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Purpose: The purpose of this research is to review literature about the performance assessment (PA) in urban fire departments (FDs) to gain state-of-the-art of the fire departments' performance assessment (FDPA) and identify its most applied methods and indicators. Design/methodology/approach: A five-stage structured literature review (SLR) is conducted to review the FDPA-related studies; then, the statistical analysis is applied to reveal more information from the extracted data and design a general framework for FDPA. Findings: The systematic literature review resulted in 336 independent variables for FDPA and finding the data envelopment analysis (DEA) as the most applied FDPA method among the mathematical and statistical models in the reviewed papers. By using analysis outcomes, a general conceptual framework for FDPA is proposed. Research limitations/implications: The reviewed studies were limited to assessments at the strategic level and urban fire protection services. Practical implications: The results of this research can support fire protection service managers, decision-makers, PA researchers and academicians to have a better understanding of FDPA and state-of-the-art in this field. Originality/value: A considerable number of studies have been done about the FDPA to provide methods to improve the efficiency and effectiveness of FDs. Although there are reviews about PA in fire service areas, to the best of our knowledge, no study has been done about FDPA. [ABSTRACT FROM AUTHOR]

Land models, which have been developed by the modeling community in the past two decades to predict future states of ecosystems and climate, have to be critically evaluated for their performance skills of simulating ecosystem responses and feedback to climate change. Benchmarking is an emerging procedure to measure and evaluate performance of models against a set of defined standards. This paper proposes a benchmarking framework for evaluation of land models. The framework includes (1) targeted aspects of model performance to be evaluated; (2) a set of benchmarks as defined references to test model performance; (3) metrics to measure and compare performance skills among models so as to identify model strengths and deficiencies; and (4) model improvement. Component 4 may or may not be involved in a benchmark analysis but is an ultimate goal of general modeling research. Land models are required to simulate exchange of water, energy, carbon and sometimes other trace gases between the atmosphere and the land-surface, and should be evaluated for their simulations of biophysical processes, biogeochemical cycles, and vegetation dynamics across timescales in response to both weather and climate change. Benchmarks that are used to evaluate models generally consist of direct observations, data-model products, and data-derived patterns and relationships. Metrics of measuring mismatches between models and benchmarks may include (1) a priori thresholds of acceptable model performance and (2) a scoring system to combine data-model mismatches for various processes at different temporal and spatial scales. The benchmark analyses should identify clues of weak model performance for future improvement. Iterations between model evaluation and improvement via benchmarking shall demonstrate progress of land modeling and help establish confidence in land models for their predictions of future states of ecosystems and climate. [ABSTRACT FROM AUTHOR]

Direct-drive wave energy converter (WEC) and buoy control algorithms have shown great potential for renewable wave energy extraction in ideal conditions. However the actual power take-off (PTO) impacts are barely considered in the WEC design. This paper highlights the demands of designing the WEC wave-to-wire control from a global point of view by studying the actual PTO impacts. A permanent magnet linear electrical machine (LEM) PTO unit is simulated and controlled to fulfill the WEC buoy control requirements. Several state of the art control algorithms, which include singular-arc (SA) control, shape-based (SB) control, model predictive control (MPC), and proportional-derivative (PD) control, are applied to maximize the wave energy production (mechanical energy). Multiple types of electrical PTOs, including ideal PTO, unlimited PTO and limited PTO, are all implemented to evaluate WEC wave-to-wire performances. Further, the PTO copper loss model and the PTO actual efficiency maps are introduced and studied to improve the electrical PTO operation efficiency. To further assess the control schemes in various wave conditions, one-year PacWave ground-truth data is applied as well. Numerical simulations are conducted using MATLAB/Simulink and the Simscape toolbox. The electrical PTO unit is composed of a LEM, an ideal inverter, and an ideal energy storage system. The results show that the actual PTO will impact the constrained controls (MPC and SB) less comapring to unconstrained controls (SA and PD). Although SB can produce the maximum energy with the limited PTOs, it is not robust for all wave conditions. At the end of the paper, the possible solutions for improving the WEC wave-to-wire performances are also provided. [ABSTRACT FROM AUTHOR]

Multi-frequency radars offer enhanced detection of clouds and precipitation compared to single-frequency systems, and are able to make more accurate retrievals when several frequencies are available simultaneously. An evaluation of a spaceborne three-frequency Ku/Ka/W-band radar system is presented in this study, based on modeling radar reflectivities from the results of a global cloud-resolving model with a 875m grid spacing. To produce the reflectivities, a scattering model has been developed for each of the hydrometeor types produced by the model, as well as for melting snow. The effects of attenuation and multiple scattering on the radar signal are modeled using a radiative transfer model, while nonuniform beam filling is reproduced with spatial averaging. The combined effects of these are then quantified both globally and in five localized case studies. Two different orbital scenarios using the same radar are compared. Overall, based on the results, it is expected that the proposed radar would detect a high-quality signal in most clouds and precipitation. The main exceptions are the thinnest clouds that are below the detection threshold of the W-band channel, and at the opposite end of the scale, heavy convective rainfall where a combination of attenuation, multiple scattering and nonuniform beam filling commonly cause significant deterioration of the signal; thus, while the latter can be generally detected, the quality of the retrievals is likely to be degraded. [ABSTRACT FROM AUTHOR]

A community diagnostics and performance metrics tool for the evaluation of Earth System Models (ESMs) has been developed that allows for routine comparison of single or multiple models, either against predecessor versions or against observations. The priority of the effort so far has been to target specific scientific themes focusing on selected Essential Climate Variables (ECVs), a range of known systematic biases common to ESMs, such as coupled tropical climate variability, monsoons, Southern Ocean processes, continental dry biases and soil hydrology-climate interactions, as well as atmospheric CO2 budgets, tropospheric and stratospheric ozone, and tropospheric aerosols. The tool is being developed in such a way that additional analyses can easily be added. A set of standard namelists for each scientific topic reproduces specific sets of diagnostics or performance metrics that have demonstrated their importance in ESM evaluation in the peer-reviewed literature. The Earth System Model Evaluation Tool (ESMValTool) is a community effort open to both users and developers encouraging open exchange of diagnostic source code and evaluation results from the CMIP ensemble. This will facilitate and improve ESM evaluation beyond the state-of-the-art and aims at supporting such activities within the Coupled Model Intercomparison Project (CMIP) and at individual modelling centres. Ultimately, we envisage running the ESMValTool alongside the Earth System Grid Federation (ESGF) as part of a more routine evaluation of CMIP model simulations while utilizing observations available in standard formats (obs4MIPs) or provided by the user. [ABSTRACT FROM AUTHOR]

