applications of fuzzy logic control can be found in many fields such as control of stream generators, automatic train operation systems, elevator control, nuclear reactor control, automobile transmission control, etc. In this paper, two new structures of hierarchical fuzzy rule-based controller are proposed to reduce the number of rules in a complete rule set of a controller. In one approach, the overall system is split into sub-systems which are treated independently in parallel. A coordinator is then used to take into account the interactions. This is done via an iterating information exchange between the lower level and the coordinator level. From the point of view of information used, this structure is very similar to central structure in that the coordinator can have at least in principle, all the information that the local controllers have.

Attitudes to teamwork and safety among Italian surgeons and operating room nurses.

PubMed

Prati, Gabriele; Pietrantoni, Luca

2014-01-01

Previous studies have shown that surgical team members' attitudes about safety and teamwork in the operating theatre may play a role in patient safety. The aim of this study was to assess attitudes about teamwork and safety among Italian surgeons and operating room nurses. Fifty-five surgeons and 48 operating room nurses working in operating theatres at one hospital in Italy completed the Operating Room Management Attitudes Questionnaire (ORMAQ). Results showed several discrepancies in attitudes about teamwork and safety between surgeons and operating room nurses. Surgeons had more positive views on the quality of surgical leadership, communication, teamwork, and organizational climate in the theatre than operating room nurses. Operating room nurses reported that safety rules and procedures were more frequently disregarded than the surgeons. The results are only partially aligned with previous ORMAQ surveys of surgical teams in other countries. The differences emphasize the influence of national culture, as well as the particular healthcare system. This study shows discrepancies on many aspects in attitudes to teamwork and safety between surgeons and operating room nurses. The findings support implementation and use of team interventions and human factor training. Finally, attitude surveys provide a method for assessing safety culture in surgery, for evaluating the effectiveness of training initiatives, and for collecting data for a hospital's quality assurance programme.

Equilibria of perceptrons for simple contingency problems.

PubMed

Dawson, Michael R W; Dupuis, Brian

2012-08-01

The contingency between cues and outcomes is fundamentally important to theories of causal reasoning and to theories of associative learning. Researchers have computed the equilibria of Rescorla-Wagner models for a variety of contingency problems, and have used these equilibria to identify situations in which the Rescorla-Wagner model is consistent, or inconsistent, with normative models of contingency. Mathematical analyses that directly compare artificial neural networks to contingency theory have not been performed, because of the assumed equivalence between the Rescorla-Wagner learning rule and the delta rule training of artificial neural networks. However, recent results indicate that this equivalence is not as straightforward as typically assumed, suggesting a strong need for mathematical accounts of how networks deal with contingency problems. One such analysis is presented here, where it is proven that the structure of the equilibrium for a simple network trained on a basic contingency problem is quite different from the structure of the equilibrium for a Rescorla-Wagner model faced with the same problem. However, these structural differences lead to functionally equivalent behavior. The implications of this result for the relationships between associative learning, contingency theory, and connectionism are discussed.

A probabilistic method to diagnose faults of air handling units

NASA Astrophysics Data System (ADS)

Dey, Debashis

Air handling unit (AHU) is one of the most extensively used equipment in large commercial buildings. This device is typically customized and lacks quality system integration which can result in hardwire failures and controller errors. Air handling unit Performance Assessment Rules (APAR) is a fault detection tool that uses a set of expert rules derived from mass and energy balances to detect faults in air handling units. APAR is computationally simple enough that it can be embedded in commercial building automation and control systems and relies only upon sensor data and control signals that are commonly available in these systems. Although APAR has many advantages over other methods, for example no training data required and easy to implement commercially, most of the time it is unable to provide the diagnosis of the faults. For instance, a fault on temperature sensor could be fixed bias, drifting bias, inappropriate location, complete failure. Also a fault in mixing box can be return and outdoor damper leak or stuck. In addition, when multiple rules are satisfied the list of faults increases. There is no proper way to have the correct diagnosis for rule based fault detection system. To overcome this limitation we proposed Bayesian Belief Network (BBN) as a diagnostic tool. BBN can be used to simulate diagnostic thinking of FDD experts through a probabilistic way. In this study we developed a new way to detect and diagnose faults in AHU through combining APAR rules and Bayesian Belief network. Bayesian Belief Network is used as a decision support tool for rule based expert system. BBN is highly capable to prioritize faults when multiple rules are satisfied simultaneously. Also it can get information from previous AHU operating conditions and maintenance records to provide proper diagnosis. The proposed model is validated with real time measured data of a campus building at University of Texas at San Antonio (UTSA).The results show that BBN is correctly able to prioritize faults which can be verified by manual investigation.

Model-Based Anomaly Detection for a Transparent Optical Transmission System

NASA Astrophysics Data System (ADS)

Bengtsson, Thomas; Salamon, Todd; Ho, Tin Kam; White, Christopher A.

In this chapter, we present an approach for anomaly detection at the physical layer of networks where detailed knowledge about the devices and their operations is available. The approach combines physics-based process models with observational data models to characterize the uncertainties and derive the alarm decision rules. We formulate and apply three different methods based on this approach for a well-defined problem in optical network monitoring that features many typical challenges for this methodology. Specifically, we address the problem of monitoring optically transparent transmission systems that use dynamically controlled Raman amplification systems. We use models of amplifier physics together with statistical estimation to derive alarm decision rules and use these rules to automatically discriminate between measurement errors, anomalous losses, and pump failures. Our approach has led to an efficient tool for systematically detecting anomalies in the system behavior of a deployed network, where pro-active measures to address such anomalies are key to preventing unnecessary disturbances to the system's continuous operation.

40 CFR Table 3 to Subpart Dddd of... - Model Rule-Operating Limits for Wet Scrubbers

Code of Federal Regulations, 2010 CFR

2010-07-01

... Scrubbers 3 Table 3 to Subpart DDDD of Part 60 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY...—Model Rule—Operating Limits for Wet Scrubbers For these operating parameters You must establish these... intermittent units) a Pressure drop across the wet scrubber or amperage to wet scrubber Minimum pressure drop...

40 CFR Table 3 to Subpart Dddd of... - Model Rule-Operating Limits for Wet Scrubbers

Code of Federal Regulations, 2011 CFR

2011-07-01

... Scrubbers 3 Table 3 to Subpart DDDD of Part 60 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY...—Model Rule—Operating Limits for Wet Scrubbers For these operating parameters You must establish these... intermittent units) a Pressure drop across the wet scrubber or amperage to wet scrubber Minimum pressure drop...

Construction safety program for the National Ignition Facility, July 30, 1999 (NIF-0001374-OC)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Benjamin, D W

1999-07-30

These rules apply to all LLNL employees, non-LLNL employees (including contract labor, supplemental labor, vendors, personnel matrixed/assigned from other National Laboratories, participating guests, visitors and students) and contractors/subcontractors. The General Rules-Code of Safe Practices shall be used by management to promote accident prevention through indoctrination, safety and health training and on-the-job application. As a condition for contracts award, all contractors and subcontractors and their employees must certify on Form S and H A-l that they have read and understand, or have been briefed and understand, the National Ignition Facility OCIP Project General Rules-Code of Safe Practices. (An interpreter must briefmore » those employees who do not speak or read English fluently.) In addition, all contractors and subcontractors shall adopt a written General Rules-Code of Safe Practices that relates to their operations. The General Rules-Code of Safe Practices must be posted at a conspicuous location at the job site office or be provided to each supervisory employee who shall have it readily available. Copies of the General Rules-Code of Safe Practices can also be included in employee safety pamphlets.« less

Individual Differences in Learning and Transfer: Stable Tendencies for Learning Exemplars versus Abstracting Rules

PubMed Central

McDaniel, Mark A.; Cahill, Michael J.; Robbins, Mathew; Wiener, Chelsea

2013-01-01

We hypothesize that during training some learners may focus on acquiring the particular exemplars and responses associated with the exemplars (termed exemplar learners), whereas other learners attempt to abstract underlying regularities reflected in the particular exemplars linked to an appropriate response (termed rule learners). Supporting this distinction, after training (on a function-learning task), participants either displayed an extrapolation profile reflecting acquisition of the trained cue-criterion associations (exemplar learners) or abstraction of the function rule (rule learners; Studies 1a and 1b). Further, working memory capacity (measured by Ospan) was associated with the tendency to rely on rule versus exemplar processes. Studies 1c and 2 examined the persistence of these learning tendencies on several categorization tasks. Study 1c showed that rule learners were more likely than exemplar learners (indexed a priori by extrapolation profiles) to resist using idiosyncratic features (exemplar similarity) in generalization (transfer) of the trained category. Study 2 showed that the rule learners but not the exemplar learners performed well on a novel categorization task (transfer) after training on an abstract coherent category. These patterns suggest that in complex conceptual tasks, (a) individuals tend to either focus on exemplars during learning or on extracting some abstraction of the concept, (b) this tendency might be a relatively stable characteristic of the individual, and (c) transfer patterns are determined by that tendency. PMID:23750912

Plant-mimetic Heat Pipes for Operation with Large Inertial and Gravitational Stresses

DTIC Science & Technology

2015-08-07

Pipes (SHLHP), we developed a set of mathematical models and experimental approaches. Our models provide design rules for heat transfer systems that could...number of fronts: 1) Design concepts and modeling tools: We have proposed a new design for loop heat pipes that operates with superheated liquid...and completed a mathematical model of steady state operation of such superheated loop heat pipes (SHLHP). We have also developed a transport theories

How to Design a Genetic Mating Scheme: A Basic Training Package for Drosophila Genetics

PubMed Central

Roote, John; Prokop, Andreas

2013-01-01

Drosophila melanogaster is a powerful model organism for biological research. The essential and common instrument of fly research is genetics, the art of applying Mendelian rules in the specific context of Drosophila with its unique classical genetic tools and the breadth of modern genetic tools and strategies brought in by molecular biology, transgenic technologies and the use of recombinases. Training newcomers to fly genetics is a complex and time-consuming task but too important to be left to chance. Surprisingly, suitable training resources for beginners currently are not available. Here we provide a training package for basic Drosophila genetics, designed to ensure that basic knowledge on all key areas is covered while reducing the time invested by trainers. First, a manual introduces to fly history, rationale for mating schemes, fly handling, Mendelian rules in fly, markers and balancers, mating scheme design, and transgenic technologies. Its self-study is followed by a practical training session on gender and marker selection, introducing real flies under the dissecting microscope. Next, through self-study of a PowerPoint presentation, trainees are guided step-by-step through a mating scheme. Finally, to consolidate knowledge, trainees are asked to design similar mating schemes reflecting routine tasks in a fly laboratory. This exercise requires individual feedback but also provides unique opportunities for trainers to spot weaknesses and strengths of each trainee and take remedial action. This training package is being successfully applied at the Manchester fly facility and may serve as a model for further training resources covering other aspects of fly research. PMID:23390611

Small Unmanned Aerial Systems: Implications of the Evolving Legal Context for Use in Natural Resources Science and Management

NASA Astrophysics Data System (ADS)

Walker, M. J.

2016-12-01

Small unmanned aerial systems (sUAS, also known as drones) potentially provide researchers and managers with the capacity to enhance temporal and spatial resolution of data sets for natural resources science and management. sUAS have been used for many types of data collection and have a partial definition in mass of the aircraft, ranging from 0.5 to <55 lbs (0.2 to <24.9 kg). Aircraft within this range of mass can present a collision hazard to other aircraft. The Federal Aviation Administration (FAA) recently faced the challenge of removing regulatory barriers to sUAS application while minimizing risk in the national airspace. The regulatory and legal framework developed for using sUAS in natural resources science and management has evolved from a very conservative approach prior in the first decade of the 21st century. FAA's recently revised operating rules for sUAS, significantly changing pilot certification requirements and operating rules in the national airspace. The next 2-5 years will bring advances in sUAS applications for science and management, building upon the accomplishments of users who complied with the former regulatory environment. We review the current operating rules (49 CFR, part 107) that apply specifically to sUAS and discuss the implications for researchers and managers. While part 107 relaxed many restrictions, it is important to understand the regulatory framework currently in place that encourages development of applications for sUAS while adhering to the mandate that the national airspace be safe and secure. We consider potential applications for natural resources science and management in the context of the recently released operating rules, especially with respect to training requirements and protocols for use.

Learning to use working memory: a reinforcement learning gating model of rule acquisition in rats

PubMed Central

Lloyd, Kevin; Becker, Nadine; Jones, Matthew W.; Bogacz, Rafal

2012-01-01

Learning to form appropriate, task-relevant working memory representations is a complex process central to cognition. Gating models frame working memory as a collection of past observations and use reinforcement learning (RL) to solve the problem of when to update these observations. Investigation of how gating models relate to brain and behavior remains, however, at an early stage. The current study sought to explore the ability of simple RL gating models to replicate rule learning behavior in rats. Rats were trained in a maze-based spatial learning task that required animals to make trial-by-trial choices contingent upon their previous experience. Using an abstract version of this task, we tested the ability of two gating algorithms, one based on the Actor-Critic and the other on the State-Action-Reward-State-Action (SARSA) algorithm, to generate behavior consistent with the rats'. Both models produced rule-acquisition behavior consistent with the experimental data, though only the SARSA gating model mirrored faster learning following rule reversal. We also found that both gating models learned multiple strategies in solving the initial task, a property which highlights the multi-agent nature of such models and which is of importance in considering the neural basis of individual differences in behavior. PMID:23115551

Use of Iqqm For Management of A Regulated River System

NASA Astrophysics Data System (ADS)

Hameed, T.; Podger, G.; Harrold, T. I.

The Integrated Quantity-Quality Model (IQQM) is a modelling tool for the planning and management of water-sharing issues within regulated and unregulated river sys- tems. IQQM represents the major river system processes, including inflows, rainfall and evaporation, infiltration, and flow routing down river channels and floodplains. It is a water balance model that operates on a daily timestep and can represent reser- voirs, wetlands, surface water/groundwater interaction, and soil moisture deficit for irrigation areas, along with many other features of both natural and regulated systems. IQQM can be customised for any river valley, and has proven to be a useful tool for the development, evaluation, and selection of operational rules for complex river systems. The Lachlan catchment lies within Australia's largest river system, the Murray- Darling Basin. Extensive development in the Murray-Darling Basin within the last 100 years has resulted in land degradation, increased salinity, poor water quality, damage to wetlands, and decline in native fish species. In response to these issues, in 1995 the Murray-Darling Basin Commission (MDBC) imposed restrictions on growth in diver- sions (the "MDBC Cap"), and the New South Wales government has more recently applied its own restrictions (the "River Flow Objectives"). To implement the MDBC Cap and the River Flow Objectives, new operational rules were required. This presen- tation describes how IQQM was used to develop and evaluate these rules for the Lach- lan system. In particular, rules for release of environmental flows were developed and evaluated. The model helped identify the flow window that would be most beneficial to the riverine environment, the critical time of year when environmental releases should be made, and resource constraint conditions when environmental releases should not be made. This process also involved intensive consultations with stakeholders. The role of IQQM within this process was to help the stakeholders understand the inter- action of various users within the valley, and the impacts of the operational rules on them.

Training Extract, AFSC 113X0B, Flight Engineer, Helicopter Qualified.

DTIC Science & Technology

1982-12-01

TRAINING .................................................................. 1I0 SE. GENERAL rLIGHT RULES A 9 C t | 7. PeRFORM INSPECIIOIS 12 7A... TRAINING .................................................................. lIC 6E. GENERAL FLIGHT RULES A a C...ME"BERS PERFORMING I-A I PROGRAM GENERATED VECTOR IMEMBERS/ NO TYPE VECTOR MEAN - SC DESCRIPTION I TN. SEP J.6 2.J TRAINING EMPHASIS RATINSS I IIOS

Web-based training related to NRC staff review of dose modeling aspects of license termination and decommissioning plans

DOE Office of Scientific and Technical Information (OSTI.GOV)

LePoire, D.; Arnish, J.; Cheng, J.J.

NRC licensees at decommissioning nuclear facilities submit License Termination Plans (LTP) or Decommissioning Plans (DP) to NRC for review and approval. To facilitate a uniform and consistent review of these plans, the NRC developed training for its staff. A live classroom course was first developed in 2005, which targeted specific aspects of the LTP and DP review process related to dose-based compliance demonstrations or modeling. A web-based training (WBT) course is being developed in 2006 to replace the classroom-based course. The advantage of the WBT is that it will allow for staff training or refreshers at any time, while themore » advantage of a classroom-based course is that it provides a forum for lively discussion and the sharing of experience of classroom participants. The training course consists of the core and advanced modules tailored to specific NRC job functions. Topics for individual modules include identifying the characteristics of simple and complex sites, identifying when outside expertise or consultation is needed, demonstrating how to conduct acceptance and technical reviews of dose modeling, and providing details regarding the level of justification needed for realistic scenarios for both dose modeling and derivation of DCGLs. Various methods of applying probabilistic uncertainty analysis to demonstrate compliance with dose-based requirements are presented. These approaches include 1) modeling the pathways of radiological exposure and estimating doses to receptors from a combination of contaminated media and radionuclides, and 2) using probabilistic analysis to determine an appropriate set of input parameters to develop derived concentration guideline limits or DCGLs (DCGLs are media- and nuclide-specific concentration limits that will meet dose-based, license termination rule criteria found in 10 CFR Part 20, Subpart E). Calculation of operational (field) DCGL's from media- and nuclide-specific DCGLs and use of operational DCGLs in conducting final status surveys are addressed in the WBT. Realistic case examples are presented and analyzed including the abstraction of a realistic site into a conceptual model and computer model. A case history is also used to demonstrate development of NRC review documents such as requests for additional information (RAIs). To enhance the web-based training experience, audio, animations, linked documents, quizzes, and scripts are being integrated with a commercial web-based training package that supports simple navigation. The course is also being integrated into both existing and state-of-the-art learning management systems. A testing group is being utilized to identify and help resolve training issues prior to deployment of the course. When completed, the course can be accessed for credited training with required modules dependent on the job category of the training participant. The modules will also be accessible to NRC staff for review or refresher following initial course completion. WBT promotes consistency in reviews and has the advantage of being able to be used as a resource to staff at any time. The WBT will provide reviewers with knowledge needed to perform risk-informed analyses (e.g., information related to development of realistic scenarios and use of probabilistic analysis). WBT on review of LTP or DP dose modeling will promote staff development, efficiency, and effectiveness in performing risk-informed, performance-based reviews of decommissioning activities at NRC-licensed facilities. (authors)« less

75 FR 25785 - Airworthiness Directives; BAE Systems (Operations) Limited Model 4101 Airplanes

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-10

... Airworthiness Directives; BAE Systems (Operations) Limited Model 4101 Airplanes AGENCY: Federal Aviation... the propeller blades, which can result in dangerous blade cracks. The European Aviation Safety Agency... issue rules on aviation safety. Subtitle I, section 106, describes the authority of the FAA...

[THE ALTERNATIVE MODEL IN TRAINING FOR OPERATION MANAGEMENT ON LUMBAR SPINE].

PubMed

Zakondyrin, D E

2015-01-01

The authors proposed to use a lumbar part of calf carcass as a new biological model for training of basic practical skills in order to perform the neurosurgical operative interventions on the spine. The proximity of anatomico-surgical parameters of given model and human cavader lumbar spine was estimated. The study proved the possibility of use of lumbar part of calf carcass for training techniques of transpedicular fixation and microdiskectomy in lumbar part.

[Operative vaginal deliveries training].

PubMed

Dupuis, O

2008-12-01

The appropriate use of forceps, vacuums or spatulas facilitates the rapid delivery of foetuses faced with life-threatening situations. It also makes possible the relief of certain cases of prolonged second-stage labor. In France, operative vaginal delivery (OVD) accounts for approximately 10% of all births. OVD training aims to optimize maternal, as well as neonatal safety. It should enable trainees to indicate or contraindicate an OVD safely, as well as to choose the appropriate instrument, use it correctly, and master quality control principles. Traditional OVD training is confronted with both spatial and time-related limitations. Spatial constraints involve both the teacher and trainee who only have limited visual access to the pelvic canal, and the head of the foetus; the time constraint occurs whenever the OVD occurs in an emergency setting. These limitations have been further aggravated by new constraints: decreasing time dedicated to training (European safety rules prohibit work the day after night duty), increasing litigation, and constraints imposed by society. Training by means of simulation removes such limitations making it possible to both avoid exposing pregnant women to the hazards of traditional training, and adapt the training to the skills of each trainee. OVD training should include forceps, vacuums and the use of spatulas. The OVD skills of obstetricians should be audited regularly on both a personal and a confidential level. Such audits could be based on a method using a simulator. Prospective studies comparing traditional and simulation-based training should be encouraged.

Failure to Visualize and Describe Operations: The Evolution and Implementation of the Operational Framework

DTIC Science & Technology

2017-05-25

Operations, and Unified Land Operations) and the US Army’s leader development model identifies how the education , training, and experience of field-grade...officers have failed in their incorporation of the framework because they lack the education , training, and experience for the use of the framework... education , training, and experience of field-grade officers at the division level have influenced their use of the operational framework. The cause for

Teaching artificial neural systems to drive: Manual training techniques for autonomous systems

NASA Technical Reports Server (NTRS)

Shepanski, J. F.; Macy, S. A.

1987-01-01

A methodology was developed for manually training autonomous control systems based on artificial neural systems (ANS). In applications where the rule set governing an expert's decisions is difficult to formulate, ANS can be used to extract rules by associating the information an expert receives with the actions taken. Properly constructed networks imitate rules of behavior that permits them to function autonomously when they are trained on the spanning set of possible situations. This training can be provided manually, either under the direct supervision of a system trainer, or indirectly using a background mode where the networks assimilates training data as the expert performs its day-to-day tasks. To demonstrate these methods, an ANS network was trained to drive a vehicle through simulated freeway traffic.

Extracting important information from Chinese Operation Notes with natural language processing methods.

PubMed

Wang, Hui; Zhang, Weide; Zeng, Qiang; Li, Zuofeng; Feng, Kaiyan; Liu, Lei

2014-04-01

Extracting information from unstructured clinical narratives is valuable for many clinical applications. Although natural Language Processing (NLP) methods have been profoundly studied in electronic medical records (EMR), few studies have explored NLP in extracting information from Chinese clinical narratives. In this study, we report the development and evaluation of extracting tumor-related information from operation notes of hepatic carcinomas which were written in Chinese. Using 86 operation notes manually annotated by physicians as the training set, we explored both rule-based and supervised machine-learning approaches. Evaluating on unseen 29 operation notes, our best approach yielded 69.6% in precision, 58.3% in recall and 63.5% F-score. Copyright © 2014 Elsevier Inc. All rights reserved.

Reducing environmental noise impacts: A USAREUR noise management program handbook

NASA Astrophysics Data System (ADS)

Feather, Timothy D.; Shekell, Ted K.

