Bridge-Level Optimization Module for Planning and Programming

2021 ◽  
pp. 036119812110413
Author(s):  
Karim Naji ◽  
Erin Santini-Bell ◽  
Kyle Kwiatkowski
Keyword(s):  
Asset Management ◽  
Element Level ◽  
Predicting Performance ◽  
Asset Class ◽  
Potential Benefits ◽  
Short And Long Term ◽  
And Performance ◽  
Departments Of Transportation ◽  
Underlying Processes

The paper briefly introduces an element-based multi-objective optimization (EB-MOO) methodology to support state departments of transportation with their decision-making process, asset management, and performance-based transportation planning and programming. The methodology focuses on the bridge asset class and consists of five modules: (i) data processing, (ii) improvement, (iii) element-level optimization (ELO), (iv) bridge-level optimization (BLO), and (v) network-level optimization (NLO) modules. These five modules jointly produce short- and long-term intervention strategies detailed at the bridge element level for planning and programming. The paper focuses on the BLO module, specifically: the basic framework of underlying processes and concepts, the optimization problem types and mathematical formulations, and the heuristic algorithm to solve the BLO problems. A prototyping tool is developed to implement these five modules of the EB-MOO methodology, test concepts, prove effectiveness, and demonstrate potential benefits. The paper also includes an illustrative example using the prototyping tool. The example consists of the BLO problems under different budget and/or performance scenarios. The implementation proves the module’s capability in producing a diverse set of Pareto optimal or near-optimal solutions, recommending set of element intervention actions and timings, predicting performance, and determining budget requirements for the entire program period. The BLO results associated with the recommended solutions serve as the fundamental inputs for the NLO module. Nevertheless, the BLO module can be used independently, providing a systematic process for the development of bridge improvement/preservation programs detailed at the element level.

Element-Level Optimization Module for Bridge Planning and Programming

2021 ◽  
pp. 036119812110413
Author(s):  
Karim Naji ◽  
Erin Santini-Bell ◽  
Kyle Kwiatkowski
Keyword(s):  
Multiobjective Optimization ◽  
Performance Management ◽  
Element Level ◽  
Screening Process ◽  
Predicting Performance ◽  
Asset Class ◽  
Decision Making Processes ◽  
Short And Long Term ◽  
Optimization Methodology ◽  
And Performance

The overall objective of this research is to support state departments of transportation with their decision-making processes and transitions to performance management and performance-based planning and programming mandated by the Moving Ahead for Progress in the 21st Century Act. Accomplishing this objective requires a systematic multiobjective optimization methodology. This research proposes such a methodology, referred to as an “element-based multiobjective optimization” (EB-MOO) methodology, which produces optimal or near-optimal sets of short- and long-term intervention strategies detailed at the bridge element level for planning and programming. The methodology currently focuses on the bridge asset class and consists of five modules: (1) data processing, (2) improvement, (3) element-level optimization (ELO), (4) bridge-level optimization (BLO), and (5) network-level optimization (NLO) modules. This paper details the ELO module, specifically: the basic framework of underlying processes and concepts, the alternative feasibility screening process, optimization problem types and mathematical formulations, and the heuristic algorithm used to solve the ELO problems. The paper also includes an illustrative example using a prototyping tool developed to implement EB-MOO methodology. The example presents several ELO problems under unconstrained scenarios. The implementation demonstrated the module’s capability in producing optimal or near-optimal ELO solutions, recommending element intervention actions, predicting performance, and determining funding requirements for the specified improvement type and program year. The broader EB-MOO methodology uses the ELO results as inputs for the BLO and NLO modules.