In this paper, circuit level analysis of the high frequency and low noise performance of an RF CMOS device with L\mathrm{ eff}= 36 nm is performed using various layout schemes. By using the modeling methodology of interconnect metals and vias, it is found that the gate parasitic capacitance from the interconnects mainly affects the degradation of high frequency and noise performance. An optimized layout scheme is proposed to reduce the gate parasitic resistance and capacitance in this paper, and the proposed layout exhibits improved RF behaviors for fT , f\mathrm {\mathrm {MAX}} , and NFmin at 26 GHz up to ~13%, ~24%, and ~18% compared with the reference layout scheme, respectively. [ABSTRACT FROM PUBLISHER]

The performance of the joint assimilation in a land surface model of a Soil Wetness Index (SWI) product provided by an exponential filter together with Leaf Area Index (LAI) is investigated. The data assimilation is evaluated with different setups using the SURFEX modeling platform, for a period of seven years (2001-2007), at the SMOSREX grassland site in southwestern France. The results obtained with a Simplified Extended Kalman Filter demonstrate the effectiveness of a joint data assimilation scheme when both SWI and Leaf Area Index are merged into the ISBA-A-gs land surface model. The assimilation of a retrieved Soil Wetness Index product presents several challenges that are investigated in this study. A significant improvement of around 13% of the root-zone soil water content is obtained by assimilating dimensionless root-zone SWI data. For comparison, the assimilation of in situ surface soil moisture is considered as well. A lower impact on the root zone is noticed. Under specific conditions, the transfer of he information from the surface to the root zone was found not accurate. Also, our results indicate that the assimilation of in situ LAI data may correct a number of deficiencies in the model, such as low LAI values in the senescence phase by using a seasonal-dependent error definition for background and observations. In order to verify the specification of the errors for SWI and LAI products, a posteriori diagnostics are employed. This approach highlights the importance of the assimilation design on the quality of the analysis. The impact of data assimilation scheme on CO2 fluxes is also quantified by using measurements of net CO2 fluxes gathered at the SMOSREX site from 2005 to 2007. An improvement of about 5% in terms of rms error is obtained. [ABSTRACT FROM AUTHOR]

Battery management system has attracted mounting research attention recently, within which cell equalization plays a key role. Although many research and practices have been devoted to developing various structures of cell equalizers, there are still substantial opportunities for performance improvement yet to investigate. In particular, mathematical modeling and systematic analysis of equalizer systems are limited. In this paper, the performance analysis of the modularized global equalizer system for Lithium-ion battery cell equalization is conducted analytically. Specifically, a mathematical model is developed to emulate the equalization dynamics by considering both charging/discharging and energy loss. Analytical formulas are derived to evaluate the performance of the global equalizer. The introduced model is also compared with the state-of-the-art structures in terms of equalization speed and energy loss. Numerical studies show that the modularized global equalization outperforms others by its substantial reduction on energy loss with similar equalization performance and much less equalizers. In addition, a module segmentation guide is provided to facilitate the equalization system design. [ABSTRACT FROM AUTHOR]

Nearly half of the earth's photosynthetically fixed carbon derives from the oceans. To determine global and region specific rates, we rely on models that estimate marine net primary productivity (NPP) thus it is essential that these models are evaluated to determine their accuracy. Here we assessed the skill of 21 ocean color models by comparing their estimates of depth-integrated NPP to 1156 in situ 14C measurements encompassing ten marine regions including the Sargasso Sea, pelagic North Atlantic, coastal Northeast Atlantic, Black Sea, Mediterranean Sea, Arabian Sea, subtropical North Pacific, Ross Sea, West Antarctic Peninsula, and the Antarctic Polar Frontal Zone. Average model skill, as determined by root-mean square difference calculations, was lowest in the Black and Mediterranean Seas, highest in the pelagic North Atlantic and the Antarctic Polar Frontal Zone, and intermediate in the other six regions. The maximum fraction of model skill that may be attributable to uncertainties in both the input variables and in situ NPP measurements, was nearly 72%. Contrary to prior studies, ocean color models were not highly challenged in extreme conditions of surface chlorophyll-a and sea surface temperature, nor in high nitrate low-chlorophyll waters. On average, the simplest depth/wavelength integrated models performed no worse than the more complex depth/wavelength resolved models. Water column depth (distance to coastlines) was the primary influence on ocean color model performance such that average skill was significantly higher at depths greater than 250 m, suggesting that ocean color models are more challenged in Case-2 waters (coastal) than in Case-1 (pelagic) waters. Given that in situ chlorophyll-a data was used as input data, algorithm improvement is required to eliminate the poor performance of ocean color models in Case-2 waters that are close to coastlines. Finally, ocean color chlorophyll-a algorithms are challenged by optically complex Case-2 waters, thus using satellitederived chlorophyll-a to estimate NPP in coastal areas would likely further reduce the skill of ocean color models. [ABSTRACT FROM AUTHOR]