1991-06-01

Noise pollution is a major environmental problem faced by the U.S. Army in Europe. Noise-related complaints from German citizens can escalate into intense political issues in German communities. This in turn hampers efficient operation of military training and often times threatens the Army's mission. In order to remedy these problems, USAREUR has developed a noise management program. A successful noise management program will limit the impact of unavoidable noise on the populace. This report, a component of the noise management program, is a reference document for noise management planning. It contains guidelines and rules-of-thumb for noise management. This document contains procedures which operation and training level personnel can understand and apply in their day to day noise management planning. Noise mitigation tips are given. Basic technical information that will aid in understanding noise mitigation is provided along with noise management through land use planning. Noise management for specific components of the military community, (airfields, base operations, training areas, and housing and recreation areas) are addressed. The nature of noise generated, means of noise abatement at the source, path, and receiver (both physical and organizational/public relations methods), and a case study example are described.

77 FR 13206 - Protective Force Personnel Medical, Physical Readiness, Training, and Access Authorization Standards

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-06

...The Department of Energy (DOE or Department) proposes to revise the regulation governing the standards for medical, physical performance, training, and access authorizations for protective force (PF) personnel employed by contractors providing security services to the Department. The existing version of this regulation was promulgated in 1993 and substantial portions of the regulation date to the mid- 1980s. Since 1993 DOE policy has placed greater reliance upon technology, vehicular response, and increased firepower and, correspondingly, has reduced its reliance upon the ability of PF personnel to perform the running tasks required in the current regulation. Furthermore, this shift in emphasis has placed a greater premium upon the retention of mature, tactically experienced, and technically sophisticated personnel, particularly since these personnel represent a considerable investment by DOE in security background investigations and training. The proposed revisions bring DOE PF medical and physical readiness requirements in line with these tactical and organizational priorities. The proposed revisions reduce the exposure of the PF population to injuries related to physical readiness testing. They would create a PF readiness classification designed specifically to encourage the retention of experienced personnel. The revisions would further ensure that PF personnel would be evaluated on a case-by-case basis on their ability to perform the essential functions of their positions without posing a direct threat to themselves or site personnel, the facility, or the general public. The proposed revisions would further ensure that reasonable accommodations would be considered before a determination is made that an individual cannot perform the essential functions of a particular position. The proposed rule also would provide for new medical review processes for PF personnel disqualified from medical certification. The proposed rule would ensure that DOE PF medical and physical readiness requirements would be compliant with the Americans with Disabilities Act (ADA) of 1990, as amended by the Americans with Disabilities Amendment Act of 2009 (ADAAA), the Privacy Act and DOE implementing regulations, and changes in DOE policy regarding PF operations made since the publication of the last version of this rule. In addition, the proposed rule would promote operational efficiency through greater emphasis on aligning training with mission-essential tasks and the increased use of simulation technologies. Finally, the proposed revision would update the regulation to reflect organizational changes in the Office of Health, Safety and Security and the creation of the National Nuclear Security Administration (NNSA).

Design of Training Systems, Phase II Report, Volume III; Model Program Descriptions and Operating Procedures. TAEG Report No. 12-2.

ERIC Educational Resources Information Center

Naval Training Equipment Center, Orlando, FL. Training Analysis and Evaluation Group.

The Design of Training Systems (DOTS) project was initiated by the Department of Defense (DOD) to develop tools for the effective management of military training organizations. Volume 3 contains the model and data base program descriptions and operating procedures designed for phase 2 of the project. Flow charts and program listings for the…

Assessing experience in the deliberate practice of running using a fuzzy decision-support system

PubMed Central

Roveri, Maria Isabel; Manoel, Edison de Jesus; Onodera, Andrea Naomi; Ortega, Neli R. S.; Tessutti, Vitor Daniel; Vilela, Emerson; Evêncio, Nelson

2017-01-01

The judgement of skill experience and its levels is ambiguous though it is crucial for decision-making in sport sciences studies. We developed a fuzzy decision support system to classify experience of non-elite distance runners. Two Mamdani subsystems were developed based on expert running coaches’ knowledge. In the first subsystem, the linguistic variables of training frequency and volume were combined and the output defined the quality of running practice. The second subsystem yielded the level of running experience from the combination of the first subsystem output with the number of competitions and practice time. The model results were highly consistent with the judgment of three expert running coaches (r>0.88, p<0.001) and also with five other expert running coaches (r>0.86, p<0.001). From the expert’s knowledge and the fuzzy model, running experience is beyond the so-called "10-year rule" and depends not only on practice time, but on the quality of practice (training volume and frequency) and participation in competitions. The fuzzy rule-based model was very reliable, valid, deals with the marked ambiguities inherent in the judgment of experience and has potential applications in research, sports training, and clinical settings. PMID:28817655

Neural network based optimal control of HVAC&R systems

NASA Astrophysics Data System (ADS)

Ning, Min

Heating, Ventilation, Air-Conditioning and Refrigeration (HVAC&R) systems have wide applications in providing a desired indoor environment for different types of buildings. It is well acknowledged that 30%-40% of the total energy generated is consumed by buildings and HVAC&R systems alone account for more than 50% of the building energy consumption. Low operational efficiency especially under partial load conditions and poor control are part of reasons for such high energy consumption. To improve energy efficiency, HVAC&R systems should be properly operated to maintain a comfortable and healthy indoor environment under dynamic ambient and indoor conditions with the least energy consumption. This research focuses on the optimal operation of HVAC&R systems. The optimization problem is formulated and solved to find the optimal set points for the chilled water supply temperature, discharge air temperature and AHU (air handling unit) fan static pressure such that the indoor environment is maintained with the least chiller and fan energy consumption. To achieve this objective, a dynamic system model is developed first to simulate the system behavior under different control schemes and operating conditions. The system model is modular in structure, which includes a water-cooled vapor compression chiller model and a two-zone VAV system model. A fuzzy-set based extended transformation approach is then applied to investigate the uncertainties of this model caused by uncertain parameters and the sensitivities of the control inputs with respect to the interested model outputs. A multi-layer feed forward neural network is constructed and trained in unsupervised mode to minimize the cost function which is comprised of overall energy cost and penalty cost when one or more constraints are violated. After training, the network is implemented as a supervisory controller to compute the optimal settings for the system. In order to implement the optimal set points predicted by the supervisory controller, a set of five adaptive PI (proportional-integral) controllers are designed for each of the five local control loops of the HVAC&R system. The five controllers are used to track optimal set points and zone air temperature set points. Parameters of these PI controllers are tuned online to reduce tracking errors. The updating rules are derived from Lyapunov stability analysis. Simulation results show that compared to the conventional night reset operation scheme, the optimal operation scheme saves around 10% energy under full load condition and 19% energy under partial load conditions.

Anticipatory Monitoring and Control of Complex Systems using a Fuzzy based Fusion of Support Vector Regressors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miltiadis Alamaniotis; Vivek Agarwal

This paper places itself in the realm of anticipatory systems and envisions monitoring and control methods being capable of making predictions over system critical parameters. Anticipatory systems allow intelligent control of complex systems by predicting their future state. In the current work, an intelligent model aimed at implementing anticipatory monitoring and control in energy industry is presented and tested. More particularly, a set of support vector regressors (SVRs) are trained using both historical and observed data. The trained SVRs are used to predict the future value of the system based on current operational system parameter. The predicted values are thenmore » inputted to a fuzzy logic based module where the values are fused to obtain a single value, i.e., final system output prediction. The methodology is tested on real turbine degradation datasets. The outcome of the approach presented in this paper highlights the superiority over single support vector regressors. In addition, it is shown that appropriate selection of fuzzy sets and fuzzy rules plays an important role in improving system performance.« less

Sootblowing optimization for improved boiler performance

DOEpatents

James, John Robert; McDermott, John; Piche, Stephen; Pickard, Fred; Parikh, Neel J.

2012-12-25

A sootblowing control system that uses predictive models to bridge the gap between sootblower operation and boiler performance goals. The system uses predictive modeling and heuristics (rules) associated with different zones in a boiler to determine an optimal sequence of sootblower operations and achieve boiler performance targets. The system performs the sootblower optimization while observing any operational constraints placed on the sootblowers.

Sootblowing optimization for improved boiler performance

DOEpatents

James, John Robert; McDermott, John; Piche, Stephen; Pickard, Fred; Parikh, Neel J

2013-07-30

A sootblowing control system that uses predictive models to bridge the gap between sootblower operation and boiler performance goals. The system uses predictive modeling and heuristics (rules) associated with different zones in a boiler to determine an optimal sequence of sootblower operations and achieve boiler performance targets. The system performs the sootblower optimization while observing any operational constraints placed on the sootblowers.

Team Training through Communications Control

DTIC Science & Technology

1982-02-01

training * operational environment * team training research issues * training approach * team communications * models of operator beharior e...on the market soon, it certainly would be investigated carefully for its applicability to the team training problem. ce A text-to-speech voice...generation system. Votrax has recently marketed such a device, and others may soon follow suit. ’ d. A speech replay system designed to produce speech from

Rules based process window OPC

NASA Astrophysics Data System (ADS)

O'Brien, Sean; Soper, Robert; Best, Shane; Mason, Mark

2008-03-01

As a preliminary step towards Model-Based Process Window OPC we have analyzed the impact of correcting post-OPC layouts using rules based methods. Image processing on the Brion Tachyon was used to identify sites where the OPC model/recipe failed to generate an acceptable solution. A set of rules for 65nm active and poly were generated by classifying these failure sites. The rules were based upon segment runlengths, figure spaces, and adjacent figure widths. 2.1 million sites for active were corrected in a small chip (comparing the pre and post rules based operations), and 59 million were found at poly. Tachyon analysis of the final reticle layout found weak margin sites distinct from those sites repaired by rules-based corrections. For the active layer more than 75% of the sites corrected by rules would have printed without a defect indicating that most rulesbased cleanups degrade the lithographic pattern. Some sites were missed by the rules based cleanups due to either bugs in the DRC software or gaps in the rules table. In the end dramatic changes to the reticle prevented catastrophic lithography errors, but this method is far too blunt. A more subtle model-based procedure is needed changing only those sites which have unsatisfactory lithographic margin.

The effects of cumulative practice on mathematics problem solving.

PubMed

Mayfield, Kristin H; Chase, Philip N

2002-01-01

This study compared three different methods of teaching five basic algebra rules to college students. All methods used the same procedures to teach the rules and included four 50-question review sessions interspersed among the training of the individual rules. The differences among methods involved the kinds of practice provided during the four review sessions. Participants who received cumulative practice answered 50 questions covering a mix of the rules learned prior to each review session. Participants who received a simple review answered 50 questions on one previously trained rule. Participants who received extra practice answered 50 extra questions on the rule they had just learned. Tests administered after each review included new questions for applying each rule (application items) and problems that required novel combinations of the rules (problem-solving items). On the final test, the cumulative group outscored the other groups on application and problem-solving items. In addition, the cumulative group solved the problem-solving items significantly faster than the other groups. These results suggest that cumulative practice of component skills is an effective method of training problem solving.

The effects of cumulative practice on mathematics problem solving.

PubMed Central

Mayfield, Kristin H; Chase, Philip N

2002-01-01

This study compared three different methods of teaching five basic algebra rules to college students. All methods used the same procedures to teach the rules and included four 50-question review sessions interspersed among the training of the individual rules. The differences among methods involved the kinds of practice provided during the four review sessions. Participants who received cumulative practice answered 50 questions covering a mix of the rules learned prior to each review session. Participants who received a simple review answered 50 questions on one previously trained rule. Participants who received extra practice answered 50 extra questions on the rule they had just learned. Tests administered after each review included new questions for applying each rule (application items) and problems that required novel combinations of the rules (problem-solving items). On the final test, the cumulative group outscored the other groups on application and problem-solving items. In addition, the cumulative group solved the problem-solving items significantly faster than the other groups. These results suggest that cumulative practice of component skills is an effective method of training problem solving. PMID:12102132

76 FR 8314 - Special Conditions: Gulfstream Model GVI Airplane; Operation Without Normal Electric Power

Federal Register 2010, 2011, 2012, 2013, 2014

2011-02-14

... DEPARTMENT OF TRANSPORTATION Federal Aviation Administration 14 CFR Part 25 [Docket No. NM444 Special Conditions No. 25-11-03-SC] Special Conditions: Gulfstream Model GVI Airplane; Operation Without... Aviation Administration, Transport Airplane Directorate, Attn: Rules Docket (ANM-113), Docket No. NM444...

Digital Avionics Information System (DAIS): Training Requirements Analysis Model Users Guide. Final Report.

ERIC Educational Resources Information Center

Czuchry, Andrew J.; And Others

This user's guide describes the functions, logical operations and subroutines, input data requirements, and available outputs of the Training Requirements Analysis Model (TRAMOD), a computerized analytical life cycle cost modeling system for use in the early stages of system design. Operable in a stand-alone mode, TRAMOD can be used for the…

HyFIS: adaptive neuro-fuzzy inference systems and their application to nonlinear dynamical systems.

PubMed

Kim, J; Kasabov, N

1999-11-01

This paper proposes an adaptive neuro-fuzzy system, HyFIS (Hybrid neural Fuzzy Inference System), for building and optimising fuzzy models. The proposed model introduces the learning power of neural networks to fuzzy logic systems and provides linguistic meaning to the connectionist architectures. Heuristic fuzzy logic rules and input-output fuzzy membership functions can be optimally tuned from training examples by a hybrid learning scheme comprised of two phases: rule generation phase from data; and rule tuning phase using error backpropagation learning scheme for a neural fuzzy system. To illustrate the performance and applicability of the proposed neuro-fuzzy hybrid model, extensive simulation studies of nonlinear complex dynamic systems are carried out. The proposed method can be applied to an on-line incremental adaptive learning for the prediction and control of nonlinear dynamical systems. Two benchmark case studies are used to demonstrate that the proposed HyFIS system is a superior neuro-fuzzy modelling technique.

Topic categorisation of statements in suicide notes with integrated rules and machine learning.

PubMed

Kovačević, Aleksandar; Dehghan, Azad; Keane, John A; Nenadic, Goran

2012-01-01

We describe and evaluate an automated approach used as part of the i2b2 2011 challenge to identify and categorise statements in suicide notes into one of 15 topics, including Love, Guilt, Thankfulness, Hopelessness and Instructions. The approach combines a set of lexico-syntactic rules with a set of models derived by machine learning from a training dataset. The machine learning models rely on named entities, lexical, lexico-semantic and presentation features, as well as the rules that are applicable to a given statement. On a testing set of 300 suicide notes, the approach showed the overall best micro F-measure of up to 53.36%. The best precision achieved was 67.17% when only rules are used, whereas best recall of 50.57% was with integrated rules and machine learning. While some topics (eg, Sorrow, Anger, Blame) prove challenging, the performance for relatively frequent (eg, Love) and well-scoped categories (eg, Thankfulness) was comparatively higher (precision between 68% and 79%), suggesting that automated text mining approaches can be effective in topic categorisation of suicide notes.

On the fusion of tuning parameters of fuzzy rules and neural network

NASA Astrophysics Data System (ADS)

Mamuda, Mamman; Sathasivam, Saratha

2017-08-01

Learning fuzzy rule-based system with neural network can lead to a precise valuable empathy of several problems. Fuzzy logic offers a simple way to reach at a definite conclusion based upon its vague, ambiguous, imprecise, noisy or missing input information. Conventional learning algorithm for tuning parameters of fuzzy rules using training input-output data usually end in a weak firing state, this certainly powers the fuzzy rule and makes it insecure for a multiple-input fuzzy system. In this paper, we introduce a new learning algorithm for tuning the parameters of the fuzzy rules alongside with radial basis function neural network (RBFNN) in training input-output data based on the gradient descent method. By the new learning algorithm, the problem of weak firing using the conventional method was addressed. We illustrated the efficiency of our new learning algorithm by means of numerical examples. MATLAB R2014(a) software was used in simulating our result The result shows that the new learning method has the best advantage of training the fuzzy rules without tempering with the fuzzy rule table which allowed a membership function of the rule to be used more than one time in the fuzzy rule base.

Toward an embedded training tool for Deep Space Network operations

NASA Technical Reports Server (NTRS)

Hill, Randall W., Jr.; Sturdevant, Kathryn F.; Johnson, W. L.

1993-01-01

There are three issues to consider when building an embedded training system for a task domain involving the operation of complex equipment: (1) how skill is acquired in the task domain; (2) how the training system should be designed to assist in the acquisition of the skill, and more specifically, how an intelligent tutor could aid in learning; and (3) whether it is feasible to incorporate the resulting training system into the operational environment. This paper describes how these issues have been addressed in a prototype training system that was developed for operations in NASA's Deep Space Network (DSN). The first two issues were addressed by building an executable cognitive model of problem solving and skill acquisition of the task domain and then using the model to design an intelligent tutor. The cognitive model was developed in Soar for the DSN's Link Monitor and Control (LMC) system; it led to several insights about learning in the task domain that were used to design an intelligent tutor called REACT that implements a method called 'impasse-driven tutoring'. REACT is one component of the LMC training system, which also includes a communications link simulator and a graphical user interface. A pilot study of the LMC training system indicates that REACT shows promise as an effective way for helping operators to quickly acquire expert skills.

Simulation of longitudinal dynamics of long freight trains in positioning operations

NASA Astrophysics Data System (ADS)

Qi, Zhaohui; Huang, Zhihao; Kong, Xianchao

2012-09-01

Positioning operations are performed in a railway goods yard, in which the freight train is pulled precisely at a specific point by a positioner. The positioner moves strictly according to the predesigned speed and provides all the traction and braking forces which are highly dependent on the longitudinal dynamic response. In order to improve the efficiency and protect the wagons from damage during positioning operations, the design speed of the positioner has to be optimised based on the simulation of longitudinal train dynamics. However, traditional models of longitudinal train dynamics are not accurate enough in some aspects. In this study, we make some changes in the traditional theory to make it suitable for the study of long freight trains in positioning operations. In the proposed method, instead of the traction force on the train, the motion of the positioner is assumed to be known; more importantly, the traditional draft gear model with nonlinear spring and linear damping is replaced by a more detailed model based on the achievement of contact and impact mechanics; the switching effects of the resistance and the coupler slack are also taken into consideration. Numerical examples that deal with positioning operations on the straight lines, slope lines and curving lines are given.

Hierarchy-associated semantic-rule inference framework for classifying indoor scenes

NASA Astrophysics Data System (ADS)

Yu, Dan; Liu, Peng; Ye, Zhipeng; Tang, Xianglong; Zhao, Wei

2016-03-01

Typically, the initial task of classifying indoor scenes is challenging, because the spatial layout and decoration of a scene can vary considerably. Recent efforts at classifying object relationships commonly depend on the results of scene annotation and predefined rules, making classification inflexible. Furthermore, annotation results are easily affected by external factors. Inspired by human cognition, a scene-classification framework was proposed using the empirically based annotation (EBA) and a match-over rule-based (MRB) inference system. The semantic hierarchy of images is exploited by EBA to construct rules empirically for MRB classification. The problem of scene classification is divided into low-level annotation and high-level inference from a macro perspective. Low-level annotation involves detecting the semantic hierarchy and annotating the scene with a deformable-parts model and a bag-of-visual-words model. In high-level inference, hierarchical rules are extracted to train the decision tree for classification. The categories of testing samples are generated from the parts to the whole. Compared with traditional classification strategies, the proposed semantic hierarchy and corresponding rules reduce the effect of a variable background and improve the classification performance. The proposed framework was evaluated on a popular indoor scene dataset, and the experimental results demonstrate its effectiveness.

Input and Age-Dependent Variation in Second Language Learning: A Connectionist Account.

PubMed

Janciauskas, Marius; Chang, Franklin

2017-07-26

Language learning requires linguistic input, but several studies have found that knowledge of second language (L2) rules does not seem to improve with more language exposure (e.g., Johnson & Newport, 1989). One reason for this is that previous studies did not factor out variation due to the different rules tested. To examine this issue, we reanalyzed grammaticality judgment scores in Flege, Yeni-Komshian, and Liu's (1999) study of L2 learners using rule-related predictors and found that, in addition to the overall drop in performance due to a sensitive period, L2 knowledge increased with years of input. Knowledge of different grammar rules was negatively associated with input frequency of those rules. To better understand these effects, we modeled the results using a connectionist model that was trained using Korean as a first language (L1) and then English as an L2. To explain the sensitive period in L2 learning, the model's learning rate was reduced in an age-related manner. By assigning different learning rates for syntax and lexical learning, we were able to model the difference between early and late L2 learners in input sensitivity. The model's learning mechanism allowed transfer between the L1 and L2, and this helped to explain the differences between different rules in the grammaticality judgment task. This work demonstrates that an L1 model of learning and processing can be adapted to provide an explicit account of how the input and the sensitive period interact in L2 learning. © 2017 The Authors. Cognitive Science - A Multidisciplinary Journal published by Wiley Periodicals, Inc.

Rapid prototyping model for percutaneous nephrolithotomy training.

PubMed

Bruyère, Franck; Leroux, Cecile; Brunereau, Laurent; Lermusiaux, Patrick

2008-01-01

Rapid prototyping is a technique used for creating computer images in three dimensions more efficiently than classic techniques. Percutaneous nephrolithotomy (PCNL) is a popular method to remove kidney stones; however, broader use by the urologic community has been hampered by the morbidity associated with needle puncture to gain access to the renal calix (bleeding, pneumothorax, hydrothorax, inadvertent colon injury). A training model to improve technique and understanding of renal anatomy could improve complications related to renal puncture; however, no model currently exists for resident training. We created a training model using the rapid prototyping technique based on abdominal CT images of a patient scheduled to undergo PCNL. This allowed our staff and residents to train on the model before performing the operation. This model allowed anticipation of particular difficulties inherent to the patient's anatomy. After training, the procedure proceeded without complication, and the patient was discharged at postoperative day 1 without problems. We hypothesize that rapid prototyping could be useful for resident education, allowing the creation of numerous models for research and surgical training. In addition, we anticipate that experienced urologists could find this technique helpful in preparation for difficult PCNL operations.

Training simulator for retinal laser photocoagulation: a new approach for surgeons' apprenticeships

NASA Astrophysics Data System (ADS)

Dubois, Patrick; Meseure, Philippe; Peugnet, Frederic; Rouland, Jean-Francois

1998-06-01

Retinal laser photocoagulation is a current practice in many eye diseases therapy. Its mastering requires a specific training usually made on actual patients with some risks. The authors present a new device aimed to deliver a complete training separated from the therapeutic practice. This training simulator is built around the actual instrument to comply with the required realism. The instrumental functionalities of the device give the residents the same operating conditions as in the actual practice. The eye fundus visualization is simulated by virtual images, based on actual fundus pictures. They are computed at the rate of 10-12 frames/second according to the adjustments and manipulations of the 3-mirror lens made by the operator. All the pictures are combined in a fundus database planned to collect a wide variety of pathologies. The pedagogical functionalities are gathered in the user's interface. The two major guidelines of the developed software was to achieve an easy to use interface and to enforce no 'school dependent' rules of valuation. This new pedagogical instrument runs on PC micro-computers which allows a low- cost technology and could provide a practical training to retinal photocoagulation without the patient. A clinical validation of its pedagogical efficiency is submitted in another abstract.