Reduced volume and increased training intensity elevate muscle Na+-K+pump α2-subunit expression as well as short- and long-term work capacity in humans

2009 ◽  
Vol 107 (6) ◽  
pp. 1771-1780 ◽  
Author(s):  
Jens Bangsbo ◽  
Thomas P. Gunnarsson ◽  
Jesper Wendell ◽  
Lars Nybo ◽  
Martin Thomassen
Keyword(s):  
Endurance Training ◽  
Muscle Protein ◽  
Work Capacity ◽  
Control Group ◽  
Muscle Adaptations ◽  
Subunit Expression ◽  
Short And Long Term ◽  
And Performance ◽  
Trained Runners

The present study examined muscle adaptations and alterations in work capacity in endurance-trained runners as a result of a reduced amount of training combined with speed endurance training. For a 6- to 9-wk period, 17 runners were assigned to either a speed endurance group with a 25% reduction in the amount of training but including speed endurance training consisting of six to twelve 30-s sprint runs 3–4 times/wk (SET group n = 12) or a control group ( n = 5), which continued the endurance training (∼55 km/wk). For the SET group, the expression of the muscle Na+-K+pump α2-subunit was 68% higher ( P < 0.05) and the plasma K+level was reduced ( P < 0.05) during repeated intense running after 9 wk. Performance in a 30-s sprint test and the first of the supramaximal exhaustive runs was improved ( P < 0.05) by 7% and 36%, respectively, after the speed endurance training period. In the SET group, maximal O2uptake was unaltered, but the 3-km (3,000-m) time was reduced ( P < 0.05) from 10.4 ± 0.1 to 10.1 ± 0.1 min and the 10-km (10,000-m) time was improved from 37.3 ± 0.4 to 36.3 ± 0.4 min (means ± SE). Muscle protein expression and performance remained unaltered in the control group. The present data suggest that both short- and long-term exercise performances can be improved with a reduction in training volume if speed endurance training is performed and that the Na+-K+pump plays a role in the control of K+homeostasis and in the development of fatigue during repeated high-intensity exercise.

Towards a Methodology for Monitoring and Analyzing the Supply Chain Behavior

2011 ◽  
pp. 186-208
Author(s):  
Reinaldo Moraga ◽  
Luis Rabelo ◽  
Alfonso Sarmiento
Keyword(s):  
Neural Networks ◽  
Sensitivity Analysis ◽  
Supply Chain ◽  
System Dynamics ◽  
Eigenvalue Analysis ◽  
Background Information ◽  
Short And Long Term ◽  
And Performance

In this chapter, the authors present general steps towards a methodology that contributes to the advancement of prediction and mitigation of undesirable supply chain behavior within short- and long- term horizons by promoting a better understanding of the structure that determines the behavior modes. Through the integration of tools such as system dynamics, neural networks, eigenvalue analysis, and sensitivity analysis, this methodology (1) captures the dynamics of the supply chain, (2) detects changes and predicts the behavior based on these changes, and (3) defines needed modifications to mitigate the unwanted behaviors and performance. In the following sections, some background information is given from literature, the general steps of the proposed methodology are discussed, and finally a case study is briefly summarized.

“Adaptative” User Interface for Expert Knowledge Validation and Evaluations Interpretation in an Asset Management Process

2007 ◽  
Author(s):  
P. Hai¨k ◽  
S. Parfouru ◽  
C. Bauby ◽  
S. Mahe
Keyword(s):  
User Interface ◽  
Asset Management ◽  
Expert Knowledge ◽  
Decision Makers ◽  
Technical Management ◽  
Base Content ◽  
Maintenance Policies ◽  
And Performance

The long term management of a production asset raises several major issues among which rank the technical management of the plant, its economics and the fleet level perspective one has to adopt. Decision makers are therefore faced with the need to define long term policies (up to the end of asset operation) which take into account multiple criteria including safety (which is paramount) and performance. In this paper we first remind the reader of the EDF three-level methodology for asset management. We then focus on the knowledge model and on the software tools that implement this methodology in order to gather, preserve, share, maintain and exploit the expert knowledge needed for asset management and to allow decision makers to define, evaluate and analyze long term plant operation and maintenance policies. Lastly, as the quality of the processed plant level evaluations (operation & maintenance strategies are evaluated, at a plantlevel, through a set of technical and economic indicators) and their interpretation relies on the quality of the knowledge captured in the tools, we focus on the definition of a “adaptative” user interface — based on Electronic Structured Documents — that allows technical/strategic experts and decision makers to consult the useful pieces of knowledge in a context dependent way. Such an interface, which, in a near future, should be fully implemented in the tools will facilitate the validation of the knowledge-base content and the analysis of the processed results.

scholarly journals Nutra-ergonomics: influence of nutrition on physical employment standards and the health of workers