This paper presents an improved multi-level simulation framework for 2D material-based nanoelectronics, which expands from device simulation, physics-based compact modeling, and circuit benchmarking, using the germanane (GeH) metal-oxide-semiconductor field-effect transistors (MOSFETs) as an example. The device simulation employs the non-equilibrium Green's function method to obtain the characteristics of 2D GeH MOSFETs for both n-type MOSFETs and p-type MOSFETs. A compact model based on the MIT virtual source model is then revised to capture the unique behaviors of 2D-material-based MOSFETs, including voltage dependency of virtual source velocity and drain-induced barrier lowering, as well as the effect of quantum capacitance. HSPICE circuit simulations are performed to analyze and optimize CMOS digital benchmark circuits. The case study demonstrates that 2D material-based transistors favor a different range of supply voltage and threshold voltage than their silicon counterpart, to achieve the optimal energy-delay product. The impact of contact resistance is also analyzed using the proposed framework. This study offers a seamless multi-level simulation approach to bridge the gap between nanoelectronics and circuit behavior, thereby advancing the understanding of materials, devices, and circuits comprehensively. The framework tailored for GeH MOSFETs provides accurate device-circuit co-optimization which can be easily extended to devices based on other 2D materials. [ABSTRACT FROM AUTHOR]

This paper discusses a performance evaluation model of the visual management (VM) case-base. The research procedure of this paper consists of the following three phases: (1) formulation of the proposed model integrated by Quantification Theory Category III and the Analytic Hierarchy Process (AHP); (2) construction of relational data between VM cases selected from the constructed case-base and typical Key Performance Indicators (KPIs), i.e. quality, delivery, cost, etc.; and (3) preliminary experimentation to confirm the utility of the proposed model derived in the first phase based on the relational data derived in the previous phase. Using the experimental results, an evaluation of the constructed case-base performance and each VM case's contribution to each KPI is possible. [ABSTRACT FROM AUTHOR]

Serial lines and assembly systems are two of the most fundamental production system structures used in practical manufacturing environments. While serial lines have been studied extensively in production systems literature and practice, assembly systems have received much less attention. Among existing results on assembly systems, most are focused on steady state performance evaluation, system properties, and improvement. On the other hand, transient behavior of such systems remains largely unexplored. In the framework of assembly systems with Bernoulli machines and finite buffers, this paper develops a mathematical model for transient analysis and derives closed-form formulas to calculate the real-time production rate, consumption rates, work-in-process, and probabilities of machine starvation and blockage, during transients. Then, an improved computationally efficient algorithm for transient performance evaluation in Bernoulli serial lines is proposed. Based on the improved algorithm, an effective and efficient method for transient performance evaluation in Bernoulli assembly systems is derived. Finally, the method is extended to complex assembly system structures. [ABSTRACT FROM AUTHOR]

Queue systems are essential in the modelling of transport systems. Increasing requirements from the beneficiaries of logistic services have led to a broadening of offerings. Consequently, models need to consider transport entities with priorities being assigned in relation to the costs corresponding to different classes of customers and/or processes. Waiting lines and queue disciplines substantially affect queue system performance. This paper aims to identify a solution for decreasing the waiting time, the total time in the system, and, overall, the cost linked to queueing delays. The influence of queue discipline on the waiting time and the total time in the system is analysed for several cases: (i) service for priority classes at the same rate of service with and without interruptions, and (ii) service for several priority classes with different service rates. The presented analysis is appropriate for increasing the performance of services dedicated to freight for two priority classes. It demonstrates how priority service can increase system performance by reducing the time in the system for customers with high costs. In addition, in the considered settings, the total time in the system is reduced for all customers, which leads to resource savings for system infrastructures. [ABSTRACT FROM AUTHOR]

Availability is considered as a crucial metrics used to evaluate the performance of a fertilizer plant. The paper develops an availability model of the urea decomposition system of a fertilizer plant to quantify the values of availability indices and to identify the most critical equipment that mainly affects the system's performance. The Markovian approach was adopted to model the system behavior. A transition diagram was constructed for the developed model and differential equations of the developed model were formulated to obtain the state probability. The availability at steady state was analyzed and investigated. The developed model was verified and its validation was carried out. A real data of industrial system in fertilizer plant was applied to validate the developed model and the effect of failure and repair rates at different mission times was presented and discussed. The model output identifies the critical subsystems and the equipment which mainly influences the system's performance. Consequently, the developed model is considered as an excellent tool for the system's performance evaluations. The performance has been optimized using Genetic Algorithm (GA). The findings of the paper will be highly useful to the plant management for timely execution of proper maintenance decisions and thus to enhance the system performance. [ABSTRACT FROM AUTHOR]

This paper focus is the mathematical modeling of the file system performance in virtual environment when using type-1 hypervisors. The modeling provides a set of hypotheses related to the expected behavior. The presented model is validated based on the analysis of a collection of the results obtained for a specific case study. Our case study includes the file system performance comparison, in full hardware virtualization, when examining four dominant type-1 hypervisors: ESXi, KVM, Hyper-V, and Xen. We chose Filebench as a benchmark tool, which guarantees comprehensive and versatile testing of file system performance, whereas for all tested hypervisors we have provided an equivalent environment and testing conditions. For all the examined hypervisors, we have tested the cases with one, two, and three virtual machines that are running simultaneously, whereas CentOS 6.3 Linux is used as the guest operating system. We have further validated the mathematical model and defined hypotheses by the means of the case study benchmark results. [ABSTRACT FROM AUTHOR]

The multichannel generator is a kind of special generator, which is developed to enhance power reliability in safety critical applications. This paper compares the dynamic performance computation for a 12/8 dual-channel switched reluctance generator (DCSRG) under single- and dual-channel operation modes. First, the static phase self- and mutual inductances are numerically calculated through finite element analysis (FEA). Based on the magnetic characteristics, the mathematical and simulation models of DCSRG under different operation modes are presented. In the dual-channel model, the effect of mutual coupling between phases of each channel in the DCSRG is considered. By using these proposed dynamic models, the different performances for the DCSRG under single- and dual-channel operation modes, such as generating process under closed-loop control, steady-state performance at different conditions, sudden change in load operation, and the operating status when changing from motoring to generating, are predicted and compared. Finally, a 12/8 DCSRG system is built for experimentation. The simulation and experimental results are also compared in the DCSRG system under different operation modes to verify the proposed modeling and analysis. [ABSTRACT FROM AUTHOR]