Naturalistic Decision Making for Power System Operators

DOE Office of Scientific and Technical Information (OSTI.GOV)

Greitzer, Frank L.; Podmore, Robin; Robinson, Marck

2010-02-01

Motivation – Investigations of large-scale outages in the North American interconnected electric system often attribute the causes to three T’s: Trees, Training and Tools. To document and understand the mental processes used by expert operators when making critical decisions, a naturalistic decision making (NDM) model was developed. Transcripts of conversations were analyzed to reveal and assess NDM-based performance criteria. Findings/Design – An item analysis indicated that the operators’ Situation Awareness Levels, mental models, and mental simulations can be mapped at different points in the training scenario. This may identify improved training methods or analytical/ visualization tools. Originality/Value – This studymore » applies for the first time, the concepts of Recognition Primed Decision Making, Situation Awareness Levels and Cognitive Task Analysis to training of electric power system operators. Take away message – The NDM approach provides a viable framework for systematic training management to accelerate learning in simulator-based training scenarios for power system operators and teams.« less

Drive Train Normal Modes Analysis for the ERDA/NASA 100-Kilowatt Wind Turbine Generator

NASA Technical Reports Server (NTRS)

Sullivan, T. L.; Miller, D. R.; Spera, D. A.

1977-01-01

Natural frequencies, as a function of power were determined using a finite element model. Operating conditions investigated were operation with a resistive electrical load and operation synchronized to an electrical utility grid. The influence of certain drive train components on frequencies and mode shapes is shown. An approximate method for obtaining drive train natural frequencies is presented.

Training Community Modeling and Simulation Business Plan: 2009 Edition

DTIC Science & Technology

2010-04-01

strategic information assurance 33 33 Provide crisis action procedures training 34 34 Provide the IC SOF-specific training at the operational level... information and products • Collaborative analysis processes • Dissemination of information throughout a command and to subordinates by redundant means...centric M&S capabilities will improve training for information warfare, assist with training for homeland defense operations, crisis -management plan- ning

Evaluation of training programs and entry-level qualifications for nuclear-power-plant control-room personnel based on the systems approach to training

DOE Office of Scientific and Technical Information (OSTI.GOV)

Haas, P M; Selby, D L; Hanley, M J

1983-09-01

This report summarizes results of research sponsored by the US Nuclear Regulatory Commission (NRC) Office of Nuclear Regulatory Research to initiate the use of the Systems Approach to Training in the evaluation of training programs and entry level qualifications for nuclear power plant (NPP) personnel. Variables (performance shaping factors) of potential importance to personnel selection and training are identified, and research to more rigorously define an operationally useful taxonomy of those variables is recommended. A high-level model of the Systems Approach to Training for use in the nuclear industry, which could serve as a model for NRC evaluation of industrymore » programs, is presented. The model is consistent with current publically stated NRC policy, with the approach being followed by the Institute for Nuclear Power Operations, and with current training technology. Checklists to be used by NRC evaluators to assess training programs for NPP control-room personnel are proposed which are based on this model.« less

Rule Extracting based on MCG with its Application in Helicopter Power Train Fault Diagnosis

NASA Astrophysics Data System (ADS)

Wang, M.; Hu, N. Q.; Qin, G. J.

2011-07-01

In order to extract decision rules for fault diagnosis from incomplete historical test records for knowledge-based damage assessment of helicopter power train structure. A method that can directly extract the optimal generalized decision rules from incomplete information based on GrC was proposed. Based on semantic analysis of unknown attribute value, the granule was extended to handle incomplete information. Maximum characteristic granule (MCG) was defined based on characteristic relation, and MCG was used to construct the resolution function matrix. The optimal general decision rule was introduced, with the basic equivalent forms of propositional logic, the rules were extracted and reduction from incomplete information table. Combined with a fault diagnosis example of power train, the application approach of the method was present, and the validity of this method in knowledge acquisition was proved.

Impact of new duty-hour rules on residency training.

PubMed

Duran-Nelson, Alisa; Van Camp, Joan; Ling, Louis

2010-11-01

On the surface, changing the rules related to the number of hours residents work per day and per week sounds like a good idea. Theoretically, residents who work fewer hours would be less tired and provide better patient care. But even small changes in residency training programs have implications for the quality of the educational experience and the cost of training, as well as patient care. This article highlights the challenges that two Minnesota residency programs are facing as they adapt to the new rules around residents' work hours.

Separation of Sperm Whale Click-Trains for Multipath Rejection and Localization

DTIC Science & Technology

2010-03-05

Correlation 12 3.3 Multipath Elimination Rules 13 4 LOCALIZATION 15 4.1 Localization Approach 15 4.2 Inter-Sensor Time-Delay Estimation Approach...Using Bayes’ rule , kj = ’°g kj = >°g< P(H, P(H0 HJ) \\J) (2) />(//,)p(zJ//,) p(H0)p(z,JH0) where p(//o) and p(H\\) are the a priori probabilities...overlapping clicks.) 3.3 MULTIPATH ELIMINATION RULES Multipath click-trains are eliminated if the individual clicks within the click-train are

Education and Training for TANF Recipients: Opportunities and Challenges under the Final Rule

ERIC Educational Resources Information Center

Lower-Basch, Elizabeth

2008-01-01

On February 5, 2008, the U.S. Department of Health and Human Services (HHS) published the final rules implementing changes in the Temporary Assistance for Needy Families (TANF) program made by the Deficit Reduction Act of 2005 (DRA). While these rules do not affect the overall statutory limitations on counting education and training toward the…

Supraspinal Control Predicts Locomotor Function and Forecasts Responsiveness to Training after Spinal Cord Injury

PubMed Central

Field-Fote, Edelle C.; Yang, Jaynie F.; Basso, D. Michele; Gorassini, Monica A.

2017-01-01

Abstract Restoration of walking ability is an area of great interest in the rehabilitation of persons with spinal cord injury. Because many cortical, subcortical, and spinal neural centers contribute to locomotor function, it is important that intervention strategies be designed to target neural elements at all levels of the neuraxis that are important for walking ability. While to date most strategies have focused on activation of spinal circuits, more recent studies are investigating the value of engaging supraspinal circuits. Despite the apparent potential of pharmacological, biological, and genetic approaches, as yet none has proved more effective than physical therapeutic rehabilitation strategies. By making optimal use of the potential of the nervous system to respond to training, strategies can be developed that meet the unique needs of each person. To complement the development of optimal training interventions, it is valuable to have the ability to predict future walking function based on early clinical presentation, and to forecast responsiveness to training. A number of clinical prediction rules and association models based on common clinical measures have been developed with the intent, respectively, to predict future walking function based on early clinical presentation, and to delineate characteristics associated with responsiveness to training. Further, a number of variables that are correlated with walking function have been identified. Not surprisingly, most of these prediction rules, association models, and correlated variables incorporate measures of volitional lower extremity strength, illustrating the important influence of supraspinal centers in the production of walking behavior in humans. PMID:27673569

Development and Application of a Taiwan Domestic Generalized Water Supply Model

NASA Astrophysics Data System (ADS)

Ho, C. C.; Chang, L. C.

2016-12-01

Water allocation in Taiwan is more complicated than other countries because high river turbidity caused by rainstorm, reservoir management governed by different organization and conjunctive use of inter-basin reservoirs and dams. Those properties cause water resource planners need make extra effort on developing customized model to simulate the impact of water supply strategies on water resources. Hence, the study develops a Generalized Water Supply Model (GWSM) to analysis Multi-reservoirs water allocation in Taiwan for advancing the planning process. The model has following functions: (1) considering reservoirs operating rule curve. (2) considering the rule of multi-reservoir operation. Such as setting supply priority of different reservoirs or using "index balance" rule. (3) considering optimal hydroelectric power operation. (4) estimating the impact of high river turbidity on water supply. (5) considering the supply priority of different water use. (6) considering irrigation supply under special constraint. Such as the maximum irrigation supply is subject to natural inflow without reservoir storage. (7) considering two-way conduit transport. (8) considering environmental flow reservation. Conjunctive use Taan and Dajia Rivers was selected to demonstrate the ability of GWSM. The results also can be provided to different authorities to realize the impact of different strategies and that is good for negotiation and reaching a consensus.

Biologically plausible learning in recurrent neural networks reproduces neural dynamics observed during cognitive tasks

PubMed Central

Miconi, Thomas

2017-01-01

Neural activity during cognitive tasks exhibits complex dynamics that flexibly encode task-relevant variables. Chaotic recurrent networks, which spontaneously generate rich dynamics, have been proposed as a model of cortical computation during cognitive tasks. However, existing methods for training these networks are either biologically implausible, and/or require a continuous, real-time error signal to guide learning. Here we show that a biologically plausible learning rule can train such recurrent networks, guided solely by delayed, phasic rewards at the end of each trial. Networks endowed with this learning rule can successfully learn nontrivial tasks requiring flexible (context-dependent) associations, memory maintenance, nonlinear mixed selectivities, and coordination among multiple outputs. The resulting networks replicate complex dynamics previously observed in animal cortex, such as dynamic encoding of task features and selective integration of sensory inputs. We conclude that recurrent neural networks offer a plausible model of cortical dynamics during both learning and performance of flexible behavior. DOI: http://dx.doi.org/10.7554/eLife.20899.001 PMID:28230528

Biologically plausible learning in recurrent neural networks reproduces neural dynamics observed during cognitive tasks.

PubMed

Miconi, Thomas

2017-02-23

Neural activity during cognitive tasks exhibits complex dynamics that flexibly encode task-relevant variables. Chaotic recurrent networks, which spontaneously generate rich dynamics, have been proposed as a model of cortical computation during cognitive tasks. However, existing methods for training these networks are either biologically implausible, and/or require a continuous, real-time error signal to guide learning. Here we show that a biologically plausible learning rule can train such recurrent networks, guided solely by delayed, phasic rewards at the end of each trial. Networks endowed with this learning rule can successfully learn nontrivial tasks requiring flexible (context-dependent) associations, memory maintenance, nonlinear mixed selectivities, and coordination among multiple outputs. The resulting networks replicate complex dynamics previously observed in animal cortex, such as dynamic encoding of task features and selective integration of sensory inputs. We conclude that recurrent neural networks offer a plausible model of cortical dynamics during both learning and performance of flexible behavior.

Surveillance system and method having parameter estimation and operating mode partitioning

NASA Technical Reports Server (NTRS)

Bickford, Randall L. (Inventor)

2003-01-01

A system and method for monitoring an apparatus or process asset including partitioning an unpartitioned training data set into a plurality of training data subsets each having an operating mode associated thereto; creating a process model comprised of a plurality of process submodels each trained as a function of at least one of the training data subsets; acquiring a current set of observed signal data values from the asset; determining an operating mode of the asset for the current set of observed signal data values; selecting a process submodel from the process model as a function of the determined operating mode of the asset; calculating a current set of estimated signal data values from the selected process submodel for the determined operating mode; and outputting the calculated current set of estimated signal data values for providing asset surveillance and/or control.

Apollo experience report: The role of flight mission rules in mission preparation and conduct

NASA Technical Reports Server (NTRS)

Keyser, L. W.

1974-01-01

The development of flight mission rules from the mission development phase through the detailed mission-planning phase and through the testing and training phase is analyzed. The procedure for review of the rules and the coordination requirements for mission-rule development are presented. The application of the rules to real-time decision making is outlined, and consideration is given to the benefit of training ground controllers and flightcrews in the methods of determining the best response to a nonnominal in-flight situation for which no action has been preplanned. The Flight Mission Rules document is discussed in terms of the purpose and objective thereof and in terms of the definition, the development, and the use of mission rules.

Digital Gunnery: How Combat Vehicle Gunnery Training Creates a Model for Training the Mission Command System.

DTIC Science & Technology

2017-06-09

DIGITAL GUNNERY: HOW COMBAT VEHICLE GUNNERY TRAINING CREATES A MODEL FOR TRAINING THE MISSION COMMAND SYSTEM A thesis presented...Training Creates a Model for Training the Mission Command System 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S...digital systems that give commanders an unprecedented ability to understand and lead in the battlefields where they operate. Unfortunately, units

47 CFR 95.207 - (R/C Rule 7) On what channels may I operate?

Code of Federal Regulations, 2011 CFR

2011-10-01

... object or apparatus, except an R/C transmitter), including a model aircraft device (any small imitation of an aircraft) or a model surface craft device (any small imitation of a boat, car or vehicle for...) The following channels may only be used to operate a model aircraft device: MHz 72.01 72.03 72.05 72...

40 CFR 60.1680 - After the required date for operator certification, who may operate the municipal waste...

Code of Federal Regulations, 2012 CFR

2012-07-01

... certification, who may operate the municipal waste combustion unit? 60.1680 Section 60.1680 Protection of... NEW STATIONARY SOURCES Emission Guidelines and Compliance Times for Small Municipal Waste Combustion Units Constructed on or Before August 30, 1999 Model Rule-Good Combustion Practices: Operator...

40 CFR 60.1680 - After the required date for operator certification, who may operate the municipal waste...

Code of Federal Regulations, 2011 CFR

2011-07-01

... certification, who may operate the municipal waste combustion unit? 60.1680 Section 60.1680 Protection of... NEW STATIONARY SOURCES Emission Guidelines and Compliance Times for Small Municipal Waste Combustion Units Constructed on or Before August 30, 1999 Model Rule-Good Combustion Practices: Operator...

40 CFR 60.1680 - After the required date for operator certification, who may operate the municipal waste...

Code of Federal Regulations, 2013 CFR

2013-07-01

... certification, who may operate the municipal waste combustion unit? 60.1680 Section 60.1680 Protection of... NEW STATIONARY SOURCES Emission Guidelines and Compliance Times for Small Municipal Waste Combustion Units Constructed on or Before August 30, 1999 Model Rule-Good Combustion Practices: Operator...

40 CFR 60.1680 - After the required date for operator certification, who may operate the municipal waste...

Code of Federal Regulations, 2014 CFR

2014-07-01

... certification, who may operate the municipal waste combustion unit? 60.1680 Section 60.1680 Protection of... NEW STATIONARY SOURCES Emission Guidelines and Compliance Times for Small Municipal Waste Combustion Units Constructed on or Before August 30, 1999 Model Rule-Good Combustion Practices: Operator...

40 CFR 60.1680 - After the required date for operator certification, who may operate the municipal waste...

Code of Federal Regulations, 2010 CFR

2010-07-01

... certification, who may operate the municipal waste combustion unit? 60.1680 Section 60.1680 Protection of... NEW STATIONARY SOURCES Emission Guidelines and Compliance Times for Small Municipal Waste Combustion Units Constructed on or Before August 30, 1999 Model Rule-Good Combustion Practices: Operator...

Fuzzy multiobjective models for optimal operation of a hydropower system

NASA Astrophysics Data System (ADS)

Teegavarapu, Ramesh S. V.; Ferreira, André R.; Simonovic, Slobodan P.

2013-06-01

Optimal operation models for a hydropower system using new fuzzy multiobjective mathematical programming models are developed and evaluated in this study. The models use (i) mixed integer nonlinear programming (MINLP) with binary variables and (ii) integrate a new turbine unit commitment formulation along with water quality constraints used for evaluation of reservoir downstream impairment. Reardon method used in solution of genetic algorithm optimization problems forms the basis for development of a new fuzzy multiobjective hydropower system optimization model with creation of Reardon type fuzzy membership functions. The models are applied to a real-life hydropower reservoir system in Brazil. Genetic Algorithms (GAs) are used to (i) solve the optimization formulations to avoid computational intractability and combinatorial problems associated with binary variables in unit commitment, (ii) efficiently address Reardon method formulations, and (iii) deal with local optimal solutions obtained from the use of traditional gradient-based solvers. Decision maker's preferences are incorporated within fuzzy mathematical programming formulations to obtain compromise operating rules for a multiobjective reservoir operation problem dominated by conflicting goals of energy production, water quality and conservation releases. Results provide insight into compromise operation rules obtained using the new Reardon fuzzy multiobjective optimization framework and confirm its applicability to a variety of multiobjective water resources problems.

HaLT: A computerized training program for hardwood lumber graders

Treesearch

P. Klinkhachorn; C.J. Schwehm; Charles W. McMillin; H.A. Huber

1989-01-01

A computer program for training both novice and experienced hardwood lumber graders in accordance with the National Hardwood Lumber Association (NHLA) rules is presented. It is anticipated that this program will help alleviate the problems of improper grading by improved and continued training and make lumber manufacturers and purchasers more knowledgeable of the rules...

Testing algorithms for a passenger train braking performance model.

DOT National Transportation Integrated Search

2011-09-01

"The Federal Railroad Administrations Office of Research and Development funded a project to establish performance model to develop, analyze, and test positive train control (PTC) braking algorithms for passenger train operations. With a good brak...

Operative and diagnostic hysteroscopy: A novel learning model combining new animal models and virtual reality simulation.

PubMed

Bassil, Alfred; Rubod, Chrystèle; Borghesi, Yves; Kerbage, Yohan; Schreiber, Elie Servan; Azaïs, Henri; Garabedian, Charles

2017-04-01

Hysteroscopy is one of the most common gynaecological procedure. Training for diagnostic and operative hysteroscopy can be achieved through numerous previously described models like animal models or virtual reality simulation. We present our novel combined model associating virtual reality and bovine uteruses and bladders. End year residents in obstetrics and gynaecology attended a full day workshop. The workshop was divided in theoretical courses from senior surgeons and hands-on training in operative hysteroscopy and virtual reality Essure ® procedures using the EssureSim™ and Pelvicsim™ simulators with multiple scenarios. Theoretical and operative knowledge was evaluated before and after the workshop and General Points Averages (GPAs) were calculated and compared using a Student's T test. GPAs were significantly higher after the workshop was completed. The biggest difference was observed in operative knowledge (0,28 GPA before workshop versus 0,55 after workshop, p<0,05). All of the 25 residents having completed the workshop applauded the realism an efficiency of this type of training. The force feedback allowed by the cattle uteruses gives the residents the possibility to manage thickness of resection as in real time surgery. Furthermore, the two-horned bovine uteruses allowed to reproduce septa resection in conditions close to human surgery CONCLUSION: Teaching operative and diagnostic hysteroscopy is essential. Managing this training through a full day workshop using a combined animal model and virtual reality simulation is an efficient model not described before. Copyright © 2017 Elsevier B.V. All rights reserved.

Influence evaluation of loading conditions during pressurized thermal shock transients based on thermal-hydraulics and structural analyses

NASA Astrophysics Data System (ADS)

Katsuyama, Jinya; Uno, Shumpei; Watanabe, Tadashi; Li, Yinsheng

2018-03-01

The thermal hydraulic (TH) behavior of coolant water is a key factor in the structural integrity assessments on reactor pressure vessels (RPVs) of pressurized water reactors (PWRs) under pressurized thermal shock (PTS) events, because the TH behavior may affect the loading conditions in the assessment. From the viewpoint of TH behavior, configuration of plant equipment and their dimensions, and operator action time considerably influence various parameters, such as the temperature and flow rate of coolant water and inner pressure. In this study, to investigate the influence of the operator action time on TH behavior during a PTS event, we developed an analysis model for a typical Japanese PWR plant, including the RPV and the main components of both primary and secondary systems, and performed TH analyses by using a system analysis code called RELAP5. We applied two different operator action times based on the Japanese and the United States (US) rules: Operators may act after 10 min (Japanese rules) and 30 min (the US rules) after the occurrence of PTS events. Based on the results of TH analysis with different operator action times, we also performed structural analyses for evaluating thermal-stress distributions in the RPV during PTS events as loading conditions in the structural integrity assessment. From the analysis results, it was clarified that differences in operator action times significantly affect TH behavior and loading conditions, as the Japanese rule may lead to lower stresses than that under the US rule because an earlier operator action caused lower pressure in the RPV.

Towards a Semantically-Enabled Control Strategy for Building Simulations: Integration of Semantic Technologies and Model Predictive Control

DOE Office of Scientific and Technical Information (OSTI.GOV)

Delgoshaei, Parastoo; Austin, Mark A.; Pertzborn, Amanda J.

State-of-the-art building simulation control methods incorporate physical constraints into their mathematical models, but omit implicit constraints associated with policies of operation and dependency relationships among rules representing those constraints. To overcome these shortcomings, there is a recent trend in enabling the control strategies with inference-based rule checking capabilities. One solution is to exploit semantic web technologies in building simulation control. Such approaches provide the tools for semantic modeling of domains, and the ability to deduce new information based on the models through use of Description Logic (DL). In a step toward enabling this capability, this paper presents a cross-disciplinary data-drivenmore » control strategy for building energy management simulation that integrates semantic modeling and formal rule checking mechanisms into a Model Predictive Control (MPC) formulation. The results show that MPC provides superior levels of performance when initial conditions and inputs are derived from inference-based rules.« less

14 CFR 133.33 - Operating rules.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 3 2010-01-01 2010-01-01 false Operating rules. 133.33 Section 133.33... OPERATIONS Operating Rules and Related Requirements § 133.33 Operating rules. (a) No person may conduct a... prescribed in § 133.47. (b) No person may conduct a rotorcraft external-load operation unless— (1) The...

Corporate culture, compliance and railroad operating rules

DOT National Transportation Integrated Search

1997-12-01

A focus group was held at the 1996 Bi-annual Operating Rules Association meeting of North American railroads to discuss the : general issue of compliance and operating rules. Twelve operating rules officers participated, representing Class I, II, and...

Model simulation of the Manasquan water-supply system in Monmouth County, New Jersey

USGS Publications Warehouse

Chang, Ming; Tasker, Gary D.; Nieswand, Steven

2001-01-01

Model simulation of the Manasquan Water Supply System in Monmouth County, New Jersey, was completed using historic hydrologic data to evaluate the effects of operational and withdrawal alternatives on the Manasquan reservoir and pumping system. Changes in the system operations can be simulated with the model using precipitation forecasts. The Manasquan Reservoir system model operates by using daily streamflow values, which were reconstructed from historical U.S. Geological Survey streamflow-gaging station records. The model is able to run in two modes--General Risk analysis Model (GRAM) and Position Analysis Model (POSA). The GRAM simulation procedure uses reconstructed historical streamflow records to provide probability estimates of certain events, such as reservoir storage levels declining below a specific level, when given an assumed set of operating rules and withdrawal rates. POSA can be used to forecast the likelihood of specified outcomes, such as streamflows falling below statutory passing flows, associated with a specific working plan for the water-supply system over a period of months. The user can manipulate the model and generate graphs and tables of streamflows and storage, for example. This model can be used as a management tool to facilitate the development of drought warning and drought emergency rule curves and safe yield values for the water-supply system.

New scheduling rules for a dynamic flexible flow line problem with sequence-dependent setup times

NASA Astrophysics Data System (ADS)

Kia, Hamidreza; Ghodsypour, Seyed Hassan; Davoudpour, Hamid

2017-09-01

In the literature, the application of multi-objective dynamic scheduling problem and simple priority rules are widely studied. Although these rules are not efficient enough due to simplicity and lack of general insight, composite dispatching rules have a very suitable performance because they result from experiments. In this paper, a dynamic flexible flow line problem with sequence-dependent setup times is studied. The objective of the problem is minimization of mean flow time and mean tardiness. A 0-1 mixed integer model of the problem is formulated. Since the problem is NP-hard, four new composite dispatching rules are proposed to solve it by applying genetic programming framework and choosing proper operators. Furthermore, a discrete-event simulation model is made to examine the performances of scheduling rules considering four new heuristic rules and the six adapted heuristic rules from the literature. It is clear from the experimental results that composite dispatching rules that are formed from genetic programming have a better performance in minimization of mean flow time and mean tardiness than others.