2016 ◽  
Vol 41 (6 (Suppl. 2)) ◽  
pp. S165-S174 ◽  
Author(s):  
Jane Shearer ◽  
Terry E. Graham ◽  
Tina L. Skinner
Keyword(s):  
Worker Safety ◽  
Work Schedule ◽  
Physical And Mental Health ◽  
Health And Wellbeing ◽  
Workplace Productivity ◽  
Employment Standards ◽  
Short And Long Term ◽  
And Performance

The importance of ergonomics across several scientific domains, including biomechanics, psychology, sociology, and physiology, have been extensively explored. However, the role of other factors that may influence the health and productivity of workers, such as nutrition, is generally overlooked. Nutra-ergonomics describes the interface between workers, their work environment, and performance in relation to their nutritional status. It considers nutrition to be an integral part of a safe and productive workplace that encompasses physical and mental health as well as the long-term wellbeing of workers. This review explores the knowledge, awareness, and common practices of nutrition, hydration, stimulants, and fortified product use employed prior to physical employment standards testing and within the workplace. The influence of these nutra-ergonomic strategies on physical employment standards, worker safety, and performance will be examined. Further, the roles, responsibilities, and implications for the applicant, worker, and the employer will be discussed within the context of nutra-ergonomics, with reference to the provision and sustainability of an environment conducive to optimize worker health and wellbeing. Beyond physical employment standards, workplace productivity, and performance, the influence of extended or chronic desynchronization (irregular or shift work) in the work schedule on metabolism and long-term health, including risk of developing chronic and complex diseases, is discussed. Finally, practical nutra-ergonomic strategies and recommendations for the applicant, worker, and employer alike will be provided to enhance the short- and long-term safety, performance, health, and wellbeing of workers.

A Comprehensive Validated Model of Innovation and Performance: An Empirical Study of Turkish Companies

2020 ◽  
Vol 17 (03) ◽  
pp. 2050019
Author(s):  
Eyup Calik ◽  
Basak Cetinguc ◽  
Fethi Calisir
Keyword(s):  
Firm Performance ◽  
Structural Equation ◽  
Innovation Process ◽  
Equation Modeling ◽  
Innovation Culture ◽  
Short And Long Term ◽  
Innovation Output ◽  
And Performance ◽  
Sequential Relationship

Organizations should maintain their innovation trajectories by developing products, processes, marketing, and organizational methods to achieve and sustain competitive advantage. However, by itself, creating value through innovation is not enough for companies: transforming these innovations into firm performance is also crucial. This study aims to validate the relationships among innovation and firm performance components and to explore the effect of innovation culture on innovation components and personnel performance. In our model, the innovation construct is comprised of innovation input, innovation process, and innovation output components, while firm performance construct includes four performance components such as financial, customer, market, and personnel performance. Moreover, this comprehensive model was proposed based on the literature, and structural equation modeling (SEM) was performed by employing data gained from 353 companies in Turkey to validate the model. According to the results, there is a sequential relationship within innovation components and firm performance components, while the relationships among innovation components and firm performance components are observed holistically. This paper contributes to the innovation literature by introducing a validated model to clarify these relationships. This model can be evaluated by company leaders to identify not only their firm’s innovation path but also short and long-term innovation results. Furthermore, the findings indicate that companies should manage the system from innovation input to financial gains without delicately compromising the whole sequential and holistic relationship. Managers should also be aware of the power of innovation culture on innovation path and personnel performance directly to create a convenient atmosphere.

Working Memory Training From an Individual Differences Perspective

2019 ◽  
pp. 14-39
Author(s):  
Erika Borella ◽  
Barbara Carretti ◽  
Cesare Cornoldi ◽  
Rossana De Beni
Keyword(s):  
Older Adults ◽  
Working Memory ◽  
Task Demands ◽  
Memory Training ◽  
Training Procedure ◽  
Adaptive Procedure ◽  
Age Related ◽  
Short And Long Term ◽  
Underlying Processes

This chapter presents and discusses a verbal WM training developed for older adults. The model of working memory (WM) proposed by Cornoldi and Vecchi, which is based on an analysis of individual and age-related differences, is used as a framework for discussing the efficacy of the WM training procedure proposed and developed for older adults. The model (a) assumes that different WM tasks (and underlying processes) may be located along two continua that describe the type of content to be processed and the degree of active control required by the task and (b) considers metacognitive/motivational aspects, which also have a role in determining WM performance. The WM training procedure presented here takes into account not only the capacity to use WM resources and attentional control by adopting an adaptive procedure, but also the importance of including variations in the training task demands to produce a challenging and engaging task that sustains motivation and favor the training’s short- and long-term efficacy, at least in older adults. These aspects seem crucial in explaining the results obtained with this verbal WM training program in aging.