This paper makes an attempt to assess the benefits of replacing a conventional generator excitation system (AVR+PSS) with a nonlinear voltage regulator using the concepts of synchronizing and damping torque components in a single machine infinite bus (SMIB) system. In recent years, there has been considerable interest in designing nonlinear excitation controllers, which are expected to give better dynamic performance over a wider range of system and operating conditions. The performance of these controllers is often justified by simulation studies on few test cases which may not adequately represent the diverse operating conditions of a typical power system. The performance of two such nonlinear controllers which are designed based on feedback linearization and include automatic voltage regulation with good dynamic performance have been analyzed using an SMIB model. Linearizing the nonlinear control laws along with the SMIB system equations, a Heffron Phillip's type of a model has been derived. Concepts of synchronizing and damping torque components have been used to show that such controllers can impair the small signal stability under certain operating conditions. This paper shows the possibility of negative damping contribution due to nonlinear voltage regulators and gives a new insight on understanding the physical impact of complex nonlinear control laws on power system dynamics. [ABSTRACT FROM PUBLISHER]

Several studies sustained the possibility that a photochemical reflectance index (PRI) directly obtained from satellite data can be used as a proxy for ecosystem light use efficiency (LUE) in diagnostic models of gross primary productivity. This modelling approach would avoid the complications that are involved in using meteorological data as constraints for a fixed maximum LUE. However, no unifying model predicting LUE across climate zones and time based on MODIS PRI has been published to date. In this study, we evaluate the efficiency with which MODIS-based PRI can be used to estimate ecosystem light use efficiency at study sites of different plant functional types and vegetation densities. Our objective is to examine if known limitations such as dependance on viewing and illumination geometry can be overcome and a single PRIbased model of LUE (i.e. based on the same reference band) can be applied under a wide range of conditions. Furthermore, we were interested in the effect of using different faPAR (fraction of absorbed photosynthetically active radiation) products on the in-situ LUE used as ground truth and thus on the whole evaluation exercise. We found that estimating LUE at site-level based on PRI reduces uncertainty compared to the approaches relying on a maximum LUE reduced by minimum temperature and vapour pressure deficit. Despite the advantages of using PRI to estimate LUE at sitelevel, we could not establish an universally applicable light use efficiency model based on MODIS PRI. Models that were optimised for a pool of data from several sites did not perform well. [ABSTRACT FROM AUTHOR]

Performance analysis is playing an indispensable role in design and evaluation for on-chip networks. In former studies, the end-to-end delay bound is calculated by the equivalent service curve method based on network calculus when resource sharing happens. However, in this paper, we propose a composable method to get the bound. This method uses the aggregated local arrival curve to get the local delay bound first, then calculates the end-to-end bound by summing up local bounds. This method solves the scalability problem and largely decreases the computation complexity compared with the former method. [ABSTRACT FROM PUBLISHER]

Recent technological developments have led to the production of inexpensive, non-invasive, miniature magneto-inertial sensors, ideal for obtaining sport performance measures during training or competition. This systematic review evaluates current evidence and the future potential of their use in sport performance evaluation. Articles published in English (April 2017) were searched in Web-of-Science, Scopus, Pubmed, and Sport-Discus databases. A keyword search of titles, abstracts and keywords which included studies using accelerometers, gyroscopes and/or magnetometers to analyse sport motor-tasks performed by athletes (excluding risk of injury, physical activity, and energy expenditure) resulted in 2040 papers. Papers and reference list screening led to the selection of 286 studies and 23 reviews. Information on sport, motor-tasks, participants, device characteristics, sensor position and fixing, experimental setting and performance indicators was extracted. The selected papers dealt with motor capacity assessment (51 papers), technique analysis (163), activity classification (19), and physical demands assessment (61). Focus was placed mainly on elite and sub-elite athletes (59%) performing their sport in-field during training (62%) and competition (7%). Measuring movement outdoors created opportunities in winter sports (8%), water sports (16%), team sports (25%), and other outdoor activities (27%). Indications on the reliability of sensor-based performance indicators are provided, together with critical considerations and future trends. [ABSTRACT FROM AUTHOR]

This paper is devoted to the performance analysis and continuous improvement of multiproduct manufacturing systems. First, a Bernoulli model of multiproduct serial line with unreliable machines and finite buffers is introduced. In such a model, each machine is capable of processing multiple product types, and each buffer is shared for all products. Closed formulas have been derived to evaluate the production rate of the line with one or two machines, and recursive procedures are used to analyze longer lines. Numerical studies indicate that such a method has a high precision in performance evaluation. The system-theoretic properties, such as asymptotic property, monotonicity, and reversibility, have been investigated. Second, in order to improve system performance, bottleneck (BN) analysis has been carried out to identify the machine and product whose improvement will lead to the largest improvement in the system production rate. Various types of BNs have been defined, and the BN indicators, based on the data collected on the factory floor, are proposed to identify the BNs without the complicated calculations of the production rate and its sensitivities. Numerical experiments have justified the practical usefulness of such indicators for BN identification in multiproduct manufacturing systems. Finally, a case study is introduced to illustrate the applicability of the model and the method. [ABSTRACT FROM AUTHOR]

In lean manufacturing, milk run (MR) systems represent route-based, cyclic material handling systems that are used widely to enable frequent and consistent deliveries of containerised parts on an as-needed basis from a central storage area (the ‘supermarket’) to multiple line-side deposit points on the factory floor. In the first part of this two-part paper, a basic, single-tugger MR system is described, and stability conditions as well as the probability of exceeding either the physical capacity of the tugger or the prescribed cycle time are derived. Given the stability conditions, and the distribution of the number of containers requested per MR, in the second part of the paper, the number of Kanban required in the MR system is examined, and analytical approximations are derived both for the number of Kanban required and for predicting workstation starvation. The latter is a key concern when designing a MR system that will support workstations in a manufacturing plant. The performance of the analytic approximation is evaluated by simulating various MR systems. Our results suggest that, in a stable MR system, the number of Kanban and the physical capacity of the tugger have a bigger impact on workstation starvation than the prescribed cycle time. [ABSTRACT FROM PUBLISHER]