Laparoscopic surgical box model training for surgical trainees with limited prior laparoscopic experience.

PubMed

Gurusamy, Kurinchi Selvan; Nagendran, Myura; Toon, Clare D; Davidson, Brian R

2014-03-01

Surgical training has traditionally been one of apprenticeship, where the surgical trainee learns to perform surgery under the supervision of a trained surgeon. This is time consuming, costly, and of variable effectiveness. Training using a box model physical simulator is an option to supplement standard training. However, the value of this modality on trainees with limited prior laparoscopic experience is unknown. To compare the benefits and harms of box model training for surgical trainees with limited prior laparoscopic experience versus standard surgical training or supplementary animal model training. We searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE, and Science Citation Index Expanded to May 2013. We planned to include all randomised clinical trials comparing box model trainers versus other forms of training including standard laparoscopic training and supplementary animal model training in surgical trainees with limited prior laparoscopic experience. We also planned to include trials comparing different methods of box model training. Two authors independently identified trials and collected data. We analysed the data with both the fixed-effect and the random-effects models using Review Manager 5. For each outcome, we calculated the risk ratio (RR), mean difference (MD), or standardised mean difference (SMD) with 95% confidence intervals (CI) based on intention-to-treat analysis whenever possible. We identified eight trials that met the inclusion criteria. One trial including 17 surgical trainees did not contribute to the meta-analysis. We included seven trials (249 surgical trainees belonging to various postgraduate years ranging from year one to four) in which the participants were randomised to supplementary box model training (122 trainees) versus standard training (127 trainees). Only one trial (50 trainees) was at low risk of bias. The box trainers used in all the seven trials were video trainers. Six trials were conducted in USA and one trial in Canada. The surgeries in which the final assessments were made included laparoscopic total extraperitoneal hernia repairs, laparoscopic cholecystectomy, laparoscopic tubal ligation, laparoscopic partial salpingectomy, and laparoscopic bilateral mid-segment salpingectomy. The final assessments were made on a single operative procedure.There were no deaths in three trials (0/82 (0%) supplementary box model training versus 0/86 (0%) standard training; RR not estimable; very low quality evidence). The other trials did not report mortality. The estimated effect on serious adverse events was compatible with benefit and harm (three trials; 168 patients; 0/82 (0%) supplementary box model training versus 1/86 (1.1%) standard training; RR 0.36; 95% CI 0.02 to 8.43; very low quality evidence). None of the trials reported patient quality of life. The operating time was significantly shorter in the supplementary box model training group versus the standard training group (1 trial; 50 patients; MD -6.50 minutes; 95% CI -10.85 to -2.15). The proportion of patients who were discharged as day-surgery was significantly higher in the supplementary box model training group versus the standard training group (1 trial; 50 patients; 24/24 (100%) supplementary box model training versus 15/26 (57.7%) standard training; RR 1.71; 95% CI 1.23 to 2.37). None of the trials reported trainee satisfaction. The operating performance was significantly better in the supplementary box model training group versus the standard training group (seven trials; 249 trainees; SMD 0.84; 95% CI 0.57 to 1.10).None of the trials compared box model training versus animal model training or versus different methods of box model training. There is insufficient evidence to determine whether laparoscopic box model training reduces mortality or morbidity. There is very low quality evidence that it improves technical skills compared with standard surgical training in trainees with limited previous laparoscopic experience. It may also decrease operating time and increase the proportion of patients who were discharged as day-surgery in the first total extraperitoneal hernia repair after box model training. However, the duration of the benefit of box model training is unknown. Further well-designed trials of low risk of bias and random errors are necessary. Such trials should assess the long-term impact of box model training on clinical outcomes and compare box training with other forms of training.

Study of the Light Utility Helicopter (LUH) Acquisition Program as a Model for Defense Acquisition of Nondevelopmental Items

DTIC Science & Technology

2014-12-01

Local Economic Impact of UH-72A Manufacture ................42  viii e.  EADS’ (Now Airbus Group’s) Suppliers and Subcontractors...Headquarters, Department of the Army IFR instrument flight rules IOTE initial operational test and evaluation IR infrared KO contracting officer kt...instrument flight rules ( IFR ) and visual flight rules (VFR) capabilities, thereby allowing flight at night and under low visibility weather

How should we build a generic open-source water management simulator?

NASA Astrophysics Data System (ADS)

Khadem, M.; Meier, P.; Rheinheimer, D. E.; Padula, S.; Matrosov, E.; Selby, P. D.; Knox, S.; Harou, J. J.

2014-12-01

Increasing water needs for agriculture, industry and cities mean effective and flexible water resource system management tools will remain in high demand. Currently many regions or countries use simulators that have been adapted over time to their unique system properties and water management rules and realities. Most regions operate with a preferred short-list of water management and planning decision support systems. Is there scope for a simulator, shared within the water management community, that could be adapted to different contexts, integrate community contributions, and connect to generic data and model management software? What role could open-source play in such a project? How could a genericuser-interface and data/model management software sustainably be attached to this model or suite of models? Finally, how could such a system effectively leverage existing model formulations, modeling technologies and software? These questions are addressed by the initial work presented here. We introduce a generic water resource simulation formulation that enables and integrates both rule-based and optimization driven technologies. We suggest how it could be linked to other sub-models allowing for detailed agent-based simulation of water management behaviours. An early formulation is applied as an example to the Thames water resource system in the UK. The model uses centralised optimisation to calculate allocations but allows for rule-based operations as well in an effort to represent observed behaviours and rules with fidelity. The model is linked through import/export commands to a generic network model platform named Hydra. Benefits and limitations of the approach are discussed and planned work and potential use cases are outlined.

Culture and error in space: implications from analog environments.

PubMed

Helmreich, R L

2000-09-01

An ongoing study investigating national, organizational, and professional cultures in aviation and medicine is described. Survey data from 26 nations on 5 continents show highly significant national differences regarding appropriate relationships between leaders and followers, in group vs. individual orientation, and in values regarding adherence to rules and procedures. These findings replicate earlier research on dimensions of national culture. Data collected also isolate significant operational issues in multi-national flight crews. While there are no better or worse cultures, these cultural differences have operational implications for the way crews function in an international space environment. The positive professional cultures of pilots and physicians exhibit a high enjoyment of the job and professional pride. However, a negative component was also identified characterized by a sense of personal invulnerability regarding the effects of stress and fatigue on performance. This misperception of personal invulnerability has operational implications such as failures in teamwork and increased probability of error. A second component of the research examines team error in operational environments. From observational data collected during normal flight operations, new models of threat and error and their management were developed that can be generalized to operations in space and other socio-technological domains. Five categories of crew error are defined and their relationship to training programs in team performance, known generically as Crew Resource Management, is described. The relevance of these data for future spaceflight is discussed.

Training Fires on Indian Reservations in Idaho, Oregon, and Washington

EPA Pesticide Factsheets

The Federal Air Rules for Reservations (FARR) Open Burning Rule allows Fire Protection Services to request permission from EPA to conduct an outdoor burn by qualified personnel to train firefighters on fire suppression and fire fighting techniques.

How Long Does It Take to Learn a Second Language?: Applying the "10,000-Hour Rule" as a Model for Fluency

ERIC Educational Resources Information Center

Eaton, Sarah Elaine

2011-01-01

This study applies the model of expertise developed by Ericsson et al (2007) to second and foreign language learning. Ericsson et al posits that in order to achieve expertise (as they define it) requires 10,000 or longer of "intense training". Applying this model to language learning, equating an expert level of competence with fluency, various…

Dokan Hydropower Reservoir Operation under Stochastic Conditions as Regards the Inflows and the Energy Demands

NASA Astrophysics Data System (ADS)

Izat Rashed, Ghamgeen

2018-03-01

This paper presented a way of obtaining certain operating rules on time steps for the management of a large reservoir operation with a peak hydropower plant associated to it. The rules were allowed to have the form of non-linear regression equations which link a decision variable (here the water volume in the reservoir at the end of the time step) by several parameters influencing it. This paper considered the Dokan hydroelectric development KR-Iraq, which operation data are available for. It was showing that both the monthly average inflows and the monthly power demands are random variables. A model of deterministic dynamic programming intending the minimization of the total amount of the squares differences between the demanded energy and the generated energy is run with a multitude of annual scenarios of inflows and monthly required energies. The operating rules achieved allow the efficient and safe management of the operation and it is quietly and accurately known the forecast of the inflow and of the energy demand on the next time step.

Operation of Dokan Reservoir under Stochastic Conditions as Regards the Inflows and the Energy Demands

NASA Astrophysics Data System (ADS)

Rashed, G. I.

2018-02-01

This paper presented a way of obtaining certain operating rules on time steps for the management of a large reservoir operation with a peak hydropower plant associated to it. The rules were allowed to have the form of non-linear regression equations which link a decision variable (here the water volume in the reservoir at the end of the time step) by several parameters influencing it. This paper considered the Dokan hydroelectric development KR-Iraq, which operation data are available for. It was showing that both the monthly average inflows and the monthly power demands are random variables. A model of deterministic dynamic programming intending the minimization of the total amount of the squares differences between the demanded energy and the generated energy is run with a multitude of annual scenarios of inflows and monthly required energies. The operating rules achieved allow the efficient and safe management of the operation and it is quietly and accurately known the forecast of the inflow and of the energy demand on the next time step.

The Effect of Model Grid Resolution on the Distributed Hydrologic Simulations for Forecasting Stream Flows and Reservoir Storage

NASA Astrophysics Data System (ADS)

Turnbull, S. J.

2017-12-01

Within the US Army Corps of Engineers (USACE), reservoirs are typically operated according to a rule curve that specifies target water levels based on the time of year. The rule curve is intended to maximize flood protection by specifying releases of water before the dominant rainfall period for a region. While some operating allowances are permissible, generally the rule curve elevations must be maintained. While this operational approach provides for the required flood control purpose, it may not result in optimal reservoir operations for multi-use impoundments. In the Russian River Valley of California a multi-agency research effort called Forecast-Informed Reservoir Operations (FIRO) is assessing the application of forecast weather and streamflow predictions to potentially enhance the operation of reservoirs in the watershed. The focus of the study has been on Lake Mendocino, a USACE project important for flood control, water supply, power generation and ecological flows. As part of this effort the Engineer Research and Development Center is assessing the ability of utilizing the physics based, distributed watershed model Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model to simulate stream flows, reservoir stages, and discharges while being driven by weather forecast products. A key question in this application is the effect of watershed model resolution on forecasted stream flows. To help resolve this question, GSSHA models of multiple grid resolutions, 30, 50, and 270m, were developed for the upper Russian River, which includes Lake Mendocino. The models were derived from common inputs: DEM, soils, land use, stream network, reservoir characteristics, and specified inflows and discharges. All the models were calibrated in both event and continuous simulation mode using measured precipitation gages and then driven with the West-WRF atmospheric model in prediction mode to assess the ability of the model to function in short term, less than one week, forecasting mode. In this presentation we will discuss the effect the grid resolution has model development, parameter assignment, streamflow prediction and forecasting capability utilizing the West-WRF forecast hydro-meteorology.

Impact of operator experience and training strategy on procedural outcomes with leadless pacing: Insights from the Micra Transcatheter Pacing Study.

PubMed

El-Chami, Mikhael; Kowal, Robert C; Soejima, Kyoko; Ritter, Philippe; Duray, Gabor Z; Neuzil, Petr; Mont, Lluis; Kypta, Alexander; Sagi, Venkata; Hudnall, John Harrison; Stromberg, Kurt; Reynolds, Dwight

2017-07-01

Leadless pacemaker systems have been designed to avoid the need for a pocket and transvenous lead. However, delivery of this therapy requires a new catheter-based procedure. This study evaluates the role of operator experience and different training strategies on procedural outcomes. A total of 726 patients underwent implant attempt with the Micra transcatheter pacing system (TPS; Medtronic, Minneapolis, MN, USA) by 94 operators trained in a teaching laboratory using a simulator, cadaver, and large animal models (lab training) or locally at the hospital with simulator/demo model and proctorship (hospital training). Procedure success, procedure duration, fluoroscopy time, and safety outcomes were compared between training methods and experience (implant case number). The Micra TPS procedure was successful in 99.2% of attempts and did not differ between the 55 operators trained in the lab setting and the 39 operators trained locally at the hospital (P = 0.189). Implant case number was also not a determinant of procedural success (P = 0.456). Each operator performed between one and 55 procedures. Procedure time and fluoroscopy duration decreased by 2.0% (P = 0.002) and 3.2% (P < 0.001) compared to the previous case. Major complication rate and pericardial effusion rate were not associated with case number (P = 0.755 and P = 0.620, respectively). There were no differences in the safety outcomes by training method. Among a large group of operators, implantation success was high regardless of experience. While procedure duration and fluoroscopy times decreased with implant number, complications were low and not associated with case number. Procedure and safety outcomes were similar between distinct training methodologies. © 2017 Wiley Periodicals, Inc.

Classifying the Indication for Colonoscopy Procedures: A Comparison of NLP Approaches in a Diverse National Healthcare System.

PubMed

Patterson, Olga V; Forbush, Tyler B; Saini, Sameer D; Moser, Stephanie E; DuVall, Scott L

2015-01-01

In order to measure the level of utilization of colonoscopy procedures, identifying the primary indication for the procedure is required. Colonoscopies may be utilized not only for screening, but also for diagnostic or therapeutic purposes. To determine whether a colonoscopy was performed for screening, we created a natural language processing system to identify colonoscopy reports in the electronic medical record system and extract indications for the procedure. A rule-based model and three machine-learning models were created using 2,000 manually annotated clinical notes of patients cared for in the Department of Veterans Affairs. Performance of the models was measured and compared. Analysis of the models on a test set of 1,000 documents indicates that the rule-based system performance stays fairly constant as evaluated on training and testing sets. However, the machine learning model without feature selection showed significant decrease in performance. Therefore, rule-based classification system appears to be more robust than a machine-learning system in cases when no feature selection is performed.

Changes to CMS Reimbursement Rules for Intraoperative Neurophysiological Monitoring: Implications for Telemedicine

PubMed Central

2013-01-01

Abstract Intraoperative neurophysiological monitoring (IONM) is used as an adjunct for surgeries that pose risk to nervous system structures. IONM is performed by a technologist in the operating room and is overseen by a highly trained fellowship-trained physician clinical neurophysiologist. Telemedicine has allowed the professional oversight component to be done remotely, with reimbursement for multiple simultaneous cases. Recent changes to Current Procedure Terminology coding and Medicare reimbursement policies provide options only for exclusive 1:1 technologist:oversight physician billing. This policy change may create profound repercussions in the practice of telemedicine by actively discouraging the leveraging of highly specialized and scarce expertise through on-site physician extenders. PMID:23952785

Abstract rule learning in 11- and 14-month-old infants.

PubMed

Koulaguina, Elena; Shi, Rushen

2013-02-01

This study tests the hypothesis that distributional information can guide infants in the generalization of word order movement rules at the initial stage of language acquisition. Participants were 11- and 14-month-old infants. Stimuli were sentences in Russian, a language that was unknown to our infants. During training the word order of each sentence was transformed following a consistent pattern (e.g., ABC-BAC). During the test phase infants heard novel sentences that respected the trained rule and ones that violated the trained rule (i.e., a different transformation such as ABC-ACB). Stimuli words had highly variable phonological and morphological shapes. The cue available was the positional information of words and their non-adjacent relations across sentences. We found that 14-month-olds, but not 11-month-olds, showed evidence of abstract rule generalization to novel instances. The implications of this finding to early syntactic acquisition are discussed.

A Biologically Inspired Computational Model of Basal Ganglia in Action Selection.

PubMed

Baston, Chiara; Ursino, Mauro

2015-01-01

The basal ganglia (BG) are a subcortical structure implicated in action selection. The aim of this work is to present a new cognitive neuroscience model of the BG, which aspires to represent a parsimonious balance between simplicity and completeness. The model includes the 3 main pathways operating in the BG circuitry, that is, the direct (Go), indirect (NoGo), and hyperdirect pathways. The main original aspects, compared with previous models, are the use of a two-term Hebb rule to train synapses in the striatum, based exclusively on neuronal activity changes caused by dopamine peaks or dips, and the role of the cholinergic interneurons (affected by dopamine themselves) during learning. Some examples are displayed, concerning a few paradigmatic cases: action selection in basal conditions, action selection in the presence of a strong conflict (where the role of the hyperdirect pathway emerges), synapse changes induced by phasic dopamine, and learning new actions based on a previous history of rewards and punishments. Finally, some simulations show model working in conditions of altered dopamine levels, to illustrate pathological cases (dopamine depletion in parkinsonian subjects or dopamine hypermedication). Due to its parsimonious approach, the model may represent a straightforward tool to analyze BG functionality in behavioral experiments.

Application of Decision Making and Team Training Research to Operational Training. A Translative Technique.

DTIC Science & Technology

DECISION MAKING , * GROUP DYNAMICS, NAVAL TRAINING, TRANSFER OF TRAINING, SCIENTIFIC RESEARCH, CLASSIFICATION, PROBLEM SOLVING, MATHEMATICAL MODELS, SUBMARINES, SIMULATORS, PERFORMANCE(HUMAN), UNDERSEA WARFARE.

Longitudinal train dynamics: an overview

NASA Astrophysics Data System (ADS)

Wu, Qing; Spiryagin, Maksym; Cole, Colin

2016-12-01

This paper discusses the evolution of longitudinal train dynamics (LTD) simulations, which covers numerical solvers, vehicle connection systems, air brake systems, wagon dumper systems and locomotives, resistance forces and gravitational components, vehicle in-train instabilities, and computing schemes. A number of potential research topics are suggested, such as modelling of friction, polymer, and transition characteristics for vehicle connection simulations, studies of wagon dumping operations, proper modelling of vehicle in-train instabilities, and computing schemes for LTD simulations. Evidence shows that LTD simulations have evolved with computing capabilities. Currently, advanced component models that directly describe the working principles of the operation of air brake systems, vehicle connection systems, and traction systems are available. Parallel computing is a good solution to combine and simulate all these advanced models. Parallel computing can also be used to conduct three-dimensional long train dynamics simulations.

14 CFR Special Federal Aviation... - Special Operating Rules for the Conduct of Instrument Flight Rules (IFR) Area Navigation (RNAV...

Code of Federal Regulations, 2013 CFR

2013-01-01

... 14 Aeronautics and Space 2 2013-01-01 2013-01-01 false Special Operating Rules for the Conduct of Instrument Flight Rules (IFR) Area Navigation (RNAV) Operations using Global Positioning Systems (GPS) in... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL...

14 CFR Special Federal Aviation... - Special Operating Rules for the Conduct of Instrument Flight Rules (IFR) Area Navigation (RNAV...

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 2 2010-01-01 2010-01-01 false Special Operating Rules for the Conduct of Instrument Flight Rules (IFR) Area Navigation (RNAV) Operations using Global Positioning Systems (GPS) in... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL...

14 CFR Special Federal Aviation... - Special Operating Rules for the Conduct of Instrument Flight Rules (IFR) Area Navigation (RNAV...

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 2 2011-01-01 2011-01-01 false Special Operating Rules for the Conduct of Instrument Flight Rules (IFR) Area Navigation (RNAV) Operations using Global Positioning Systems (GPS) in... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL...

14 CFR Special Federal Aviation... - Special Operating Rules for the Conduct of Instrument Flight Rules (IFR) Area Navigation (RNAV...

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 2 2012-01-01 2012-01-01 false Special Operating Rules for the Conduct of Instrument Flight Rules (IFR) Area Navigation (RNAV) Operations using Global Positioning Systems (GPS) in... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL...

14 CFR Special Federal Aviation... - Special Operating Rules for the Conduct of Instrument Flight Rules (IFR) Area Navigation (RNAV...

Code of Federal Regulations, 2014 CFR

2014-01-01

... 14 Aeronautics and Space 2 2014-01-01 2014-01-01 false Special Operating Rules for the Conduct of Instrument Flight Rules (IFR) Area Navigation (RNAV) Operations using Global Positioning Systems (GPS) in... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL...

Visual artificial grammar learning: comparative research on humans, kea (Nestor notabilis) and pigeons (Columba livia)

PubMed Central

Stobbe, Nina; Westphal-Fitch, Gesche; Aust, Ulrike; Fitch, W. Tecumseh

2012-01-01

Artificial grammar learning (AGL) provides a useful tool for exploring rule learning strategies linked to general purpose pattern perception. To be able to directly compare performance of humans with other species with different memory capacities, we developed an AGL task in the visual domain. Presenting entire visual patterns simultaneously instead of sequentially minimizes the amount of required working memory. This approach allowed us to evaluate performance levels of two bird species, kea (Nestor notabilis) and pigeons (Columba livia), in direct comparison to human participants. After being trained to discriminate between two types of visual patterns generated by rules at different levels of computational complexity and presented on a computer screen, birds and humans received further training with a series of novel stimuli that followed the same rules, but differed in various visual features from the training stimuli. Most avian and all human subjects continued to perform well above chance during this initial generalization phase, suggesting that they were able to generalize learned rules to novel stimuli. However, detailed testing with stimuli that violated the intended rules regarding the exact number of stimulus elements indicates that neither bird species was able to successfully acquire the intended pattern rule. Our data suggest that, in contrast to humans, these birds were unable to master a simple rule above the finite-state level, even with simultaneous item presentation and despite intensive training. PMID:22688635

Category Learning Strategies in Younger and Older Adults: Rule Abstraction and Memorization

PubMed Central

Wahlheim, Christopher N.; McDaniel, Mark A.; Little, Jeri L.