Short- and Long-Term Changes in Joint Co-Contraction Associated With Motor Learning as Revealed From Surface EMG

2002 ◽  
Vol 88 (2) ◽  
pp. 991-1004 ◽  
Author(s):  
Rieko Osu ◽  
David W. Franklin ◽  
Hiroko Kato ◽  
Hiroaki Gomi ◽  
Kazuhisa Domen ◽  
...  
Keyword(s):  
Surface Emg ◽  
Internal Models ◽  
Series Data ◽  
Time Step ◽  
Cross Correlation Analysis ◽  
Performance Error ◽  
Short And Long Term ◽  
And Performance ◽  
The Brain

In the field of motor control, two hypotheses have been controversial: whether the brain acquires internal models that generate accurate motor commands, or whether the brain avoids this by using the viscoelasticity of musculoskeletal system. Recent observations on relatively low stiffness during trained movements support the existence of internal models. However, no study has revealed the decrease in viscoelasticity associated with learning that would imply improvement of internal models as well as synergy between the two hypothetical mechanisms. Previously observed decreases in electromyogram (EMG) might have other explanations, such as trajectory modifications that reduce joint torques. To circumvent such complications, we required strict trajectory control and examined only successful trials having identical trajectory and torque profiles. Subjects were asked to perform a hand movement in unison with a target moving along a specified and unusual trajectory, with shoulder and elbow in the horizontal plane at the shoulder level. To evaluate joint viscoelasticity during the learning of this movement, we proposed an index of muscle co-contraction around the joint (IMCJ). The IMCJ was defined as the summation of the absolute values of antagonistic muscle torques around the joint and computed from the linear relation between surface EMG and joint torque. The IMCJ during isometric contraction, as well as during movements, was confirmed to correlate well with joint stiffness estimated using the conventional method, i.e., applying mechanical perturbations. Accordingly, the IMCJ during the learning of the movement was computed for each joint of each trial using estimated EMG-torque relationship. At the same time, the performance error for each trial was specified as the root mean square of the distance between the target and hand at each time step over the entire trajectory. The time-series data of IMCJ and performance error were decomposed into long-term components that showed decreases in IMCJ in accordance with learning with little change in the trajectory and short-term interactions between the IMCJ and performance error. A cross-correlation analysis and impulse responses both suggested that higher IMCJs follow poor performances, and lower IMCJs follow good performances within a few successive trials. Our results support the hypothesis that viscoelasticity contributes more when internal models are inaccurate, while internal models contribute more after the completion of learning. It is demonstrated that the CNS regulates viscoelasticity on a short- and long-term basis depending on performance error and finally acquires smooth and accurate movements while maintaining stability during the entire learning process.

Acute Postoperative Pain

2017 ◽  
Author(s):  
Kelly Zach ◽  
Julio A. Gonzalez-Sotomayor
Keyword(s):  
Postoperative Pain ◽  
Patient Characteristics ◽  
Current Evidence ◽  
Long Term Outcomes ◽  
Acute Postoperative Pain ◽  
Analgesic Regimen ◽  
Potential Benefits ◽  
Short And Long Term ◽  
Selection Of

Inadequate management of acute postoperative pain increases morbidity and mortality. Poorly controlled pain results in delayed hospital discharge and may lead to the development of chronic pain. Current evidence supports the implementation of a multimodal analgesic regimen, where different pharmacologic and nonpharmacologic interventions are used. The selection of the different components of this multimodal analgesic approach should consider their potential benefits and limitations, as well as the unique patient characteristics and the surgical procedure. It is the responsibility of the perioperative health care provider to formulate an optimal pain management strategy to ultimately enhance patient satisfaction and improve short- and long-term outcomes.

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