In lean manufacturing, milk run (MR) systems represent route-based, cyclic material-handling systems that are used widely to enable frequent and consistent deliveries of containerised parts on an as-needed basis from a central storage area (the ‘supermarket’) to multiple line-side deposit points on the factory floor. MR systems generally result in short lead times, low variability, and low line-side inventory levels. In the first part of this two-part paper, a basic, single-tugger MR system is described. Stability conditions are derived with respect to the ‘physical capacity’ of the tugger, and the ‘time utilisation’ of the driver/material handler, both of which are key criteria since the number of containers that can be delivered during each MR is limited, and each MR targets a prescribed cycle time to ensure timely and consistent deliveries. We also derive the distribution of the number of containers requested per MR, which allows the model to estimate the probability of exceeding the physical capacity of the tugger or the prescribed cycle time, under the assumption that sufficient kanban are available for each part type delivered by the MR system. The results of the study facilitate the design and analysis of MR systems used in industry. [ABSTRACT FROM PUBLISHER]

Owing to inevitable errors of the material and fabrication process, the cross-axis sensitivity commonly exists in a large number of MEMS devices based on parallel plate structures. Such cross-axis interference results in the non-negligible rotation of the plate that deteriorates the performance of MEMS devices. Therefore, suppressing the cross-axis sensitivity is extremely critical in the device design. This paper proposes a novel theory to identify the interplay between the cross-axis interference and squeeze film air damping, and further develops a correlated theory of the damping induced suppression. The model of tilting plate with a tiny amplitude is set up by exploiting the Reynolds equation coupled with the equations of the mass deflection, and the analytical expressions of corresponding properties are derived to elucidate the suppression mechanism and its characterization. The analytical calculation and numerical simulation analysis demonstrate that the damping induced improvement effect exists objectively and is remarkable in the condition of a large mass and a small air film thickness. The cross-axis sensitivity rendered by the tilt angle quantitatively declines 80% in terms of the air damping. The theoretical underpinning can be utilized to elaborate the ubiquitous interplay between squeeze film air damping and cross-axis interference in non-vacuum MEMS devices, which is of paramount importance for achieving high performance and stability. More importantly, it is not an exclusive method that can be combined with other methods to minimize the cross-axis interference fully. [ABSTRACT FROM AUTHOR]

Caching at mobile devices and leveraging cooperative device-to-device (D2D) communications are two promising approaches to support massive content delivery over wireless networks while mitigating the effects of interference. To show the impact of cooperative communication on the performance of cache-enabled D2D networks, the notion of device clustering must be factored in to convey a realistic description of the network performance. In this regard, this paper develops a novel mathematical model, based on stochastic geometry and an optimization framework for cache-assisted coordinated multi-point (CoMP) transmissions with clustered devices. Devices are spatially distributed into disjoint clusters and are assumed to have a surplus memory to cache files from a known library, following a random probabilistic caching scheme. Desired contents that are not self-cached can be obtained via D2D CoMP transmissions from neighboring devices or, as a last resort, from the network. For this model, we analytically characterize the offloading gain and rate coverage probability as functions of the system parameters. An optimal caching strategy is then defined as the content placement scheme that maximizes the offloading gain. For a tractable optimization framework, we pursue two separate approaches to obtain a lower bound and a provably accurate approximation of the offloading gain, which allows us to obtain optimized caching strategies. Remarkably, if we replace the obtained expression for offloading gain with its lower bound, we can find a suboptimal caching strategy that is not only described via analytical formulas but can also show an improvement over the state-of-the-art caching schemes. Results reveal that cooperative transmission becomes more appealing in denser D2D caching networks and adverse interference conditions, which is the case of the imminent Internet of Things (IoT) and ns era. [ABSTRACT FROM AUTHOR]

This paper proposes a new cyclic model of combined regenerative Brayton and inverse Brayton cycles. The new combined regenerative Brayton and inverse Brayton cycles recover heat energy after the working fluid leaves the turbine of the inverse Brayton cycle while the original combined regenerative Brayton and inverse Brayton cycles recover heat energy before the working fluid enters the turbine of the inverse Brayton cycle. Performance analysis and optimisation of the two classes combined cycles are carried out. Furthermore, the effect of the regenerator on the performance of the two combined cycles is analysed. It is found that the new combined cycle can obtain higher thermal efficiency and larger specific work than those of the original combined cycle at low compressor pressure ratio of the top cycle, and the regenerator can improve the performance of both the combined cycles. By theoretical analysis of this paper, it reveals that the new combined cycle will be well applied in the prospect, and the original combined cycle will be suited to low power output equipments. This paper aims at enriching the gas turbine theory and providing a possible way to save energy. [ABSTRACT FROM PUBLISHER]

Energy storage is a novel technology with perceived performance and lifecycle risks. In addition, there are many different business/regulatory paradigms for investors in storage resources based on existing business models for electric power assets today. At the heart of designing storage applications for best cost-benefit results and for evaluating storage economics of particular applications is the way different business models realize direct monetized benefits and indirect avoided costs from energy storage. This paper unpacks the complexities of deploying and operating energy storage and identifies any potential barriers to participation in storage. It lays out some of the existing and hypothetical business models for the investment in and operation of electric storage, and explores the complexities and possibilities of these business models when storage is bucketed” as a generation, transmission, distribution, or customer asset. It also identifies possible policy recommendations and areas for further analysis, including some alternative models that consider storage as a unique asset class that offers services offered by other assets today. [ABSTRACT FROM PUBLISHER]

STATCOM can provide fast and efficient reactive power support to maintain power system voltage stability. In the literature, various STATCOM control methods have been discussed including many applications of proportional-integral (PI) controllers. However, these previous works obtain the PI gains via a trial-and-error approach or extensive studies with a tradeoff of performance and applicability. Hence, control parameters for the optimal performance at a given operating point may not be effective at a different operating point. This paper proposes a new control model based on adaptive PI control, which can self-adjust the control gains during a disturbance such that the performance always matches a desired response, regardless of the change of operating condition. Since the adjustment is autonomous, this gives the plug-and-play capability for STATCOM operation. In the simulation test, the adaptive PI control shows consistent excellence under various operating conditions, such as different initial control gains, different load levels, change of transmission network, consecutive disturbances, and a severe disturbance. In contrast, the conventional STATCOM control with tuned, fixed PI gains usually perform fine in the original system, but may not perform as efficient as the proposed control method when there is a change of system conditions. [ABSTRACT FROM AUTHOR]