2016-01-01

Despite the fundamental role of category learning in cognition, few studies have examined how this ability differs between younger and older adults. The present experiment examined possible age differences in category learning strategies and their effects on learning. Participants were trained on a category determined by a disjunctive rule applied to relational features. The utilization of rule- and exemplar-based strategies was indexed by self-reports and transfer performance. Based on self-reported strategies, both age groups had comparable frequencies of rule- and exemplar-based learners, but older adults had a higher frequency of intermediate learners (i.e., learners not identifying with a reliance on either rule- or exemplar-based strategies). Training performance was higher for younger than older adults regardless of the strategy utilized, showing that older adults were impaired in their ability to learn the correct rule or to remember exemplar-label associations. Transfer performance converged with strategy reports in showing higher fidelity category representations for younger adults. Younger adults with high working memory capacity were more likely to use an exemplar-based strategy, and older adults with high working memory capacity showed better training performance. Age groups did not differ in their self-reported memory beliefs, and these beliefs did not predict training strategies or performance. Overall, the present results contradict earlier findings that older adults prefer rule- to exemplar-based learning strategies, presumably to compensate for memory deficits. PMID:26950225

Luria-Delbrück Revisited: The Classic Experiment Doesn't Rule out Lamarckian Evolution

NASA Astrophysics Data System (ADS)

Holmes, Caroline; Ghafari, Mahan; Abbas, Anzar; Saravanan, Varun; Nemenman, Ilya

We re-examine data from the classic 1943 Luria-Delbruck fluctuation experiment. This experiment is often credited with establishing that phage resistance in bacteria is acquired through a Darwinian mechanism (natural selection on standing variation) rather than through a Lamarckian mechanism (environmentally induced mutations). We argue that, for the Lamarckian model of evolution to be ruled out by the experiment, the experiment must favor pure Darwinian evolution over both the Lamarckian model and a model that allows both Darwinian and Lamarckian mechanisms. Analysis of the combined model was not performed in the 1943 paper, and nor was analysis of the possibility of neither model fitting the experiment. Using Bayesian model selection, we find that: 1) all datasets from the paper favor Darwinian over purely Lamarckian evolution, 2) some of the datasets are unable to distinguish between the purely Darwinian and the combined models, and 3) the other datasets cannot be explained by any of the models considered. In summary, the classic experiment cannot rule out Lamarckian contributions to the evolutionary dynamics. This work was supported by National Science Foundation Grant 1410978, NIH training Grant 5R90DA033462, and James S. McDonnell Foundation Grant 220020321.

Designing adaptive operating rules for a large multi-purpose reservoir

NASA Astrophysics Data System (ADS)

Geressu, Robel; Rougé, Charles; Harou, Julien

2017-04-01

Reservoirs whose live storage capacity is large compared with annual inflow have "memory", i.e., their storage levels contain information about past inflows and reservoir operations. Such "long-memory" reservoirs can be found in basins in dry regions such as the Nile River Basin in Africa, the Colorado River Basin in the US, or river basins in Western and Central Asia. There the effects of a dry year have the potential to impact reservoir levels and downstream releases for several subsequent years, prompting tensions in transboundary basins. Yet, current reservoir operation rules in those reservoirs do not reflect this by integrating past climate history and release decisions among the factors that influence operating decisions. This work proposes and demonstrates an adaptive reservoir operating rule that explicitly accounts for the recent history of release decisions, and not only current storage level and near-term inflow forecasts. This implies adding long-term (e.g., multiyear) objectives to the existing short-term (e.g., annual) ones. We apply these operating rules to the Grand Ethiopian Renaissance Dam, a large reservoir under construction on the Blue Nile River. Energy generation has to be balanced with the imperative of releasing enough water in low flow years (e.g., the minimum 1, 2 or 3 year cumulative flow) to avoid tensions with downstream countries, Sudan and Egypt. Maximizing the minimum multi-year releases could be of interest for the Nile problem to minimize the impact on performance of the large High Aswan Dam in Egypt. Objectives include maximizing the average and minimum annual energy generation and maximizing the minimum annual, two year and three year cumulative releases. The system model is tested using 30 stochastically generated streamflow series. One can then derive adaptive release rules depending on the value of one- and two-year total releases with respect to thresholds. Then, there are 3 sets of release rules for the reservoir depending on whether one or both thresholds are not met, vs. only one with a non-adaptive rule. Multi-objective evolutionary algorithms (MOEAs) are used to obtain the Pareto front, i.e., non-dominated adaptive and non-adaptive operating rule sets. Implementing adaptive rules is found to improve the trade-offs between energy generation criteria and minimum release targets. Compared with non-adaptive operations, an adaptive operating policy shows an increase of around 3 and 10 Billion cubic meters in the minimum 1 and 3-year cumulative releases for a given value of the same average annual energy generation.

Algorithm To Architecture Mapping Model (ATAMM) multicomputer operating system functional specification

NASA Technical Reports Server (NTRS)

Mielke, R.; Stoughton, J.; Som, S.; Obando, R.; Malekpour, M.; Mandala, B.

1990-01-01

A functional description of the ATAMM Multicomputer Operating System is presented. ATAMM (Algorithm to Architecture Mapping Model) is a marked graph model which describes the implementation of large grained, decomposed algorithms on data flow architectures. AMOS, the ATAMM Multicomputer Operating System, is an operating system which implements the ATAMM rules. A first generation version of AMOS which was developed for the Advanced Development Module (ADM) is described. A second generation version of AMOS being developed for the Generic VHSIC Spaceborne Computer (GVSC) is also presented.

Teaching Operant Conditioning at the Zoo.

ERIC Educational Resources Information Center

Lukas, Kristen E.; Marr, M. Jackson; Maple, Terry L.

1998-01-01

Describes a partnership between Zoo Atlanta and the Georgia Institute of Technology in teaching the principles of operant conditioning to students in an experimental psychology class. Maintains that the positive training techniques used in zoos are models of applied operant conditioning. Includes a discussion of zoo training goals. (MJP)

A psychologist's view of validating aviation systems

NASA Technical Reports Server (NTRS)

Stein, Earl S.; Wagner, Dan

1994-01-01

All systems, no matter what they are designed to do, have shortcomings that may make them less productive than was hoped during the initial development. Such shortcomings can arise at any stage of development: from conception to the end of the implementation life cycle. While systems failure and errors of a lesser magnitude can occur as a function of mechanical or software breakdown, the majority of such problems, in aviation are usually laid on the shoulders of the human operator and, to a lesser extent, on human factors. The operator bears the responsibility and blame even though, from a human factors perspective, error may have been designed into the system. Human factors is not a new concept in aviation. The name may be new, but the issues related to operators in the loop date back to the industrial revolution of the nineteenth century and certainly to the aviation build-up for World War I. During this first global confrontation, military services from all sides discovered rather quickly that poor selection and training led to drastically increased personnel losses. While hardware design became an issue later, the early efforts were primarily focused on increased care in pilot selection and on their training. This actually involved early labor-intensive simulation, using such devices as sticks and chairs mounted on rope networks which could be manually moved in response to control input. The use of selection criteria and improved training led to more viable person-machine systems. More pilots survived training and their first ten missions in the air, a rule of thumb arrived at by experience which predicted ultimate survival better than any other. This rule was to hold through World War II. At that time, personnel selection and training became very sophisticated based on previous standards. Also, many psychologists were drafted into Army Air Corps programs which were geared towards refining the human factor. However, despite the talent involved in these programs and the tremendous build-up of aviation during the war, there were still aircraft designs that were man killers (no sexism implied since all combat pilots were men). One classic design error that was identified fifty years ago was the multipointer altimeter, which could easily be misread especially by a pilot under considerable task load. It has led to flying fully operational aircraft into the terrain. The authors of the research which formally identified this problem put 'Human Errors' in quotes to express their dissatisfaction with the traditional approach to accident investigation. It traditionally places the burden of guilt on the operator. Some of these altimeters still exist in older aircraft to this day.

POPEYE: A production rule-based model of multitask supervisory control (POPCORN)

NASA Technical Reports Server (NTRS)

Townsend, James T.; Kadlec, Helena; Kantowitz, Barry H.

1988-01-01

Recent studies of relationships between subjective ratings of mental workload, performance, and human operator and task characteristics have indicated that these relationships are quite complex. In order to study the various relationships and place subjective mental workload within a theoretical framework, we developed a production system model for the performance component of the complex supervisory task called POPCORN. The production system model is represented by a hierarchial structure of goals and subgoals, and the information flow is controlled by a set of condition-action rules. The implementation of this production system, called POPEYE, generates computer simulated data under different task difficulty conditions which are comparable to those of human operators performing the task. This model is the performance aspect of an overall dynamic psychological model which we are developing to examine and quantify relationships between performance and psychological aspects in a complex environment.

Fuzzy logic application for modeling man-in-the-loop space shuttle proximity operations. M.S. Thesis - MIT

NASA Technical Reports Server (NTRS)

Brown, Robert B.

1994-01-01

A software pilot model for Space Shuttle proximity operations is developed, utilizing fuzzy logic. The model is designed to emulate a human pilot during the terminal phase of a Space Shuttle approach to the Space Station. The model uses the same sensory information available to a human pilot and is based upon existing piloting rules and techniques determined from analysis of human pilot performance. Such a model is needed to generate numerous rendezvous simulations to various Space Station assembly stages for analysis of current NASA procedures and plume impingement loads on the Space Station. The advantages of a fuzzy logic pilot model are demonstrated by comparing its performance with NASA's man-in-the-loop simulations and with a similar model based upon traditional Boolean logic. The fuzzy model is shown to respond well from a number of initial conditions, with results typical of an average human. In addition, the ability to model different individual piloting techniques and new piloting rules is demonstrated.

A new in silico classification model for ready biodegradability, based on molecular fragments.

PubMed

Lombardo, Anna; Pizzo, Fabiola; Benfenati, Emilio; Manganaro, Alberto; Ferrari, Thomas; Gini, Giuseppina

2014-08-01

Regulations such as the European REACH (Registration, Evaluation, Authorization and restriction of Chemicals) often require chemicals to be evaluated for ready biodegradability, to assess the potential risk for environmental and human health. Because not all chemicals can be tested, there is an increasing demand for tools for quick and inexpensive biodegradability screening, such as computer-based (in silico) theoretical models. We developed an in silico model starting from a dataset of 728 chemicals with ready biodegradability data (MITI-test Ministry of International Trade and Industry). We used the novel software SARpy to automatically extract, through a structural fragmentation process, a set of substructures statistically related to ready biodegradability. Then, we analysed these substructures in order to build some general rules. The model consists of a rule-set made up of the combination of the statistically relevant fragments and of the expert-based rules. The model gives good statistical performance with 92%, 82% and 76% accuracy on the training, test and external set respectively. These results are comparable with other in silico models like BIOWIN developed by the United States Environmental Protection Agency (EPA); moreover this new model includes an easily understandable explanation. Copyright © 2014 Elsevier Ltd. All rights reserved.

Home-Grown Citizens

ERIC Educational Resources Information Center

Anderson, Sarah; Gurnee, Anne

2016-01-01

While the purpose of K-12 education is largely to train students for college and career, free education in a democratic society has another purpose: to prepare citizens to rule themselves. In this article, Anderson and Gurnee explain how place-based learning equips students to be active citizens in their communities. In this model, school localize…

Mentoring SFRM: A New Approach to International Space Station Flight Control Training

NASA Technical Reports Server (NTRS)

Huning, Therese; Barshi, Immanuel; Schmidt, Lacey

2009-01-01

The Mission Operations Directorate (MOD) of the Johnson Space Center is responsible for providing continuous operations support for the International Space Station (ISS). Operations support requires flight controllers who are skilled in team performance as well as the technical operations of the ISS. Space Flight Resource Management (SFRM), a NASA adapted variant of Crew Resource Management (CRM), is the competency model used in the MOD. ISS flight controller certification has evolved to include a balanced focus on development of SFRM and technical expertise. The latest challenge the MOD faces is how to certify an ISS flight controller (Operator) to a basic level of effectiveness in 1 year. SFRM training uses a twopronged approach to expediting operator certification: 1) imbed SFRM skills training into all Operator technical training and 2) use senior flight controllers as mentors. This paper focuses on how the MOD uses senior flight controllers as mentors to train SFRM skills.

Manpower, Personnel, and Training Assessment (MPTA) Handbook

DTIC Science & Technology

2015-11-01

Occupational Specialty (MOS), any Additional Skill Identifier (ASI) required, core knowledge, skills, and abilities ( KSAs ) required for the job...of training, usability assessments, interviews with Soldiers, and manpower modeling . Some guidelines on the type of questions to ask in this portion... modeling , and simulation activities into an efficient continuum. COICs are the operational effectiveness and operational suitability issues (not

Compliance with railroad operating rules and corporate culture influences : results of a focus group and structured interviews

DOT National Transportation Integrated Search

1999-10-01

A focus group was held at the November 11, 1996 meeting of the Operating Rules Association of North American Railroads to discuss the general issue of compliance and operating rules. Twelve operating rules officers participated, representing Class I,...

A Comprehensive Planning Model and Delivery System for Leadership Training Programs.

ERIC Educational Resources Information Center

Janosik, Steven M.; Sina, Julie A.

1988-01-01

Presents an eight-step planning model that operationally defines a comprehensive delivery systems approach to campuswide leadership training. Lists four goals of the model: to increase efficiency of leadership training through shared resources, to decrease costs, to provide quality control, and to increase impact of programming effort by creating…

A Pilot Study on Modeling of Diagnostic Criteria Using OWL and SWRL.

PubMed

Hong, Na; Jiang, Guoqian; Pathak, Jyotishiman; Chute, Christopher G

2015-01-01

The objective of this study is to describe our efforts in a pilot study on modeling diagnostic criteria using a Semantic Web-based approach. We reused the basic framework of the ICD-11 content model and refined it into an operational model in the Web Ontology Language (OWL). The refinement is based on a bottom-up analysis method, in which we analyzed data elements (including value sets) in a collection (n=20) of randomly selected diagnostic criteria. We also performed a case study to formalize rule logic in the diagnostic criteria of metabolic syndrome using the Semantic Web Rule Language (SWRL). The results demonstrated that it is feasible to use OWL and SWRL to formalize the diagnostic criteria knowledge, and to execute the rules through reasoning.

Computer model of Raritan River Basin water-supply system in central New Jersey

USGS Publications Warehouse

Dunne, Paul; Tasker, Gary D.

1996-01-01

This report describes a computer model of the Raritan River Basin water-supply system in central New Jersey. The computer model provides a technical basis for evaluating the effects of alternative patterns of operation of the Raritan River Basin water-supply system during extended periods of below-average precipitation. The computer model is a continuity-accounting model consisting of a series of interconnected nodes. At each node, the inflow volume, outflow volume, and change in storage are determined and recorded for each month. The model runs with a given set of operating rules and water-use requirements including releases, pumpages, and diversions. The model can be used to assess the hypothetical performance of the Raritan River Basin water- supply system in past years under alternative sets of operating rules. It also can be used to forecast the likelihood of specified outcomes, such as the depletion of reservoir contents below a specified threshold or of streamflows below statutory minimum passing flows, for a period of up to 12 months. The model was constructed on the basis of current reservoir capacities and the natural, unregulated monthly runoff values recorded at U.S. Geological Survey streamflow- gaging stations in the basin.

Coupling hydrological modeling and support vector regression to model hydropeaking in alpine catchments.

PubMed

Chiogna, Gabriele; Marcolini, Giorgia; Liu, Wanying; Pérez Ciria, Teresa; Tuo, Ye

2018-08-15

Water management in the alpine region has an important impact on streamflow. In particular, hydropower production is known to cause hydropeaking i.e., sudden fluctuations in river stage caused by the release or storage of water in artificial reservoirs. Modeling hydropeaking with hydrological models, such as the Soil Water Assessment Tool (SWAT), requires knowledge of reservoir management rules. These data are often not available since they are sensitive information belonging to hydropower production companies. In this short communication, we propose to couple the results of a calibrated hydrological model with a machine learning method to reproduce hydropeaking without requiring the knowledge of the actual reservoir management operation. We trained a support vector machine (SVM) with SWAT model outputs, the day of the week and the energy price. We tested the model for the Upper Adige river basin in North-East Italy. A wavelet analysis showed that energy price has a significant influence on river discharge, and a wavelet coherence analysis demonstrated the improved performance of the SVM model in comparison to the SWAT model alone. The SVM model was also able to capture the fluctuations in streamflow caused by hydropeaking when both energy price and river discharge displayed a complex temporal dynamic. Copyright © 2018 Elsevier B.V. All rights reserved.

Expert training with standardized operative technique helps establish a successful penile prosthetics program for urologic resident education.

PubMed

King, Ashley B; Klausner, Adam P; Johnson, Corey M; Moore, Blake W; Wilson, Steven K; Grob, B Mayer

2011-10-01

The challenge of resident education in urologic surgery programs is to overcome disparity imparted by diverse patient populations, limited training times, and inequalities in the availability of expert surgical educators. Specifically, in the area of prosthetic urology, only a small proportion of programs have full-time faculty available to train residents in this discipline. To examine whether a new model using yearly training sessions from a recognized expert can establish a successful penile prosthetics program and result in better outcomes, higher case volumes, and willingness to perform more complex surgeries. A recognized expert conducted one to two operative training sessions yearly to teach standardized technique for penile prosthetics to residents. Each session consisted of three to four operative cases performed under the direct supervision of the expert. Retrospective data were collected from all penile prosthetic operations before (February, 2000 to June, 2004: N = 44) and after (July, 2004 to October, 2007: N = 79) implementation of these sessions. Outcomes reviewed included patient age, race, medical comorbidities, operative time, estimated blood loss, type of prosthesis, operative approach, drain usage, length of stay, and complications including revision/explantation rates. Statistical analysis was performed using Student's t-tests, Fisher's tests, and survival curves using the Kaplan-Meier technique (P value ≤ 0.05 to define statistical significance). Patient characteristics were not significantly different pre- vs. post-training. Operative time and estimated blood loss significantly decreased. Inflatable implants increased from 19/44 (43.2%, pre-training) to 69/79 (87.3%, post-training) (P < 0.01). Operations per year increased from 9.96 (pre-training) to 24 (post-training) (P < 0.01). Revision/explantation occurred in 11/44 patients (25%, pre-training) vs. 7/79 (8.9%, post-training) (P < 0.05). These data demonstrate that yearly sessions with a recognized expert can improve surgical outcomes, type, and volume of implants and can reduce explantation/revision rates. This represents an excellent model for improved training of urologic residents in penile prosthetics surgery. © 2011 International Society for Sexual Medicine.

Differences in perceptual learning transfer as a function of training task.

PubMed

Green, C Shawn; Kattner, Florian; Siegel, Max H; Kersten, Daniel; Schrater, Paul R

2015-01-01

A growing body of research--including results from behavioral psychology, human structural and functional imaging, single-cell recordings in nonhuman primates, and computational modeling--suggests that perceptual learning effects are best understood as a change in the ability of higher-level integration or association areas to read out sensory information in the service of particular decisions. Work in this vein has argued that, depending on the training experience, the "rules" for this read-out can either be applicable to new contexts (thus engendering learning generalization) or can apply only to the exact training context (thus resulting in learning specificity). Here we contrast learning tasks designed to promote either stimulus-specific or stimulus-general rules. Specifically, we compare learning transfer across visual orientation following training on three different tasks: an orientation categorization task (which permits an orientation-specific learning solution), an orientation estimation task (which requires an orientation-general learning solution), and an orientation categorization task in which the relevant category boundary shifts on every trial (which lies somewhere between the two tasks above). While the simple orientation-categorization training task resulted in orientation-specific learning, the estimation and moving categorization tasks resulted in significant orientation learning generalization. The general framework tested here--that task specificity or generality can be predicted via an examination of the optimal learning solution--may be useful in building future training paradigms with certain desired outcomes.

Automated medical resident rotation and shift scheduling to ensure quality resident education and patient care.

PubMed

Smalley, Hannah K; Keskinocak, Pinar

2016-03-01

At academic teaching hospitals around the country, the majority of clinical care is provided by resident physicians. During their training, medical residents often rotate through various hospitals and/or medical services to maximize their education. Depending on the size of the training program, manually constructing such a rotation schedule can be cumbersome and time consuming. Further, rules governing allowable duty hours for residents have grown more restrictive in recent years (ACGME 2011), making day-to-day shift scheduling of residents more difficult (Connors et al., J Thorac Cardiovasc Surg 137:710-713, 2009; McCoy et al., May Clin Proc 86(3):192, 2011; Willis et al., J Surg Edu 66(4):216-221, 2009). These rules limit lengths of duty periods, allowable duty hours in a week, and rest periods, to name a few. In this paper, we present two integer programming models (IPs) with the goals of (1) creating feasible assignments of residents to rotations over a one-year period, and (2) constructing night and weekend call-shift schedules for the individual rotations. These models capture various duty-hour rules and constraints, provide the ability to test multiple what-if scenarios, and largely automate the process of schedule generation, solving these scheduling problems more effectively and efficiently compared to manual methods. Applying our models on data from a surgical residency program, we highlight the infeasibilities created by increased duty-hour restrictions placed on residents in conjunction with current scheduling paradigms.

Automated detection of pain from facial expressions: a rule-based approach using AAM

NASA Astrophysics Data System (ADS)

Chen, Zhanli; Ansari, Rashid; Wilkie, Diana J.

2012-02-01

In this paper, we examine the problem of using video analysis to assess pain, an important problem especially for critically ill, non-communicative patients, and people with dementia. We propose and evaluate an automated method to detect the presence of pain manifested in patient videos using a unique and large collection of cancer patient videos captured in patient homes. The method is based on detecting pain-related facial action units defined in the Facial Action Coding System (FACS) that is widely used for objective assessment in pain analysis. In our research, a person-specific Active Appearance Model (AAM) based on Project-Out Inverse Compositional Method is trained for each patient individually for the modeling purpose. A flexible representation of the shape model is used in a rule-based method that is better suited than the more commonly used classifier-based methods for application to the cancer patient videos in which pain-related facial actions occur infrequently and more subtly. The rule-based method relies on the feature points that provide facial action cues and is extracted from the shape vertices of AAM, which have a natural correspondence to face muscular movement. In this paper, we investigate the detection of a commonly used set of pain-related action units in both the upper and lower face. Our detection results show good agreement with the results obtained by three trained FACS coders who independently reviewed and scored the action units in the cancer patient videos.

DNA biosensors that reason.

PubMed

Sainz de Murieta, Iñaki; Rodríguez-Patón, Alfonso

2012-08-01

Despite the many designs of devices operating with the DNA strand displacement, surprisingly none is explicitly devoted to the implementation of logical deductions. The present article introduces a new model of biosensor device that uses nucleic acid strands to encode simple rules such as "IF DNA_strand(1) is present THEN disease(A)" or "IF DNA_strand(1) AND DNA_strand(2) are present THEN disease(B)". Taking advantage of the strand displacement operation, our model makes these simple rules interact with input signals (either DNA or any type of RNA) to generate an output signal (in the form of nucleotide strands). This output signal represents a diagnosis, which either can be measured using FRET techniques, cascaded as the input of another logical deduction with different rules, or even be a drug that is administered in response to a set of symptoms. The encoding introduces an implicit error cancellation mechanism, which increases the system scalability enabling longer inference cascades with a bounded and controllable signal-noise relation. It also allows the same rule to be used in forward inference or backward inference, providing the option of validly outputting negated propositions (e.g. "diagnosis A excluded"). The models presented in this paper can be used to implement smart logical DNA devices that perform genetic diagnosis in vitro. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Dust Plume Modeling at Fort Bliss: Move-Out Operations, Combat Training and Wind Erosion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chapman, Elaine G.; Rishel, Jeremy P.; Rutz, Frederick C.

2006-09-29

The potential for air-quality impacts from heavy mechanized vehicles operating in the training ranges and on the unpaved main supply routes at Fort Bliss was investigated. This report details efforts by the staff of Pacific Northwest National Laboratory for the Fort Bliss Directorate of Environment in this investigation. Dust emission and dispersion from typical activities, including move outs and combat training, occurring on the installation were simulated using the atmospheric modeling system DUSTRAN. Major assumptions associated with designing specific modeling scenarios are summarized, and results from the simulations are presented.

Mirrored STDP Implements Autoencoder Learning in a Network of Spiking Neurons.

PubMed

Burbank, Kendra S

2015-12-01

The autoencoder algorithm is a simple but powerful unsupervised method for training neural networks. Autoencoder networks can learn sparse distributed codes similar to those seen in cortical sensory areas such as visual area V1, but they can also be stacked to learn increasingly abstract representations. Several computational neuroscience models of sensory areas, including Olshausen & Field's Sparse Coding algorithm, can be seen as autoencoder variants, and autoencoders have seen extensive use in the machine learning community. Despite their power and versatility, autoencoders have been difficult to implement in a biologically realistic fashion. The challenges include their need to calculate differences between two neuronal activities and their requirement for learning rules which lead to identical changes at feedforward and feedback connections. Here, we study a biologically realistic network of integrate-and-fire neurons with anatomical connectivity and synaptic plasticity that closely matches that observed in cortical sensory areas. Our choice of synaptic plasticity rules is inspired by recent experimental and theoretical results suggesting that learning at feedback connections may have a different form from learning at feedforward connections, and our results depend critically on this novel choice of plasticity rules. Specifically, we propose that plasticity rules at feedforward versus feedback connections are temporally opposed versions of spike-timing dependent plasticity (STDP), leading to a symmetric combined rule we call Mirrored STDP (mSTDP). We show that with mSTDP, our network follows a learning rule that approximately minimizes an autoencoder loss function. When trained with whitened natural image patches, the learned synaptic weights resemble the receptive fields seen in V1. Our results use realistic synaptic plasticity rules to show that the powerful autoencoder learning algorithm could be within the reach of real biological networks.

Mirrored STDP Implements Autoencoder Learning in a Network of Spiking Neurons

PubMed Central

Burbank, Kendra S.

2015-01-01

The autoencoder algorithm is a simple but powerful unsupervised method for training neural networks. Autoencoder networks can learn sparse distributed codes similar to those seen in cortical sensory areas such as visual area V1, but they can also be stacked to learn increasingly abstract representations. Several computational neuroscience models of sensory areas, including Olshausen & Field’s Sparse Coding algorithm, can be seen as autoencoder variants, and autoencoders have seen extensive use in the machine learning community. Despite their power and versatility, autoencoders have been difficult to implement in a biologically realistic fashion. The challenges include their need to calculate differences between two neuronal activities and their requirement for learning rules which lead to identical changes at feedforward and feedback connections. Here, we study a biologically realistic network of integrate-and-fire neurons with anatomical connectivity and synaptic plasticity that closely matches that observed in cortical sensory areas. Our choice of synaptic plasticity rules is inspired by recent experimental and theoretical results suggesting that learning at feedback connections may have a different form from learning at feedforward connections, and our results depend critically on this novel choice of plasticity rules. Specifically, we propose that plasticity rules at feedforward versus feedback connections are temporally opposed versions of spike-timing dependent plasticity (STDP), leading to a symmetric combined rule we call Mirrored STDP (mSTDP). We show that with mSTDP, our network follows a learning rule that approximately minimizes an autoencoder loss function. When trained with whitened natural image patches, the learned synaptic weights resemble the receptive fields seen in V1. Our results use realistic synaptic plasticity rules to show that the powerful autoencoder learning algorithm could be within the reach of real biological networks. PMID:26633645

Differential Modifications of Synaptic Weights During Odor Rule Learning: Dynamics of Interaction Between the Piriform Cortex with Lower and Higher Brain Areas

PubMed Central

Cohen, Yaniv; Wilson, Donald A.; Barkai, Edi

2015-01-01

Learning of a complex olfactory discrimination (OD) task results in acquisition of rule learning after prolonged training. Previously, we demonstrated enhanced synaptic connectivity between the piriform cortex (PC) and its ascending and descending inputs from the olfactory bulb (OB) and orbitofrontal cortex (OFC) following OD rule learning. Here, using recordings of evoked field postsynaptic potentials in behaving animals, we examined the dynamics by which these synaptic pathways are modified during rule acquisition. We show profound differences in synaptic connectivity modulation between the 2 input sources. During rule acquisition, the ascending synaptic connectivity from the OB to the anterior and posterior PC is simultaneously enhanced. Furthermore, post-training stimulation of the OB enhanced learning rate dramatically. In sharp contrast, the synaptic input in the descending pathway from the OFC was significantly reduced until training completion. Once rule learning was established, the strength of synaptic connectivity in the 2 pathways resumed its pretraining values. We suggest that acquisition of olfactory rule learning requires a transient enhancement of ascending inputs to the PC, synchronized with a parallel decrease in the descending inputs. This combined short-lived modulation enables the PC network to reorganize in a manner that enables it to first acquire and then maintain the rule. PMID:23960200

Effective and efficient learning in the operating theater with intraoperative video-enhanced surgical procedure training.

PubMed

van Det, M J; Meijerink, W J H J; Hoff, C; Middel, B; Pierie, J P E N

2013-08-01

INtraoperative Video Enhanced Surgical procedure Training (INVEST) is a new training method designed to improve the transition from basic skills training in a skills lab to procedural training in the operating theater. Traditionally, the master-apprentice model (MAM) is used for procedural training in the operating theater, but this model lacks uniformity and efficiency at the beginning of the learning curve. This study was designed to investigate the effectiveness and efficiency of INVEST compared to MAM. Ten surgical residents with no laparoscopic experience were recruited for a laparoscopic cholecystectomy training curriculum either by the MAM or with INVEST. After a uniform course in basic laparoscopic skills, each trainee performed six cholecystectomies that were digitally recorded. For 14 steps of the procedure, an observer who was blinded for the type of training determined whether the step was performed entirely by the trainee (2 points), partially by the trainee (1 point), or by the supervisor (0 points). Time measurements revealed the total procedure time and the amount of effective procedure time during which the trainee acted as the operating surgeon. Results were compared between both groups. Trainees in the INVEST group were awarded statistically significant more points (115.8 vs. 70.2; p < 0.001) and performed more steps without the interference of the supervisor (46.6 vs. 18.8; p < 0.001). Total procedure time was not lengthened by INVEST, and the part performed by trainees was significantly larger (69.9 vs. 54.1 %; p = 0.004). INVEST enhances effectiveness and training efficiency for procedural training inside the operating theater without compromising operating theater time efficiency.

The role of predictive uncertainty in the operational management of reservoirs

NASA Astrophysics Data System (ADS)

Todini, E.

2014-09-01

The present work deals with the operational management of multi-purpose reservoirs, whose optimisation-based rules are derived, in the planning phase, via deterministic (linear and nonlinear programming, dynamic programming, etc.) or via stochastic (generally stochastic dynamic programming) approaches. In operation, the resulting deterministic or stochastic optimised operating rules are then triggered based on inflow predictions. In order to fully benefit from predictions, one must avoid using them as direct inputs to the reservoirs, but rather assess the "predictive knowledge" in terms of a predictive probability density to be operationally used in the decision making process for the estimation of expected benefits and/or expected losses. Using a theoretical and extremely simplified case, it will be shown why directly using model forecasts instead of the full predictive density leads to less robust reservoir management decisions. Moreover, the effectiveness and the tangible benefits for using the entire predictive probability density instead of the model predicted values will be demonstrated on the basis of the Lake Como management system, operational since 1997, as well as on the basis of a case study on the lake of Aswan.

Analyzing injury severity factors at highway railway grade crossing accidents involving vulnerable road users: A comparative study.

PubMed

Ghomi, Haniyeh; Bagheri, Morteza; Fu, Liping; Miranda-Moreno, Luis F

2016-11-16

The main objective of this study is to identify the main factors associated with injury severity of vulnerable road users (VRUs) involved in accidents at highway railroad grade crossings (HRGCs) using data mining techniques. This article applies an ordered probit model, association rules, and classification and regression tree (CART) algorithms to the U.S. Federal Railroad Administration's (FRA) HRGC accident database for the period 2007-2013 to identify VRU injury severity factors at HRGCs. The results show that train speed is a key factor influencing injury severity. Further analysis illustrated that the presence of illumination does not reduce the severity of accidents for high-speed trains. In addition, there is a greater propensity toward fatal accidents for elderly road users compared to younger individuals. Interestingly, at night, injury accidents involving female road users are more severe compared to those involving males. The ordered probit model was the primary technique, and CART and association rules act as the supporter and identifier of interactions between variables. All 3 algorithms' results consistently show that the most influential accident factors are train speed, VRU age, and gender. The findings of this research could be applied for identifying high-risk hotspots and developing cost-effective countermeasures targeting VRUs at HRGCs.

An implementation of cellular automaton model for single-line train working diagram

NASA Astrophysics Data System (ADS)

Hua, Wei; Liu, Jun

2006-04-01

According to the railway transportation system's characteristics, a new cellular automaton model for the single-line railway system is presented in this paper. Based on this model, several simulations were done to imitate the train operation under three working diagrams. From a different angle the results show how the organization of train operation impacts on the railway carrying capacity. By using the non-parallel train working diagram the influence of fast-train on slow-train is found to be the strongest. Many slow-trains have to wait in-between neighbouring stations to let the fast-train(s) pass through first. So the slow-train will advance like a wave propagating from the departure station to the arrival station. This also resembles the situation of a highway jammed traffic flow. Furthermore, the nonuniformity of travel times between the sections also greatly limits the railway carrying capacity. After converting the nonuniform sections into the sections with uniform travel times while the total travel time is kept unchanged, all three carrying capacities are improved greatly as shown by simulation. It also shows that the cellular automaton model is an effective and feasible way to investigate the railway transportation system.

A simple rule based model for scheduling farm management operations in SWAT

NASA Astrophysics Data System (ADS)

Schürz, Christoph; Mehdi, Bano; Schulz, Karsten

2016-04-01

For many interdisciplinary questions at the watershed scale, the Soil and Water Assessment Tool (SWAT; Arnold et al., 1998) has become an accepted and widely used tool. Despite its flexibility, the model is highly demanding when it comes to input data. At SWAT's core the water balance and the modeled nutrient cycles are plant growth driven (implemented with the EPIC crop growth model). Therefore, land use and crop data with high spatial and thematic resolution, as well as detailed information on cultivation and farm management practices are required. For many applications of the model however, these data are unavailable. In order to meet these requirements, SWAT offers the option to trigger scheduled farm management operations by applying the Potential Heat Unit (PHU) concept. The PHU concept solely takes into account the accumulation of daily mean temperature for management scheduling. Hence, it contradicts several farming strategies that take place in reality; such as: i) Planting and harvesting dates are set much too early or too late, as the PHU concept is strongly sensitivity to inter-annual temperature fluctuations; ii) The timing of fertilizer application, in SWAT this often occurs simultaneously on the same date in in each field; iii) and can also coincide with precipitation events. Particularly, the latter two can lead to strong peaks in modeled nutrient loads. To cope with these shortcomings we propose a simple rule based model (RBM) to schedule management operations according to realistic farmer management practices in SWAT. The RBM involves simple strategies requiring only data that are input into the SWAT model initially, such as temperature and precipitation data. The user provides boundaries of time periods for operation schedules to take place for all crops in the model. These data are readily available from the literature or from crop variety trials. The RBM applies the dates by complying with the following rules: i) Operations scheduled in the spring planting season and fall harvesting season are temperature dependent. Warmer than usual conditions trigger the setting of respective operations earlier in spring and later in fall to prolong the cropping season. ii) Operations are randomized within a time span ± 5 days around the calculated dates and iii) are only set on days where no rainfall occurs. Advantages offered by the RBM framework are the implementation of farmers undertaking different farming strategies, such as conventional or conservative farming, and the consideration of the prevailing weather conditions on the planting periods, thus the shifting management operations due to climate change will also be considered over the long term. By applying these rules to the available data we were able to establish a simple framework developing more realistic crop management schedules for SWAT which are an improvement over the current PHU concept implemented in SWAT. The outlined framework is easily extendible and adaptable to many other applications in SWAT. Case studies have yet to demonstrate the applicability and the validity of the proposed RBM.

Individual Markers of Resilience in Train Traffic Control: The Role of Operators' Goals and Strategic Mental Models and Implications for Variation, Expertise, and Performance.

PubMed

Lo, Julia C; Pluyter, Kari R; Meijer, Sebastiaan A

2016-02-01

The aim of this study was to examine individual markers of resilience and obtain quantitative insights into the understanding and the implications of variation and expertise levels in train traffic operators' goals and strategic mental models and their impact on performance. The Dutch railways are one of the world's most heavy utilized railway networks and have been identified to be weak in system and organizational resilience. Twenty-two train traffic controllers enacted two scenarios in a human-in-the-loop simulator. Their experience, goals, strategic mental models, and performance were assessed through questionnaires and simulator logs. Goals were operationalized through performance indicators and strategic mental models through train completion strategies. A variation was found between operators for both self-reported primary performance indicators and completion strategies. Further, the primary goal of only 14% of the operators reflected the primary organizational goal (i.e., arrival punctuality). An incongruence was also found between train traffic controllers' self-reported performance indicators and objective performance in a more disrupted condition. The level of experience tends to affect performance differently. There is a gap between primary organizational goals and preferred individual goals. Further, the relative strong diversity in primary operator goals and strategic mental models indicates weak resilience at the individual level. With recent and upcoming large-scale changes throughout the sociotechnical space of the railway infrastructure organization, the findings are useful to facilitate future railway traffic control and the development of a resilient system. © 2015, Human Factors and Ergonomics Society.

A MODEL LOCAL CIVIL DEFENSE TRAINING PLAN, AN ORGANIZATION AND TRAINING DEVELOPMENT RESEARCH STUDY.

ERIC Educational Resources Information Center

BRICTSON, R.C.; AND OTHERS

THIS DETAILED AND COMPREHENSIVE EXAMINATION OF LOCAL CIVIL DEFENSE TRAINING INCLUDES A SURVEY OF CIVIL DEFENSE OPERATIONS UNDERTAKEN TO DEFINE A MODEL LOCAL TRAINING PLAN. SPECIFIC LOCAL CIVIL DEFENSE OFFICES WERE SELECTED FOR INTENSIVE STUDY AND DATA COLLECTION. UTILIZING THE DATA OBTAINED AND FUNCTIONAL CATEGORIES DERIVED FROM THE FEDERAL CIVIL…

Optimization of European call options considering physical delivery network and reservoir operation rules

NASA Astrophysics Data System (ADS)

Cheng, Wei-Chen; Hsu, Nien-Sheng; Cheng, Wen-Ming; Yeh, William W.-G.

2011-10-01

This paper develops alternative strategies for European call options for water purchase under hydrological uncertainties that can be used by water resources managers for decision making. Each alternative strategy maximizes its own objective over a selected sequence of future hydrology that is characterized by exceedance probability. Water trade provides flexibility and enhances water distribution system reliability. However, water trade between two parties in a regional water distribution system involves many issues, such as delivery network, reservoir operation rules, storage space, demand, water availability, uncertainty, and any existing contracts. An option is a security giving the right to buy or sell an asset; in our case, the asset is water. We extend a flow path-based water distribution model to include reservoir operation rules. The model simultaneously considers both the physical distribution network as well as the relationships between water sellers and buyers. We first test the model extension. Then we apply the proposed optimization model for European call options to the Tainan water distribution system in southern Taiwan. The formulation lends itself to a mixed integer linear programming model. We use the weighing method to formulate a composite function for a multiobjective problem. The proposed methodology provides water resources managers with an overall picture of water trade strategies and the consequence of each strategy. The results from the case study indicate that the strategy associated with a streamflow exceedence probability of 50% or smaller should be adopted as the reference strategy for the Tainan water distribution system.

Virtual reality training for surgical trainees in laparoscopic surgery.

PubMed

Nagendran, Myura; Gurusamy, Kurinchi Selvan; Aggarwal, Rajesh; Loizidou, Marilena; Davidson, Brian R

2013-08-27

Standard surgical training has traditionally been one of apprenticeship, where the surgical trainee learns to perform surgery under the supervision of a trained surgeon. This is time-consuming, costly, and of variable effectiveness. Training using a virtual reality simulator is an option to supplement standard training. Virtual reality training improves the technical skills of surgical trainees such as decreased time for suturing and improved accuracy. The clinical impact of virtual reality training is not known. To assess the benefits (increased surgical proficiency and improved patient outcomes) and harms (potentially worse patient outcomes) of supplementary virtual reality training of surgical trainees with limited laparoscopic experience. We searched the Cochrane Central Register of Controlled Trials (CENTRAL) in The Cochrane Library, MEDLINE, EMBASE and Science Citation Index Expanded until July 2012. We included all randomised clinical trials comparing virtual reality training versus other forms of training including box-trainer training, no training, or standard laparoscopic training in surgical trainees with little laparoscopic experience. We also planned to include trials comparing different methods of virtual reality training. We included only trials that assessed the outcomes in people undergoing laparoscopic surgery. Two authors independently identified trials and collected data. We analysed the data with both the fixed-effect and the random-effects models using Review Manager 5 analysis. For each outcome we calculated the mean difference (MD) or standardised mean difference (SMD) with 95% confidence intervals based on intention-to-treat analysis. We included eight trials covering 109 surgical trainees with limited laparoscopic experience. Of the eight trials, six compared virtual reality versus no supplementary training. One trial compared virtual reality training versus box-trainer training and versus no supplementary training, and one trial compared virtual reality training versus box-trainer training. There were no trials that compared different forms of virtual reality training. All the trials were at high risk of bias. Operating time and operative performance were the only outcomes reported in the trials. The remaining outcomes such as mortality, morbidity, quality of life (the primary outcomes of this review) and hospital stay (a secondary outcome) were not reported. Virtual reality training versus no supplementary training: The operating time was significantly shorter in the virtual reality group than in the no supplementary training group (3 trials; 49 participants; MD -11.76 minutes; 95% CI -15.23 to -8.30). Two trials that could not be included in the meta-analysis also showed a reduction in operating time (statistically significant in one trial). The numerical values for operating time were not reported in these two trials. The operative performance was significantly better in the virtual reality group than the no supplementary training group using the fixed-effect model (2 trials; 33 participants; SMD 1.65; 95% CI 0.72 to 2.58). The results became non-significant when the random-effects model was used (2 trials; 33 participants; SMD 2.14; 95% CI -1.29 to 5.57). One trial could not be included in the meta-analysis as it did not report the numerical values. The authors stated that the operative performance of virtual reality group was significantly better than the control group. Virtual reality training versus box-trainer training: The only trial that reported operating time did not report the numerical values. In this trial, the operating time in the virtual reality group was significantly shorter than in the box-trainer group. Of the two trials that reported operative performance, only one trial reported the numerical values. The operative performance was significantly better in the virtual reality group than in the box-trainer group (1 trial; 19 participants; SMD 1.46; 95% CI 0.42 to 2.50). In the other trial that did not report the numerical values, the authors stated that the operative performance in the virtual reality group was significantly better than the box-trainer group. Virtual reality training appears to decrease the operating time and improve the operative performance of surgical trainees with limited laparoscopic experience when compared with no training or with box-trainer training. However, the impact of this decreased operating time and improvement in operative performance on patients and healthcare funders in terms of improved outcomes or decreased costs is not known. Further well-designed trials at low risk of bias and random errors are necessary. Such trials should assess the impact of virtual reality training on clinical outcomes.

Migrant and Seasonal Agricultural Worker Protection Act: Forestry contractors' model operating plan

Treesearch

Dan Bremer

2007-01-01

The Model Operating Plan for forestry contractors is a voluntary plan for compliance with the Migrant and Seasonal Agricultural Worker Protection Act (MSPA) of 1983, with amendments passed in 1996 and 1997. This plan is designed as a guide for forestry contractors who wish to comply with all federal, state, and local rules and regulations that govern their employer/...

40 CFR Table 3 to Subpart Ffff of... - Model Rule-Operating Limits for Incinerators and Wet Scrubbers

Code of Federal Regulations, 2010 CFR

2010-07-01

... Incinerators and Wet Scrubbers 3 Table 3 to Subpart FFFF of Part 60 Protection of Environment ENVIRONMENTAL...—Model Rule—Operating Limits for Incinerators and Wet Scrubbers As stated in § 60.3023, you must comply... units. a 2. Pressure drop across the wet scrubber or amperage to wet scrubber Minimum pressure drop or...

40 CFR Table 3 to Subpart Ffff of... - Model Rule-Operating Limits for Incinerators and Wet Scrubbers

Code of Federal Regulations, 2011 CFR

2011-07-01

... Incinerators and Wet Scrubbers 3 Table 3 to Subpart FFFF of Part 60 Protection of Environment ENVIRONMENTAL...—Model Rule—Operating Limits for Incinerators and Wet Scrubbers As stated in § 60.3023, you must comply... units. a 2. Pressure drop across the wet scrubber or amperage to wet scrubber Minimum pressure drop or...

Are short-term focused training courses on a phantom model using porcine gall bladder useful for trainees in acquiring basic laparoscopic skills?

PubMed

Bansal, Virinder Kumar; Panwar, Rajesh; Misra, Mahesh C; Bhattacharjee, Hemanga K; Jindal, Vikas; Loli, Athiko; Goswami, Amit; Krishna, Asuri; Tamang, Tseten

2012-04-01

The best training method in laparoscopic surgery has not been defined. We evaluated the efficacy of laparoscopic skills acquisition in a short-term focused program. Two hundred fifty-six participants undergoing training on a phantom model were divided into 2 groups. Group 1 had no exposure and group 2 had performed a few laparoscopic surgeries. Acquisition of laparoscopic skills was assessed by operation time and the modified Global Operative Assessment of Laparoscopic Skills (GOALS) scale. A questionnaire was sent to the participants after 3 to 6 months for assessment of impact of training. There was a statistically significant improvement in the assessed parameters and in the mean score of all 5 domains of GOALS. The participants in group 2 performed better than those in group 1 in the first case. The difference between both the groups disappeared after the training. Participants who responded to the questionnaire felt that training helped them in improving their performance in the operation theater.

The Space Environmental Impact System

NASA Astrophysics Data System (ADS)

Kihn, E. A.

2009-12-01

The Space Environmental Impact System (SEIS) is an operational tool for incorporating environmental data sets into DoD Modeling and Simulation (M&S) which allows for enhanced decision making regarding acquisitions, testing, operations and planning. The SEIS system creates, from the environmental archives and developed rule-base, a tool for describing the effects of the space environment on particular military systems, both historically and in real-time. The system uses data available over the web, and in particular data provided by NASA’s virtual observatory network, as well as modeled data generated specifically for this purpose. The rule base system developed to support SEIS is an open XML based model which can be extended to events from any environmental domain. This presentation will show how the SEIS tool allows users to easily and accurately evaluate the effect of space weather in terms that are meaningful to them as well as discuss the relevant standards used in its construction and go over lessons learned from fielding an operational environmental decision tool.

Development of an integrated hydrological modeling system for near-real-time multi-objective reservoir operation in large river basins

NASA Astrophysics Data System (ADS)

Wang, L.; Koike, T.