Water environment system is a complex system, and an agent-based model presents an effective approach that has been implemented in water resource management research. Urban water resource optimal allocation is a challenging and critical issue in water environment systems, which belongs to the resource optimal allocation problem. In this paper, a novel approach based on multiagent Q-learning is proposed to deal with this problem. In the proposed approach, water users of different regions in the city are abstracted into the agent-based model. To realize the cooperation among these stakeholder agents, a maximum mapping value function-based Q-learning algorithm is proposed in this study, which allows the agents to self-learn. In the proposed algorithm, an adaptive reward value function is used to improve the performance of the multiagent Q-learning algorithm, where the influence of multiple factors on the optimal allocation can be fully considered. The proposed approach can deal with various situations in urban water resource allocation. The experimental results show that the proposed approach is capable of allocating water resource efficiently and the objectives of all the stakeholder agents can be successfully achieved. [ABSTRACT FROM PUBLISHER]

Many control problems encountered in industrial applications such as deburring, cutting, and polishing are required to simultaneously perform force control and contour following. If the mathematical model of the contour to be followed is known, then the control problem is straightforward, and many existing approaches can be used to tackle this problem. In contrast, if the mathematical model is not available, the control problem will become much more challenging. Among all possible solutions to circumvent the aforementioned difficulties, using a vision system to obtain the mathematical model of the contour to be followed is one of the best options. To this end, this paper proposes a vision-based approach, in which a vision system is employed to provide the exterior contour information of the object for machining. Subsequently, coordinate transformation between the image plane and the robot frame is performed. Based on the exterior contour information after coordinate transformation, a Pythagorean hodograph quintic spline interpolator based on S curve acceleration/deceleration is developed to generate motion commands. The fact that the arc length of a Pythagorean hodograph curve can be easily computed makes it particularly useful when performing motion planning for high-precision motion control systems. Moreover, in order to improve contour following accuracy, an integrated motion control structure consisting of an adaptive disturbance compensator, a sliding mode controller, and a friction compensator is also developed. Finally, several contour following experiments are conducted by a planar two-link robot manipulator to verify the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

The modeling of cutting forces plays an important role in the progress of research and technology in most machining processes. In particular, peripheral milling is a cutting process difficult to model due to the large number of variables involved. Among these variables, tool runout affects process performance by modifying milling force patterns, shortening the tool life and machine components, and by degrading workpiece quality. In this paper, a methodology to evaluate tool runout in peripheral milling is presented. The use of a boring toolholder is proposed to make controllable changes in the tool offset that modifies tool runout. In addition, the proposed methodology has been validated by means of a piezoactuator-based system that allows tool runout compensation through controlling workpiece displacement. Experimental and simulated results presented in this paper reveal the practical applications of this methodology for researchers and engineers involved in the practice of milling and its modeling. [ABSTRACT FROM AUTHOR]

SUMMARY Multiwatermarking is the technique to embed multiple messages into the same media content. It can be used to identify media content's owners or trace the illegal redistributors in media distribution. Especially in cloud environment with multiple content providers or users, multiwatermarking may have potential applications. However, some performances of multiple watermark embedding, for example, the distortion and security, are not considered. In this paper, the application scenarios of multiwatermarking in cloud environment are figured out, which investigate the secure media distribution models suitable for cloud-based platform. Additionally, the multiwatermarking based on additive rule is studied and then analyzed theoretically from two aspects, one of which is the multi-embedding of same watermark sequence and the other is the multiembedding of different watermark sequences. The analysis emphasizes on four aspects; that is, robustness, capacity, distortion, and security. And each of which considers two cases, that is, the authorized embedding and unauthorized embedding. Additionally, the correlation detection based on multiwatermarking is proposed, and for each case, the corresponding suggestions to improve system performance are proposed. Some comparative experiments are performed, and results are given to show the validity of these theoretical analysis.Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Data envelopment analysis (DEA) is a non-parametric analytical methodology widely used in efficiency measurement of decision making units (DMUs). Conventionally, after identifying the efficient frontier, each DMU is compared to this frontier and classified as efficient or inefficient. This paper first introduces the strongly efficient frontier ( SEF) and strongly inefficient frontier ( SIF), and then proposes several models to calculate various distances between DMUs and both frontiers. Specifically, the distances considered in this paper include: (1) both the distance to SEF and the distance to SIF, where the former reveals a unit's potential opportunity to become a best performer while the latter reveals its potential risk to become a worst performer, and (2) both the closest distance and the farthest distance to frontiers, which may provide different valuable benchmarking information for units. Subsequently, based on these distances, eight efficiency indices are suggested to rank DMUs. Due to different distances adopted in these indices, the efficiency of units can be evaluated from diverse perspectives with different indices employed. In addition, all units can be fully ranked by these indices. The efficiency of 24 major Asian container ports is analyzed with our study, where the potential opportunities and potential crises of these ports are revealed and some new insights about their efficiency are provided. [ABSTRACT FROM AUTHOR]

The paper deals with the quantitative assessment of photovoltaic inverter system performance, focusing on the problem of its reliability and availability predictions. In particular, the problem of data uncertainty, due to a scarce knowledge of the components' reliabilities, is taken into account. This problem is crucial for new technology systems and is faced within a Bayesian probabilistic framework: components' reliability and availability parameters - hazard rate and repair rate - are considered as random variables, characterized in the paper by suitable Lognormal distributions, as motivated by well known and established physical and mathematical models relating, for instance, the hazard rate to the various factors (environmental, operational, manufacturing factors etc.) affecting the components' reliabilities. Such methodology allows expressing the system availability uncertainty as a function of component uncertain data. For sake of brevity, due to complexity of the problem deriving from many sources of randomness, the paper develops only a methodology for establishing the prior (or "a priori") distributions characterizing the basic (input) random variables (hazard rate and repair rate). On the basis of such distributions, the prior distribution of the components' availability (output random variables of the problem) is deduced analytically. It is shown that a new distribution, denoted as "Beta-Lognormal", is capable of efficiently representing the uncertainty of component availability, and its analytical properties are deduced. Numerical applications are presented to show the feasibility of the approach. [ABSTRACT FROM AUTHOR]