2010-12-01

The climate change-induced variability in hydrological cycles directly affects regional water resources management. For improved multiple multi-objective reservoir operation, an integrated modeling system has been developed by incorporating a global optimization system (SCE-UA) into a distributed biosphere hydrological model (WEB-DHM) coupled with the reservoir routing module. The reservoir storage change is estimated from the difference between the simulated inflows and outflows; while the reservoir water level can be defined from the updated reservoir storage by using the H-V curve. According to the reservoir water level, the new operation rule can be decided. For optimization: (1) WEB-DHM is calibrated for each dam’s inflows separately; (2) then the calibrated WEB-DHM is used to simulate inflows and outflows by assuming outflow proportional to inflow; and (3) the proportion coefficients are optimized with Shuffle Complex Evolution method (SCE-UA), to fulfill an objective function towards minimum flood risk at downstream and maximum reservoir water storage for future use. The GSMaP product offers hourly global precipitation maps in near real-time (about four hours after observation). Aiming at near real-time reservoir operation in large river basins, the integrated modeling system takes the inputs from both an operational global quantitative precipitation forecast (JMA-GPV; to achieve an optimal operation rule in the assumed lead time period) and the GSMaP product (to perform current operation with the obtained optimal rule, after correction by gauge rainfall). The newly-developed system was then applied to the Red River Basin, with an area of 160,000 km2, to test its performance for near real-time dam operation. In Vietnam, three reservoirs are located in the upstream of Hanoi city, with Hoa Binh the largest (69% of total volume). After calibration with the gauge rainfall, the inflows to three reservoirs are well simulated; the discharge and water level at Hanoi city are also well reproduced with the actual dam releases. With the corrected GSMaP rainfall (by using gauge rainfall), the inflows to reservoirs and the water level at Hanoi city can be also reasonably reproduced. The study aims at achieving an optimal operation rule in the lead time period (with the quantitative precipitation forecast) and then using it to perform current operation (with the corrected GSMaP rainfall). At Hanoi, there are relatively low flows in July, but high floods in August 2005. Results show that with the actual operation, dangerous water level in Hanoi was observed; while with the lead-time operation, the water level in Hanoi can be obviously cut down, and maximum water storage is also achieved for Hoa Binh reservoir at the end of flood season.

Cost efficiency of the non-associative flow rule simulation of an industrial component

NASA Astrophysics Data System (ADS)

Galdos, Lander; de Argandoña, Eneko Saenz; Mendiguren, Joseba

2017-10-01

In the last decade, metal forming industry is becoming more and more competitive. In this context, the FEM modeling has become a primary tool of information for the component and process design. Numerous researchers have been focused on improving the accuracy of the material models implemented on the FEM in order to improve the efficiency of the simulations. Aimed at increasing the efficiency of the anisotropic behavior modelling, in the last years the use of non-associative flow rule models (NAFR) has been presented as an alternative to the classic associative flow rule models (AFR). In this work, the cost efficiency of the used flow rule model has been numerically analyzed by simulating an industrial drawing operation with two different models of the same degree of flexibility: one AFR model and one NAFR model. From the present study, it has been concluded that the flow rule has a negligible influence on the final drawing prediction; this is mainly driven by the model parameter identification procedure. Even though the NAFR formulation is complex when compared to the AFR, the present study shows that the total simulation time while using explicit FE solvers has been reduced without loss of accuracy. Furthermore, NAFR formulations have an advantage over AFR formulations in parameter identification because the formulation decouples the yield stress and the Lankford coefficients.

JELC-LITE: Unconventional Instructional Design for Special Operations Training

NASA Technical Reports Server (NTRS)

Friedman, Mark

2012-01-01

Current special operations staff training is based on the Joint Event Life Cycle (JELC). It addresses operational level tasks in multi-week, live military exercises which are planned over a 12 to 18 month timeframe. As the military experiences changing global mission sets, shorter training events using distributed technologies will increasingly be needed to augment traditional training. JELC-Lite is a new approach for providing relevant training between large scale exercises. This new streamlined, responsive training model uses distributed and virtualized training technologies to establish simulated scenarios. It keeps proficiency levels closer to optimal levels -- thereby reducing the performance degradation inherent in periodic training. It can be delivered to military as well as under-reached interagency groups to facilitate agile, repetitive training events. JELC-Lite is described by four phases paralleling the JELC, differing mostly in scope and scale. It has been successfully used with a Theater Special Operations Command and fits well within the current environment of reduced personnel and financial resources.

Extending radiative transfer models by use of Bayes rule. [in atmospheric science

NASA Technical Reports Server (NTRS)

Whitney, C.

1977-01-01

This paper presents a procedure that extends some existing radiative transfer modeling techniques to problems in atmospheric science where curvature and layering of the medium and dynamic range and angular resolution of the signal are important. Example problems include twilight and limb scan simulations. Techniques that are extended include successive orders of scattering, matrix operator, doubling, Gauss-Seidel iteration, discrete ordinates and spherical harmonics. The procedure for extending them is based on Bayes' rule from probability theory.

14 CFR 135.4 - Applicability of rules for eligible on-demand operations.

Code of Federal Regulations, 2011 CFR

2011-01-01

...-demand operations. 135.4 Section 135.4 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT... OPERATIONS OPERATING REQUIREMENTS: COMMUTER AND ON DEMAND OPERATIONS AND RULES GOVERNING PERSONS ON BOARD SUCH AIRCRAFT General § 135.4 Applicability of rules for eligible on-demand operations. (a) An...

Wind Tunnel Testing on Crosswind Aerodynamic Forces Acting on Railway Vehicles

NASA Astrophysics Data System (ADS)

Kwon, Hyeok-Bin; Nam, Seong-Won; You, Won-Hee

This study is devoted to measure the aerodynamic forces acting on two railway trains, one of which is a high-speed train at 300km/h maximum operation speed, and the other is a conventional train at the operating speed 100km/h. The three-dimensional train shapes have been modeled as detailed as possible including the inter-car, the upper cavity for pantograph, and the bogie systems. The aerodynamic forces on each vehicle of the trains have been measured in the subsonic wind tunnel with 4m×3m test section of Korea Aerospace Research Institute at Daejeon, Korea. The aerodynamic forces and moments of the train models have been plotted for various yaw angles and the characteristics of the aerodynamic coefficients has been discussed relating to the experimental conditions.

Reward-based learning under hardware constraints-using a RISC processor embedded in a neuromorphic substrate.

PubMed

Friedmann, Simon; Frémaux, Nicolas; Schemmel, Johannes; Gerstner, Wulfram; Meier, Karlheinz

2013-01-01

In this study, we propose and analyze in simulations a new, highly flexible method of implementing synaptic plasticity in a wafer-scale, accelerated neuromorphic hardware system. The study focuses on globally modulated STDP, as a special use-case of this method. Flexibility is achieved by embedding a general-purpose processor dedicated to plasticity into the wafer. To evaluate the suitability of the proposed system, we use a reward modulated STDP rule in a spike train learning task. A single layer of neurons is trained to fire at specific points in time with only the reward as feedback. This model is simulated to measure its performance, i.e., the increase in received reward after learning. Using this performance as baseline, we then simulate the model with various constraints imposed by the proposed implementation and compare the performance. The simulated constraints include discretized synaptic weights, a restricted interface between analog synapses and embedded processor, and mismatch of analog circuits. We find that probabilistic updates can increase the performance of low-resolution weights, a simple interface between analog synapses and processor is sufficient for learning, and performance is insensitive to mismatch. Further, we consider communication latency between wafer and the conventional control computer system that is simulating the environment. This latency increases the delay, with which the reward is sent to the embedded processor. Because of the time continuous operation of the analog synapses, delay can cause a deviation of the updates as compared to the not delayed situation. We find that for highly accelerated systems latency has to be kept to a minimum. This study demonstrates the suitability of the proposed implementation to emulate the selected reward modulated STDP learning rule. It is therefore an ideal candidate for implementation in an upgraded version of the wafer-scale system developed within the BrainScaleS project.

Reward-based learning under hardware constraints—using a RISC processor embedded in a neuromorphic substrate

PubMed Central

Friedmann, Simon; Frémaux, Nicolas; Schemmel, Johannes; Gerstner, Wulfram; Meier, Karlheinz

2013-01-01

In this study, we propose and analyze in simulations a new, highly flexible method of implementing synaptic plasticity in a wafer-scale, accelerated neuromorphic hardware system. The study focuses on globally modulated STDP, as a special use-case of this method. Flexibility is achieved by embedding a general-purpose processor dedicated to plasticity into the wafer. To evaluate the suitability of the proposed system, we use a reward modulated STDP rule in a spike train learning task. A single layer of neurons is trained to fire at specific points in time with only the reward as feedback. This model is simulated to measure its performance, i.e., the increase in received reward after learning. Using this performance as baseline, we then simulate the model with various constraints imposed by the proposed implementation and compare the performance. The simulated constraints include discretized synaptic weights, a restricted interface between analog synapses and embedded processor, and mismatch of analog circuits. We find that probabilistic updates can increase the performance of low-resolution weights, a simple interface between analog synapses and processor is sufficient for learning, and performance is insensitive to mismatch. Further, we consider communication latency between wafer and the conventional control computer system that is simulating the environment. This latency increases the delay, with which the reward is sent to the embedded processor. Because of the time continuous operation of the analog synapses, delay can cause a deviation of the updates as compared to the not delayed situation. We find that for highly accelerated systems latency has to be kept to a minimum. This study demonstrates the suitability of the proposed implementation to emulate the selected reward modulated STDP learning rule. It is therefore an ideal candidate for implementation in an upgraded version of the wafer-scale system developed within the BrainScaleS project. PMID:24065877

The Influence of Informal Power Structures on School Board-Teacher Union Contract Negotiations.

ERIC Educational Resources Information Center

Miller-Whitehead, Marie

A study examined behaviors of participants trained in a nonadversarial model of contract negotiation, focusing on possible influences of formal and informal power structures, written and unwritten rules, and firmly entrenched adversarial behavior on the bargaining process. Participants were representatives of a district's teacher union and board…

Implementing a Bayes Filter in a Neural Circuit: The Case of Unknown Stimulus Dynamics.

PubMed

Sokoloski, Sacha

2017-09-01

In order to interact intelligently with objects in the world, animals must first transform neural population responses into estimates of the dynamic, unknown stimuli that caused them. The Bayesian solution to this problem is known as a Bayes filter, which applies Bayes' rule to combine population responses with the predictions of an internal model. The internal model of the Bayes filter is based on the true stimulus dynamics, and in this note, we present a method for training a theoretical neural circuit to approximately implement a Bayes filter when the stimulus dynamics are unknown. To do this we use the inferential properties of linear probabilistic population codes to compute Bayes' rule and train a neural network to compute approximate predictions by the method of maximum likelihood. In particular, we perform stochastic gradient descent on the negative log-likelihood of the neural network parameters with a novel approximation of the gradient. We demonstrate our methods on a finite-state, a linear, and a nonlinear filtering problem and show how the hidden layer of the neural network develops tuning curves consistent with findings in experimental neuroscience.

A novel single neuron perceptron with universal approximation and XOR computation properties.

PubMed

Lotfi, Ehsan; Akbarzadeh-T, M-R

2014-01-01

We propose a biologically motivated brain-inspired single neuron perceptron (SNP) with universal approximation and XOR computation properties. This computational model extends the input pattern and is based on the excitatory and inhibitory learning rules inspired from neural connections in the human brain's nervous system. The resulting architecture of SNP can be trained by supervised excitatory and inhibitory online learning rules. The main features of proposed single layer perceptron are universal approximation property and low computational complexity. The method is tested on 6 UCI (University of California, Irvine) pattern recognition and classification datasets. Various comparisons with multilayer perceptron (MLP) with gradient decent backpropagation (GDBP) learning algorithm indicate the superiority of the approach in terms of higher accuracy, lower time, and spatial complexity, as well as faster training. Hence, we believe the proposed approach can be generally applicable to various problems such as in pattern recognition and classification.

U.S. Foreign Policy and the Military Instrument of National Power: Important Questions and a Model for Developing Military Engagement Recommendations

DTIC Science & Technology

2011-05-01

concern for the true welfare of the populace and operated in a 25 repressive and cruel manner towards them.45 Also, institutions from within the...government structure was based on a constitutional, hereditary emirate that was ruled by princes (Amirs) from the Al Sabah ruling family since the middle

TOXPERT: An Expert System for Risk Assessment

PubMed Central

Soto, R. J.; Osimitz, T. G.; Oleson, A.

1988-01-01

TOXPERT is an artificial intelligence based system used to model product safety, toxicology (TOX) and regulatory (REG) decision processes. An expert system shell uses backward chaining rule control to link “marketing approval” goals to the type of product, REG agency, exposure conditions and TOX. Marketing risks are primarily a function of the TOX, hazards and exposure potential. The method employed differentiates between REG requirements in goal seeking control for various types of products. This is accomplished by controlling rule execution by defining frames for each REG agency. In addition, TOXPERT produces classifications of TOX ratings and suggested product labeling. This production rule system uses principles of TOX, REGs, corporate guidelines and internal “rules of thumb.” TOXPERT acts as an advisor for this narrow domain. Advantages are that it can make routine decisions freeing professional's time for more complex problem solving, provide backup and training.

Feynman rules for the Standard Model Effective Field Theory in R ξ -gauges

NASA Astrophysics Data System (ADS)

Dedes, A.; Materkowska, W.; Paraskevas, M.; Rosiek, J.; Suxho, K.

2017-06-01

We assume that New Physics effects are parametrized within the Standard Model Effective Field Theory (SMEFT) written in a complete basis of gauge invariant operators up to dimension 6, commonly referred to as "Warsaw basis". We discuss all steps necessary to obtain a consistent transition to the spontaneously broken theory and several other important aspects, including the BRST-invariance of the SMEFT action for linear R ξ -gauges. The final theory is expressed in a basis characterized by SM-like propagators for all physical and unphysical fields. The effect of the non-renormalizable operators appears explicitly in triple or higher multiplicity vertices. In this mass basis we derive the complete set of Feynman rules, without resorting to any simplifying assumptions such as baryon-, lepton-number or CP conservation. As it turns out, for most SMEFT vertices the expressions are reasonably short, with a noticeable exception of those involving 4, 5 and 6 gluons. We have also supplemented our set of Feynman rules, given in an appendix here, with a publicly available Mathematica code working with the FeynRules package and producing output which can be integrated with other symbolic algebra or numerical codes for automatic SMEFT amplitude calculations.

Human factors phase IV : risk analysis tool for new train control technology.

DOT National Transportation Integrated Search

2005-01-31

This report covers the theoretical development of the safety state model for railroad operations. Using data from a train control technology experiment, experimental application of the model is demonstrated. A stochastic model of system behavior is d...

Human factors phase IV : risk analysis tool for new train control technology

DOT National Transportation Integrated Search

2005-01-01

This report covers the theoretical development of the safety state model for railroad operations. Using data from a train control technology experiment, experimental application of the model is demonstrated. A stochastic model of system behavior is d...

40 CFR Table 4 to Subpart Mmmm of... - Model Rule-Operating Parameters for Existing Sewage Sludge Incineration Units a

Code of Federal Regulations, 2013 CFR

2013-07-01

... Existing Sewage Sludge Incineration Units a 4 Table 4 to Subpart MMMM of Part 60 Protection of Environment... SOURCES Emission Guidelines and Compliance Times for Existing Sewage Sludge Incineration Units Pt. 60... Sewage Sludge Incineration Units a For these operating parameters You must establish these operating...

40 CFR Table 4 to Subpart Mmmm of... - Model Rule-Operating Parameters for Existing Sewage Sludge Incineration Units a

Code of Federal Regulations, 2014 CFR

2014-07-01

... Existing Sewage Sludge Incineration Units a 4 Table 4 to Subpart MMMM of Part 60 Protection of Environment... SOURCES Emission Guidelines and Compliance Times for Existing Sewage Sludge Incineration Units Pt. 60... Sewage Sludge Incineration Units a For these operating parameters You must establish these operating...

The benefits of virtual reality simulator training for laparoscopic surgery.

PubMed

Hart, Roger; Karthigasu, Krishnan

2007-08-01

Virtual reality is a computer-generated system that provides a representation of an environment. This review will analyse the literature with regard to any benefit to be derived from training with virtual reality equipment and to describe the current equipment available. Virtual reality systems are not currently realistic of the live operating environment because they lack tactile sensation, and do not represent a complete operation. The literature suggests that virtual reality training is a valuable learning tool for gynaecologists in training, particularly those in the early stages of their careers. Furthermore, it may be of benefit for the ongoing audit of surgical skills and for the early identification of a surgeon's deficiencies before operative incidents occur. It is only a matter of time before realistic virtual reality models of most complete gynaecological operations are available, with improved haptics as a result of improved computer technology. It is inevitable that in the modern climate of litigation virtual reality training will become an essential part of clinical training, as evidence for its effectiveness as a training tool exists, and in many countries training by operating on live animals is not possible.

A novel chaotic based image encryption using a hybrid model of deoxyribonucleic acid and cellular automata

NASA Astrophysics Data System (ADS)

Enayatifar, Rasul; Sadaei, Hossein Javedani; Abdullah, Abdul Hanan; Lee, Malrey; Isnin, Ismail Fauzi

2015-08-01

Currently, there are many studies have conducted on developing security of the digital image in order to protect such data while they are sending on the internet. This work aims to propose a new approach based on a hybrid model of the Tinkerbell chaotic map, deoxyribonucleic acid (DNA) and cellular automata (CA). DNA rules, DNA sequence XOR operator and CA rules are used simultaneously to encrypt the plain-image pixels. To determine rule number in DNA sequence and also CA, a 2-dimension Tinkerbell chaotic map is employed. Experimental results and computer simulations, both confirm that the proposed scheme not only demonstrates outstanding encryption, but also resists various typical attacks.

75 FR 62639 - Air Ambulance and Commercial Helicopter Operations, Part 91 Helicopter Operations, and Part 135...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-12

...This proposed rule addresses air ambulance and commercial helicopter operations, part 91 helicopter operations, and load manifest requirements for all part 135 aircraft. From 2002 to 2008, there has been an increase in fatal helicopter air ambulance accidents. To address these safety concerns, the FAA is proposing to implement operational procedures and require additional equipment on board helicopter air ambulances. Many of these proposed requirements currently are found in agency guidance publications and would address National Transportation Safety Board (NTSB) safety recommendations. Some of these safety concerns are not unique to the helicopter air ambulance industry and affect all commercial helicopter operations. Accordingly, the FAA also is proposing to amend regulations pertaining to all commercial helicopter operations conducted under part 135 to include equipment requirements, pilot training, and alternate airport weather minima. The changes are intended to provide certificate holders and pilots with additional tools and procedures that will aid in preventing accidents.

Adapting the Goddard research and engineering management exercise (GREMEX) to nonspacecraft environments

NASA Technical Reports Server (NTRS)

Wales, R. O.

1973-01-01

A computerized training aid for all levels of research and development managers is presented. The computer model used for NASA training simulates development of a spacecraft. Operation of the model is described together with instructions for changing the input-data cards to alter the nomenclature and response of the model for use in other training environments.

Making intelligent systems team players. A guide to developing intelligent monitoring systems

NASA Technical Reports Server (NTRS)

Land, Sherry A.; Malin, Jane T.; Thronesberry, Carroll; Schreckenghost, Debra L.

1995-01-01

This reference guide for developers of intelligent monitoring systems is based on lessons learned by developers of the DEcision Support SYstem (DESSY), an expert system that monitors Space Shuttle telemetry data in real time. DESSY makes inferences about commands, state transitions, and simple failures. It performs failure detection rather than in-depth failure diagnostics. A listing of rules from DESSY and cue cards from DESSY subsystems are included to give the development community a better understanding of the selected model system. The G-2 programming tool used in developing DESSY provides an object-oriented, rule-based environment, but many of the principles in use here can be applied to any type of monitoring intelligent system. The step-by-step instructions and examples given for each stage of development are in G-2, but can be used with other development tools. This guide first defines the authors' concept of real-time monitoring systems, then tells prospective developers how to determine system requirements, how to build the system through a combined design/development process, and how to solve problems involved in working with real-time data. It explains the relationships among operational prototyping, software evolution, and the user interface. It also explains methods of testing, verification, and validation. It includes suggestions for preparing reference documentation and training users.

ReactionPredictor: prediction of complex chemical reactions at the mechanistic level using machine learning.

PubMed

Kayala, Matthew A; Baldi, Pierre

2012-10-22

Proposing reasonable mechanisms and predicting the course of chemical reactions is important to the practice of organic chemistry. Approaches to reaction prediction have historically used obfuscating representations and manually encoded patterns or rules. Here we present ReactionPredictor, a machine learning approach to reaction prediction that models elementary, mechanistic reactions as interactions between approximate molecular orbitals (MOs). A training data set of productive reactions known to occur at reasonable rates and yields and verified by inclusion in the literature or textbooks is derived from an existing rule-based system and expanded upon with manual curation from graduate level textbooks. Using this training data set of complex polar, hypervalent, radical, and pericyclic reactions, a two-stage machine learning prediction framework is trained and validated. In the first stage, filtering models trained at the level of individual MOs are used to reduce the space of possible reactions to consider. In the second stage, ranking models over the filtered space of possible reactions are used to order the reactions such that the productive reactions are the top ranked. The resulting model, ReactionPredictor, perfectly ranks polar reactions 78.1% of the time and recovers all productive reactions 95.7% of the time when allowing for small numbers of errors. Pericyclic and radical reactions are perfectly ranked 85.8% and 77.0% of the time, respectively, rising to >93% recovery for both reaction types with a small number of allowed errors. Decisions about which of the polar, pericyclic, or radical reaction type ranking models to use can be made with >99% accuracy. Finally, for multistep reaction pathways, we implement the first mechanistic pathway predictor using constrained tree-search to discover a set of reasonable mechanistic steps from given reactants to given products. Webserver implementations of both the single step and pathway versions of ReactionPredictor are available via the chemoinformatics portal http://cdb.ics.uci.edu/.

Category learning strategies in younger and older adults: Rule abstraction and memorization.

PubMed

Wahlheim, Christopher N; McDaniel, Mark A; Little, Jeri L

2016-06-01

Despite the fundamental role of category learning in cognition, few studies have examined how this ability differs between younger and older adults. The present experiment examined possible age differences in category learning strategies and their effects on learning. Participants were trained on a category determined by a disjunctive rule applied to relational features. The utilization of rule- and exemplar-based strategies was indexed by self-reports and transfer performance. Based on self-reported strategies, the frequencies of rule- and exemplar-based learners were not significantly different between age groups, but there was a significantly higher frequency of intermediate learners (i.e., learners not identifying with a reliance on either rule- or exemplar-based strategies) in the older than younger adult group. Training performance was higher for younger than older adults regardless of the strategy utilized, showing that older adults were impaired in their ability to learn the correct rule or to remember exemplar-label associations. Transfer performance converged with strategy reports in showing higher fidelity category representations for younger adults. Younger adults with high working memory capacity were more likely to use an exemplar-based strategy, and older adults with high working memory capacity showed better training performance. Age groups did not differ in their self-reported memory beliefs, and these beliefs did not predict training strategies or performance. Overall, the present results contradict earlier findings that older adults prefer rule- to exemplar-based learning strategies, presumably to compensate for memory deficits. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Multidimensional Simulation Applied to Water Resources Management

NASA Astrophysics Data System (ADS)

Camara, A. S.; Ferreira, F. C.; Loucks, D. P.; Seixas, M. J.