This paper proposes a control method suitable for limited armature voltage and current in a permanent-magnet synchronous motor drive system based on direct torque control (DTC). First, this paper proposes torque-limiting and flux-weakening controls that are suitable for a DTC-based motor drive system. The proposed method utilizes a mathematical model in a rotating reference frame synchronized to the stator flux linkage. Second, this paper proposes an antiwindup scheme for the torque controller of the DTC system. Windup of the controller degrades the performances of torque-limiting (current-limiting) control and of torque control. Applying the antiwindup results improves the performance of the proposed torque-limiting method in the transient state. This paper presents a DTC-based drive system combined with a speed controller. The proposed system can achieve stable control, and its effectiveness is confirmed experimentally. [ABSTRACT FROM PUBLISHER]

Purpose – This study aims to investigate the development of predictive tools in performance measurement and management (PMM), and modeling of a forward-looking method to help managers to quantitatively target performance measures based on achieving desired improvement, minimum cost and strategic priorities. Design/methodology/approach – A case-based methodology is used to test the conceptual approach in a production system. Mathematical models are used to model modules of the proposed approach. The proposed approach is applied to an actual conventional power plant unit to show its applicability and superiority over conventional methods. Findings – The developed system enables managers to develop systematic ways to manage future performance; for example, planning, performance forecasting and target setting. The predictive ability of the developed system is comparable with the judgment of the manager in the case company. Originality/value – This paper proposes the use of mathematical models in the development of performance measures targeted on performance prediction and desired improvement. The paper also offers practical help to organizations to embed a forward-looking capability into their operations. [ABSTRACT FROM AUTHOR]

The paper presents a fast mathematical model that can be used to quickly asses the propulsive characteristics of liquid propelled rocket engines. The main propulsive parameters are computed using combustion surfaces obtained after a nonlinear data fitting analysis. This approach is much more time efficient than using standard codes which rely on frequent calls of the Fuel Combustion Charts and interpolating their data. The tool developed based on the proposed mathematical model can be used separately or it can be integrated in a multidisciplinary optimisation algorithm for a preliminary microlauncher design. [ABSTRACT FROM AUTHOR]

In this paper, the application of optimal state estimation and optimal state feedback algorithms for real-time active magnetic bearing control is treated. A linear quadratic Gaussian controller, consisting of an extended Kalman filter and an optimal state feedback regulator, is implemented. It is shown that this controller yields improved rotor positioning accuracy, better system dynamics, higher bearing stiffness, and reduced control energy effort compared to the conventionally used proportional–integral–differential control approaches. In addition, a method for compensating unbalance-caused forces and vibrations of the magnetically levitated rotor is presented which is based on the estimation of unknown disturbance forces. All results achieved in this paper are verified by means of measurements. [ABSTRACT FROM PUBLISHER]

Studies on scheduling with learning considerations have recently become important. Most studies focus on single-machine settings. However, numerous complex industrial problems can be modeled as flowshop scheduling problems. This paper thus focuses on minimizing the makespan in an m-machine permutation flowshop with learning considerations. This paper proposes a dominance theorem and a lower bound to accelerate the branch-and-bound algorithm for seeking the optimal solution. This paper also adapts four well-known existing heuristic algorithms to yield the near-optimal solutions. Eventually, the performances of all the algorithms proposed in this paper are reported for small and large job-sized problems. The computational experiments indicate that the branch-and-bound algorithm can solve problems of up to 18 jobs within a reasonable amount of time, and the heuristic algorithms are quite accurate with a mean error percentage of less than 0.1%. [ABSTRACT FROM AUTHOR]

This paper describes an approach in improving the performance of the position sensorless control of an interior permanent-magnet synchronous motor using parameter identification. The model-based sensorless method requires accurate motor parameters. At low speed, the resistance variation degrades the accuracy of position estimation. The identified parameter is used in the sensorless drive system to improve the accuracy of position estimation. In this paper, the resistance is identified online, but the offline identified value of the q-axis inductance is used. The experimental results reveal the effectiveness of applying parameter identification to the sensorless drive system. [ABSTRACT FROM PUBLISHER]

This paper describes the field oriented control of a salient pole wound field synchronous machine in stator flux coordinates. The procedure for derivation of flux linkage equations along any general rotating axes including stator flux axes is given. The stator flux equations are used to identify the cross-coupling occurring between the axes due to saliency in the machine. The coupling terms are canceled as feedforward terms in the generation of references for current controllers to achieve good decoupling during transients. The design of current controller for stator-flux-oriented control is presented. This paper proposes the method of extending rotor flux closed loop observer for sensorless control of wound field synchronous machine. This paper also proposes a new sensorless control by using stator flux closed loop observer and estimation of torque angle using stator current components in stator flux coordinates. Detailed experimental results from a sensorless 15.8 hp salient pole wound field synchronous machine drive are presented to demonstrate the performance of the proposed control strategy from a low speed of 0.8 Hz to 50 Hz. [ABSTRACT FROM AUTHOR]

In this paper, performance evaluation of a two-stage supply chain which consists of a supplier and a retailer under uncertainty environment is examined. In the literature; many studies have been investigated on supply chain performance analysis in uncertainty environment and demand parameter is an essential data on these analyses. When there is sufficient data about demand, it is easy to construct probability distribution of demand. However, in the absence of enough historical data, it is impossible to construct the probability distribution. The demand parameter is intuitively determined and shown by a fuzzy distribution in such situations. This paper intends to find closed form solutions in order to maximize the performance of a two-stage supply chain with coordination under fuzzy environment. The coordination of the supply chain is maintained by contracts. The contracts analysed in this study are revenue sharing contract and buy back contract. Numerical examples are presented to show the validity of the proposed models and to investigate the effect of contract parameters on the total performance of the supply chain. [ABSTRACT FROM AUTHOR]

As the Linear-Exponential-Normal (LEN) Principal-Agent model has gained in popularity, it has also increasingly been applied to problems inherently inconsistent with the assumptions underpinning this fragile framework. Concerns regarding LEN analysis in such cases are generally countered by appealing to the results' intuitive nature. When consistent with economic intuition, it is argued, the constraints the LEN framework imposes on such problems are likely non-consequential. This paper demonstrates in two simple cases that even seemingly intuitive results of non-optimal LEN analysis can be fundamentally different from the results that obtain from analysis of the unrestricted programs. Accordingly the paper makes a case for limiting LEN-type analysis to settings that are actually compatible with this framework. [ABSTRACT FROM AUTHOR]

This paper presents a general modeling framework for Intermodal Freight Transport Terminals (IFTTs). The model allows simulating and evaluating the performance of such key elements of the intermodal transportation chain. Hence, it may be used by the decision maker to identify the IFTT bottlenecks, as well as to test different solutions to improve the IFTT dynamics. The proposed modeling framework is modular and based on timed Petri Nets (PNs), where places represent resources and capacities or conditions, transitions model inputs, flows, and activities into the terminal and tokens are intermodal transport units or the means on which they are transported. The model is able to represent the different types of existing IFTTs. Its effectiveness is tested first on an example from the literature and then on a real case study, the railroad inland terminal of a leading Italian intermodal logistics company, showing its ease of application. In the real case study, using the proposed formalism we test the as-is IFTT performance and evaluate alternative possible to-be improvements in order to identify and eliminate emerging criticalities in the terminal dynamics. [ABSTRACT FROM AUTHOR]

Since their origins in the 1980's, grey systems thinking and grey numbers have found a wide and growing range of applications. One of these is in providing decision support for multi-criteria choice. All the key elements of multi-criteria modelling are potentially infused with a lack of certainty: weights on criteria, performance levels of alternatives, choice of criteria, inter-dependence between criteria, and so on. For a long time, multi-criteria researchers have recognised that, especially from a practical point of view, their decision support models are imprecise, that they are often operating with only partial information about the problem they are seeking to solve. And, indeed, in some circumstances, especially in supporting choice between discrete alternatives, models do not need to be precise or based on full provision of information in order to be useful. This has been referred to as decision making with partial information and a wide variety of formalisations of multi-criteria decision making with partial information have been advanced. In this paper, we explore how using grey systems can provide a perspective on multi-criteria choice with partial information that potentially enhances existing thinking and directly relates to the ambiguity and uncertainty of choice - effectively the real world of decision modelling for many application contexts. [ABSTRACT FROM AUTHOR]

Due to an inherently poor voltage regulation, the Self Excited Induction Generators (SEIGs) are incapable of supplying RL loads. One way of improving their voltage regulation is by series capacitance compensation. However, as the steady state load-ability limit of a compensated SEIG is increased, it is more likely to experience resonance due to change in either inductive loading or frequency or both. In this paper, a detailed analysis of resonating behavior of a single phase, two winding SEIG is carried out. The effects of resonance on the performance of SEIG are evaluated through performance characteristics obtained at the loads of different power factors. A steady state model of series compensated single phase, double winding SEIG is developed through MATLAB M file. The optimum excitation and compensation capacitances are selected by performing experimental tests on a 1 phase, double winding, 220/230 V SEIG. [ABSTRACT FROM AUTHOR]

Purpose – Technical education plays an important role in the development of a country in this age of knowledge economy. Indian technical education system is facing many opportunities and challenges, one of which is how to assess the performance of technical institutions based on multiple criteria. The purpose of this paper is to describe and illustrate an application of a structured approach to determine relative efficiency and ranking of a set of private engineering colleges under multi-criteria environment. Design/methodology/approach – To cater to the increasing need of technical manpower, a very large number of private engineering colleges have been established in the state of West Bengal of eastern India within a very short period. Uniform and acceptable quality of the graduates from many of these private engineering colleges is a concern today and therefore the need for performance evaluation and ranking of these colleges is paramount. For the proposed framework a comparatively new multiple criteria decision-making tool, multiple objective optimization on the basis of simple ratio analysis (MOOSRA) is applied for performance evaluation of eight private engineering colleges taking into account some selected criteria. The subjective weights of the criteria are determined using fuzzy analytic hierarchy process (AHP). Findings – For the analysis, the required data have been provided by the management of the colleges for the academic year of 2011-2012. Based on request of the management identities of these institutes are not disclosed. The institutes are considered as anonymous institute and coded as A, B, C, D, E, F, G and H, respectively. The result of the study reveals that E is the best and the ranking the authors get is in the order of E > F > A > H > D > C > G > B. The result shows that composite performance scores of institutions A, E and F are above the mean performance score value. Therefore these three institutions can be considered as the benchmark or peer group for the remaining five institutions which lie below the mean line of the performance score value. Originality/value – This paper provides a comprehensive yet detailed methodology for performance evaluation of academic institutions. The novelty in the approach is that fuzzy AHP and MOOSRA are being used as a benchmarking technique in a simple methodology which is generic in nature. It is one of the few studies that evaluate the performance of technical institutions in India. [ABSTRACT FROM AUTHOR]

This paper investigates whether using hourly and/or zonal prices can improve the accuracy of short- and medium-term forecasts of average daily electricity prices. We consider a 6 years period (2008-2013) of hourly day-ahead prices from 19 zones of the Pennsylvania-New Jersey-Maryland (PJM) interconnection and the PJM Dominion Hub in Virginia, U.S. The predictive performance of four multivariate models calibrated to hourly and/or zonal day-ahead prices is evaluated and compared with that of a univariate model, which uses only average daily data for the Dominion Hub. The multivariate competitors include a restricted vector autoregressive model and three factor models with the common and idiosyncratic components estimated using principal components in a semiparametric setup. The results indicate that there are statistically significant forecast improvements from incorporating the additional information, essentially for all considered forecast horizons ranging from 1 day to 2 months, but only when the correlation structure of prices across locations and/or hours is modeled using factor models. [ABSTRACT FROM AUTHOR]