1990-09-01

A framework for an integrated decision aiding simulation (IDEAS) methodology using numerical, linguistic, and pictorial entities and operations is introduced. IDEAS relies upon traditional numerical formulations, logical rules to handle linguistic entities with linguistic values, and a set of pictorial operations. Pictorial entities are defined by their shape, size, color, and position. Pictorial operators include reproduction (copy of a pictorial entity), mutation (expansion, rotation, translation, change in color), fertile encounters (intersection, reunion), and sterile encounters (absorption). Interaction between numerical, linguistic, and pictorial entities is handled through logical rules or a simplified vector calculus operation. This approach is shown to be applicable to various environmental and water resources management analyses using a model to assess the impacts of an oil spill. Future developments, including IDEAS implementation on parallel processing machines, are also discussed.

Determinants and development of a web-based child mortality prediction model in resource-limited settings: A data mining approach.

PubMed

Tesfaye, Brook; Atique, Suleman; Elias, Noah; Dibaba, Legesse; Shabbir, Syed-Abdul; Kebede, Mihiretu

2017-03-01

Improving child health and reducing child mortality rate are key health priorities in developing countries. This study aimed to identify determinant sand develop, a web-based child mortality prediction model in Ethiopian local language using classification data mining algorithm. Decision tree (using J48 algorithm) and rule induction (using PART algorithm) techniques were applied on 11,654 records of Ethiopian demographic and health survey data. Waikato Environment for Knowledge Analysis (WEKA) for windows version 3.6.8 was used to develop optimal models. 8157 (70%) records were randomly allocated to training group for model building while; the remaining 3496 (30%) records were allocated as the test group for model validation. The validation of the model was assessed using accuracy, sensitivity, specificity and area under Receiver Operating Characteristics (ROC) curve. Using Statistical Package for Social Sciences (SPSS) version 20.0; logistic regressions and Odds Ratio (OR) with 95% Confidence Interval (CI) was used to identify determinants of child mortality. The child mortality rate was 72 deaths per 1000 live births. Breast-feeding (AOR= 1.46, (95% CI [1.22. 1.75]), maternal education (AOR= 1.40, 95% CI [1.11, 1.81]), family planning (AOR= 1.21, [1.08, 1.43]), preceding birth interval (AOR= 4.90, [2.94, 8.15]), presence of diarrhea (AOR= 1.54, 95% CI [1.32, 1.66]), father's education (AOR= 1.4, 95% CI [1.04, 1.78]), low birth weight (AOR= 1.2, 95% CI [0.98, 1.51]) and, age of the mother at first birth (AOR= 1.42, [1.01-1.89]) were found to be determinants for child mortality. The J48 model had better performance, accuracy (94.3%), sensitivity (93.8%), specificity (94.3%), Positive Predictive Value (PPV) (92.2%), Negative Predictive Value (NPV) (94.5%) and, the area under ROC (94.8%). Subsequent to developing an optimal prediction model, we relied on this model to develop a web-based application system for child mortality prediction. In this study, nearly accurate results were obtained by employing decision tree and rule induction techniques. Determinants are identified and a web-based child mortality prediction model in Ethiopian local language is developed. Thus, the result obtained could support child health intervention programs in Ethiopia where trained human resource for health is limited. Advanced classification algorithms need to be tested to come up with optimal models. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Use of an expert system data analysis manager for space shuttle main engine test evaluation

NASA Technical Reports Server (NTRS)

Abernethy, Ken

1988-01-01

The ability to articulate, collect, and automate the application of the expertise needed for the analysis of space shuttle main engine (SSME) test data would be of great benefit to NASA liquid rocket engine experts. This paper describes a project whose goal is to build a rule-based expert system which incorporates such expertise. Experiential expertise, collected directly from the experts currently involved in SSME data analysis, is used to build a rule base to identify engine anomalies similar to those analyzed previously. Additionally, an alternate method of expertise capture is being explored. This method would generate rules inductively based on calculations made using a theoretical model of the SSME's operation. The latter rules would be capable of diagnosing anomalies which may not have appeared before, but whose effects can be predicted by the theoretical model.

Scalability of a Methodology for Generating Technical Trading Rules with GAPs Based on Risk-Return Adjustment and Incremental Training

NASA Astrophysics Data System (ADS)

de La Cal, E. A.; Fernández, E. M.; Quiroga, R.; Villar, J. R.; Sedano, J.

In previous works a methodology was defined, based on the design of a genetic algorithm GAP and an incremental training technique adapted to the learning of series of stock market values. The GAP technique consists in a fusion of GP and GA. The GAP algorithm implements the automatic search for crisp trading rules taking as objectives of the training both the optimization of the return obtained and the minimization of the assumed risk. Applying the proposed methodology, rules have been obtained for a period of eight years of the S&P500 index. The achieved adjustment of the relation return-risk has generated rules with returns very superior in the testing period to those obtained applying habitual methodologies and even clearly superior to Buy&Hold. This work probes that the proposed methodology is valid for different assets in a different market than previous work.

Hydropower application of confined space regulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Franseen, H.W.

1995-12-31

OSHA`s {open_quotes}Permit Required Confined Space{close_quotes} rules, 1910.146, became effective April 15, 1993. Their rules define a {open_quotes}confined space{close_quotes} and {open_quotes}permit required confined space{close_quotes}; provide general requirements for those entering the confined space, for the attendant and entry supervisor; define what a confined space program and permit system should be; and describe training requirements and rescue considerations. Tapoco Inc., began preparing confined space procedures in 1992 using Alcoa Engineering Standards and OSHA`s proposed rules. A joint union management team was formed, and this team began evaluating spaces which meet the confined space definition. In 1993, employees were trained, and all entriesmore » into spaces were done according to Alcoa`s and OSHA`s proposed rules. Rescue teams have been trained at each site. Some unique confined spaces and or unique entry conditions have been encountered which have required extensive evaluation.« less

75 FR 66709 - Commercial Radio Operators Rules

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-29

.... SUMMARY: This document proposes to amend our rules concerning commercial radio operator licenses for... operators service, to determine which rules can be clarified, streamlined, or eliminated. DATES: Submit... Radiotelegraph Operator's Certificates, and seek comment on extending the current five-year license for...

Basic Operational Robotics Instructional System

NASA Technical Reports Server (NTRS)

Todd, Brian Keith; Fischer, James; Falgout, Jane; Schweers, John

2013-01-01

The Basic Operational Robotics Instructional System (BORIS) is a six-degree-of-freedom rotational robotic manipulator system simulation used for training of fundamental robotics concepts, with in-line shoulder, offset elbow, and offset wrist. BORIS is used to provide generic robotics training to aerospace professionals including flight crews, flight controllers, and robotics instructors. It uses forward kinematic and inverse kinematic algorithms to simulate joint and end-effector motion, combined with a multibody dynamics model, moving-object contact model, and X-Windows based graphical user interfaces, coordinated in the Trick Simulation modeling environment. The motivation for development of BORIS was the need for a generic system for basic robotics training. Before BORIS, introductory robotics training was done with either the SRMS (Shuttle Remote Manipulator System) or SSRMS (Space Station Remote Manipulator System) simulations. The unique construction of each of these systems required some specialized training that distracted students from the ideas and goals of the basic robotics instruction.

77 FR 77001 - Comprehensive Review of Licensing and Operating Rules for Satellite Services

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-31

...] Comprehensive Review of Licensing and Operating Rules for Satellite Services AGENCY: Federal Communications... Notice of Proposed Rulemaking that initiated a comprehensive review of the Commission's rules governing... summary of the Order in IB Docket No. 12-267, Comprehensive Review of Licensing and Operating Rules for...

31 CFR 1.28 - Training, rules of conduct, penalties for non-compliance.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Treasury DISCLOSURE OF RECORDS Privacy Act § 1.28 Training, rules of conduct, penalties for non-compliance... Department and the individual employees by the Privacy Act for non-compliance with specified requirements of..., to avoid unauthorized disclosure either orally or in writing, and to insure that no information...

ATV Engineering Support Team Safety Console Preparation for the Johannes Kepler Mission

NASA Astrophysics Data System (ADS)

Chase, R.; Oliefka, L.

2010-09-01

This paper describes the improvements to be implemented in the Safety console position of the Engineering Support Team(EST) at the Automated Transfer Vehicle(ATV) Control Centre(ATV-CC) for the upcoming ATV Johannes Kepler mission. The ATV missions to the International Space Station are monitored and controlled from the ATV-CC in Toulouse, France. The commanding of ATV is performed by the Vehicle Engineering Team(VET) in the main control room under authority of the Flight Director. The EST performs a monitoring function in a room beside the main control room. One of the EST positions is the Safety console, which is staffed by safety engineers from ESA and the industrial prime contractor, Astrium. The function of the Safety console is to check whether the hazard controls are available throughout the mission as required by the Hazard Reports approved by the ISS Safety Review Panel. Safety console preparation activities were limited prior to the first ATV mission due to schedule constraints, and the safety engineers involved have been working to improve the readiness for ATV 2. The following steps have been taken or are in process, and will be described in this paper: • review of the implementation of Operations Control Agreement Documents(OCADs) that record the way operational hazard controls are performed to meet the needs of the Hazard Reports(typically in Flight Rules and Crew Procedures), • crosscheck of operational control needs and implementations with respect to ATV's first flight observations and post flight evaluations, with a view to identifying additional, obsolete or revised operational hazard controls, • participation in the Flight Rule review and update process carried out between missions, • participation in the assessment of anomalies observed during the first ATV mission, to ensure that any impacts are addressed in the ATV 2 safety documentation, • preparation of a Safety console handbook to provide lists of important safety aspects to be monitored at various stages of the mission, including links to relevant Hazard Reports, Flight Rules, and supporting documentation, • participation to training courses conducted in the frame of the ATV Training Academy(ATAC), and provision of courses related to safety for the other members of the VET and EST, • participation to simulations conducted at ATV-CC, including off-nominal cases. The result of these activities will be an improved level of readiness for the ATV 2 mission.

14 CFR 91.139 - Emergency air traffic rules.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 14 Aeronautics and Space 2 2014-01-01 2014-01-01 false Emergency air traffic rules. 91.139 Section...) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Flight Rules General § 91.139 Emergency air traffic rules. (a) This section prescribes a process for utilizing Notices to Airmen...

14 CFR 91.139 - Emergency air traffic rules.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 2 2012-01-01 2012-01-01 false Emergency air traffic rules. 91.139 Section...) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Flight Rules General § 91.139 Emergency air traffic rules. (a) This section prescribes a process for utilizing Notices to Airmen...

14 CFR 91.139 - Emergency air traffic rules.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 2 2010-01-01 2010-01-01 false Emergency air traffic rules. 91.139 Section...) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Flight Rules General § 91.139 Emergency air traffic rules. (a) This section prescribes a process for utilizing Notices to Airmen...

An operation support expert system based on on-line dynamics simulation and fuzzy reasoning for startup schedule optimization in fossil power plants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Matsumoto, H.; Eki, Y.; Kaji, A.

1993-12-01

An expert system which can support operators of fossil power plants in creating the optimum startup schedule and executing it accurately is described. The optimum turbine speed-up and load-up pattern is obtained through an iterative manner which is based on fuzzy resonating using quantitative calculations as plant dynamics models and qualitative knowledge as schedule optimization rules with fuzziness. The rules represent relationships between stress margins and modification rates of the schedule parameters. Simulations analysis proves that the system provides quick and accurate plant startups.

A CLIPS-based expert system for the evaluation and selection of robots

NASA Technical Reports Server (NTRS)

Nour, Mohamed A.; Offodile, Felix O.; Madey, Gregory R.

1994-01-01

This paper describes the development of a prototype expert system for intelligent selection of robots for manufacturing operations. The paper first develops a comprehensive, three-stage process to model the robot selection problem. The decisions involved in this model easily lend themselves to an expert system application. A rule-based system, based on the selection model, is developed using the CLIPS expert system shell. Data about actual robots is used to test the performance of the prototype system. Further extensions to the rule-based system for data handling and interfacing capabilities are suggested.

Adaptive time-variant models for fuzzy-time-series forecasting.

PubMed

Wong, Wai-Keung; Bai, Enjian; Chu, Alice Wai-Ching

2010-12-01

A fuzzy time series has been applied to the prediction of enrollment, temperature, stock indices, and other domains. Related studies mainly focus on three factors, namely, the partition of discourse, the content of forecasting rules, and the methods of defuzzification, all of which greatly influence the prediction accuracy of forecasting models. These studies use fixed analysis window sizes for forecasting. In this paper, an adaptive time-variant fuzzy-time-series forecasting model (ATVF) is proposed to improve forecasting accuracy. The proposed model automatically adapts the analysis window size of fuzzy time series based on the prediction accuracy in the training phase and uses heuristic rules to generate forecasting values in the testing phase. The performance of the ATVF model is tested using both simulated and actual time series including the enrollments at the University of Alabama, Tuscaloosa, and the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX). The experiment results show that the proposed ATVF model achieves a significant improvement in forecasting accuracy as compared to other fuzzy-time-series forecasting models.

The effect of experience, simulator-training and biometric feedback on manual ventilation technique.

PubMed

Lewis, Rebecca; Sherfield, Cerrie A; Fellows, Christopher R; Burrow, Rachel; Young, Iain; Dugdale, Alex

2017-05-01

To determine the frequency of provision and main providers (veterinary surgeons, nurses or trainees) of manual ventilation in UK veterinary practices. Furthermore, to determine the variation in peak inspiratory (inflation) pressure (PIP), applied to a lung model during manual ventilation, by three different groups of operators (inexperienced, experienced and specialist), before and after training. Questionnaire survey, lung model simulator development and prospective testing. Postal questionnaires were sent to 100 randomly selected veterinary practices. The lung model simulator was manually ventilated in a staged process over 3 weeks, with and without real-time biometric feedback (PIP display), by three groups of volunteer operators: inexperienced, experienced and specialist. The questionnaires determined that veterinary nurses were responsible for providing the majority of manual ventilation in veterinary practices, mainly drawing on theoretical knowledge rather than any specific training. Thoracic surgery and apnoea were the main reasons for provision of manual ventilation. Specialists performed well when manually ventilating the lung model, regardless of feedback training. Both inexperienced and experienced operators showed significant improvement in technique when using the feedback training tool: variation in PIP decreased significantly until operators provided manual ventilation at PIPs within the defined optimum range. Preferences for different forms of feedback (graphical, numerical or scale display), revealed that the operators' choice was not always the method which gave least variation in PIP. This study highlighted a need for training in manual ventilation at an early stage in veterinary and veterinary nursing careers and demonstrated how feedback is important in the process of experiential learning. A manometer device which can provide immediate feedback during training, or indeed in a real clinical setting, should improve patient safety. Copyright © 2017 Association of Veterinary Anaesthetists and American College of Veterinary Anesthesia and Analgesia. Published by Elsevier Ltd. All rights reserved.

Transfer between local and global processing levels by pigeons (Columba livia) and humans (Homo sapiens) in exemplar- and rule-based categorization tasks.

PubMed

Aust, Ulrike; Braunöder, Elisabeth

2015-02-01

The present experiment investigated pigeons' and humans' processing styles-local or global-in an exemplar-based visual categorization task in which category membership of every stimulus had to be learned individually, and in a rule-based task in which category membership was defined by a perceptual rule. Group Intact was trained with the original pictures (providing both intact local and global information), Group Scrambled was trained with scrambled versions of the same pictures (impairing global information), and Group Blurred was trained with blurred versions (impairing local information). Subsequently, all subjects were tested for transfer to the 2 untrained presentation modes. Humans outperformed pigeons regarding learning speed and accuracy as well as transfer performance and showed good learning irrespective of group assignment, whereas the pigeons of Group Blurred needed longer to learn the training tasks than the pigeons of Groups Intact and Scrambled. Also, whereas humans generalized equally well to any novel presentation mode, pigeons' transfer from and to blurred stimuli was impaired. Both species showed faster learning and, for the most part, better transfer in the rule-based than in the exemplar-based task, but there was no evidence of the used processing mode depending on the type of task (exemplar- or rule-based). Whereas pigeons relied on local information throughout, humans did not show a preference for either processing level. Additional tests with grayscale versions of the training stimuli, with versions that were both blurred and scrambled, and with novel instances of the rule-based task confirmed and further extended these findings. PsycINFO Database Record (c) 2015 APA, all rights reserved.

Commercial Training Device Requirement (CTDR) for Initial Entry Rotary Wing (IERW) Aviation Training Helicopter

DTIC Science & Technology

1989-12-24

training; 16 . PRICE CODE 17. SECURITY CLASSIFICATION 18. SECURITY CLASSIFICATION 19. SECURITY CLASSIFICATION 20. LIMITATION OF ABSTRACT OF REPORT OF...to be leased is 205. One hundred aircraft will be VFR aircraft only. One hundred and five aircraft will be instrument flight rules ( IFR ) certified, 55...of which will be IFR equipped. The other IFR -certified aircraft will be visual flight rules equipped. c. The total lease cost is based on an assumed

Development and Validity of a Silicone Renal Tumor Model for Robotic Partial Nephrectomy Training.

PubMed

Monda, Steven M; Weese, Jonathan R; Anderson, Barrett G; Vetter, Joel M; Venkatesh, Ramakrishna; Du, Kefu; Andriole, Gerald L; Figenshau, Robert S

2018-04-01

To provide a training tool to address the technical challenges of robot-assisted laparoscopic partial nephrectomy, we created silicone renal tumor models using 3-dimensional printed molds of a patient's kidney with a mass. In this study, we assessed the face, content, and construct validity of these models. Surgeons of different training levels completed 4 simulations on silicone renal tumor models. Participants were surveyed on the usefulness and realism of the model as a training tool. Performance was measured using operation-specific metrics, self-reported operative demands (NASA Task Load Index [NASA TLX]), and blinded expert assessment (Global Evaluative Assessment of Robotic Surgeons [GEARS]). Twenty-four participants included attending urologists, endourology fellows, urology residents, and medical students. Post-training surveys of expert participants yielded mean results of 79.2 on the realism of the model's overall feel and 90.2 on the model's overall usefulness for training. Renal artery clamp times and GEARS scores were significantly better in surgeons further in training (P ≤.005 and P ≤.025). Renal artery clamp times, preserved renal parenchyma, positive margins, NASA TLX, and GEARS scores were all found to improve across trials (P <.001, P = .025, P = .024, P ≤.020, and P ≤.006, respectively). Face, content, and construct validity were demonstrated in the use of a silicone renal tumor model in a cohort of surgeons of different training levels. Expert participants deemed the model useful and realistic. Surgeons of higher training levels performed better than less experienced surgeons in various study metrics, and improvements within individuals were observed over sequential trials. Future studies should aim to assess model predictive validity, namely, the association between model performance improvements and improvements in live surgery. Copyright © 2018 Elsevier Inc. All rights reserved.

A Biologically Inspired Computational Model of Basal Ganglia in Action Selection

PubMed Central

Baston, Chiara

2015-01-01

The basal ganglia (BG) are a subcortical structure implicated in action selection. The aim of this work is to present a new cognitive neuroscience model of the BG, which aspires to represent a parsimonious balance between simplicity and completeness. The model includes the 3 main pathways operating in the BG circuitry, that is, the direct (Go), indirect (NoGo), and hyperdirect pathways. The main original aspects, compared with previous models, are the use of a two-term Hebb rule to train synapses in the striatum, based exclusively on neuronal activity changes caused by dopamine peaks or dips, and the role of the cholinergic interneurons (affected by dopamine themselves) during learning. Some examples are displayed, concerning a few paradigmatic cases: action selection in basal conditions, action selection in the presence of a strong conflict (where the role of the hyperdirect pathway emerges), synapse changes induced by phasic dopamine, and learning new actions based on a previous history of rewards and punishments. Finally, some simulations show model working in conditions of altered dopamine levels, to illustrate pathological cases (dopamine depletion in parkinsonian subjects or dopamine hypermedication). Due to its parsimonious approach, the model may represent a straightforward tool to analyze BG functionality in behavioral experiments. PMID:26640481

Multi-criteria objective based climate change impact assessment for multi-purpose multi-reservoir systems

NASA Astrophysics Data System (ADS)

Müller, Ruben; Schütze, Niels

2014-05-01

Water resources systems with reservoirs are expected to be sensitive to climate change. Assessment studies that analyze the impact of climate change on the performance of reservoirs can be divided in two groups: (1) Studies that simulate the operation under projected inflows with the current set of operational rules. Due to non adapted operational rules the future performance of these reservoirs can be underestimated and the impact overestimated. (2) Studies that optimize the operational rules for best adaption of the system to the projected conditions before the assessment of the impact. The latter allows for estimating more realistically future performance and adaption strategies based on new operation rules are available if required. Multi-purpose reservoirs serve various, often conflicting functions. If all functions cannot be served simultaneously at a maximum level, an effective compromise between multiple objectives of the reservoir operation has to be provided. Yet under climate change the historically preferenced compromise may no longer be the most suitable compromise in the future. Therefore a multi-objective based climate change impact assessment approach for multi-purpose multi-reservoir systems is proposed in the study. Projected inflows are provided in a first step using a physically based rainfall-runoff model. In a second step, a time series model is applied to generate long-term inflow time series. Finally, the long-term inflow series are used as driving variables for a simulation-based multi-objective optimization of the reservoir system in order to derive optimal operation rules. As a result, the adapted Pareto-optimal set of diverse best compromise solutions can be presented to the decision maker in order to assist him in assessing climate change adaption measures with respect to the future performance of the multi-purpose reservoir system. The approach is tested on a multi-purpose multi-reservoir system in a mountainous catchment in Germany. A climate change assessment is performed for climate change scenarios based on the SRES emission scenarios A1B, B1 and A2 for a set of statistically downscaled meteorological data. The future performance of the multi-purpose multi-reservoir system is quantified and possible intensifications of trade-offs between management goals or reservoir utilizations are shown.

19 CFR 102.17 - Non-qualifying operations.

Code of Federal Regulations, 2010 CFR

2010-04-01

... TREASURY RULES OF ORIGIN Rules of Origin § 102.17 Non-qualifying operations. A foreign material shall not... General Rule of Interpretation 2(a), without any additional operation other than minor processing. [T.D...

40 CFR 60.5225 - What are the monitoring and calibration requirements for compliance with my operating limits?

Code of Federal Regulations, 2011 CFR

2011-07-01

... requirements for compliance with my operating limits? 60.5225 Section 60.5225 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) STANDARDS OF PERFORMANCE FOR NEW STATIONARY SOURCES Emission Guidelines and Compliance Times for Existing Sewage Sludge Incineration Units Model Rule...