Discrete-time spare ordering policy with randomized lead times and discounting

The paper considers a generalized discrete‐time order‐replacement model for a single unit system, which is subject to random failure when in operation. Two types of discrete randomized lead times are considered for a spare unit; one is for regular (preventive) order and another is for expedited (emergency) order. The model is formulated based on the discounted cost criterion. The underlying two‐dimensional optimization problem is reduced to a simple one‐dimensional one and then the optimal ordering policy for the spare unit is characterized under two extreme conditions: (i) unlimited inventory time and (ii) zero inventory time for the spare unit. A numerical example is used to determine the optimal spare‐ordering policy numerically and to examine the sensitivity of the model parameters.     

Mid‐infrared spectroscopy as a tool for real‐time monitoring of ethanol absorption in glycols

Fast, simple, accurate, and inexpensive methods for obtaining analyte concentration data are desirable in the industrial sector. In the present study, the use of Fourier transform mid‐infrared (FT‐MIR) spectroscopy, combined with partial least squares (PLS) regression, was investigated as a tool for real‐time monitoring of processes of ethanol absorption in glycols. Calibration was performed using simple synthetic samples containing ethanol, water, and monoethylene glycol (MEG) or diethylene glycol (DEG). The PLS models presented excellent performance, with correlation coefficients (R²) close to unity and root‐mean‐square errors of cross‐validation (RMSECV) and prediction (RMSEP) lower than 2% of the calibration data ranges for both analytes (ethanol and water) in both absorbents (MEG and DEG). The monitoring technique developed has potential to be applied in absorption processes and could also be used in other large‐scale unit operations, providing information in real time and enhancing process control.     

Distribution-free checkpoint placement algorithms based on min-max principle

In this paper, we consider two kinds of sequential checkpoint placement problems with infinite/finite time horizon. For these problems, we apply approximation methods based on the variational principle and develop computation algorithms to derive the optimal checkpoint sequence approximately. Next, we focus on the situation where the knowledge on system failure is incomplete, i.e., the system failure time distribution is unknown. We develop the so-called min-max checkpoint placement methods to determine the optimal checkpoint sequence under an uncertain circumstance in terms of the system failure time distribution. In numerical examples, we investigate quantitatively the proposed distribution-free checkpoint placement methods, and refer to their potential applicability in practice.     

Optimal periodic maintenance strategy under an intermittently used environment

In this paper, the optimal periodic replacement-like strategy with minimal repairs is considered under an intermittently used environment. Suppose that transactions or jobs with exponential service times arrive at a system according to a homogeneous Poisson process and the system is alternatively in either a busy or an idle period subject to demand for use. We derive approximately the optimal preventive maintenance schedule which minimizes the relevant expected cost criterion for the system which behaves intermittently on an M/M/1 queueing process, and compare it with the usual maintenance schedule for the continuously used system.     

Optimal planned maintenance with salvage cost for a two-unit standby redundant system

This paper considers the optimal spare ordering policies for a cold standby redundant system with two dissimilar units. Especially, the planned maintenance schedule with salvage cost is discussed. The failure time distributions for respective units are assumed to be arbitrary. By applying the expected cost per unit time in the steady-state and the stationary availability as criteria of optimality, the optimal ordering policy minimizing or maximizing each criterion is obtained under some economical and/or physical assumptions. Finally, numerical examples are presented, and the effect of the failure time distributions for the optimal ordering policy is examined in detail.     

Some Remarks on Optimum Inspection Policies

We discuss optimum inspection policies by introducing the inspection density. We derive the optimum inspection policy by using this inspection density. The models discussed are: 1) the basic model, 2) the basic model with checking time, and 3) the basic model with imperfect inspection. For each model, we obtain the approximate optimum inspection policy minimizing the total s-expected cost by applying the calculus of variations.     

Optimum Ordering Policies with Lead Time for an Operating Unit in Preventive Maintenance

An ordering policy allows a spare, delivered after a constant lead time, to be put into inventory. Under certain conditions there exists a finite and unique ordering policy maximizing the cost effectiveness, which balances the system effectiveness and the cost and is defined as [s-availability]/[s-expected cost rate].     

A note on optimum checkpointing policies

In this paper, we treat checkpointing policies. We derive the total expected loss time and obtain the optimum checkpointing policy which minimizes that expected loss time. We further present the numerical examples using the exponential and the Weibull distributions. First, we discuss the model in which the intervals between checkpointing completion times may vary, and secondly the model with constant intervals.     

The acute effects of plyometric and sled towing stimuli with and without caffeine ingestion on vertical jump performance in professional soccer players

Background

Post-activation potentiation (PAP) is the phenomenon by which muscular performance is enhanced in response to a conditioning stimulus. PAP has typically been evidenced via improved counter movement jump (CMJ) performance. This study examined the effects of PAP, with and without prior caffeine ingestion, on CMJ performance.

Methods

Twelve male professional soccer players (23?±?5 years) performed two trials of plyometric exercises and sled towing 60 min after placebo or caffeine ingestion (5 mg.kg^??1) in a randomized, counterbalanced and double-blinded design. CMJ performance was assessed at baseline and 1, 3 and 5 min after the conditioning stimulus (T1, T3 and T5, respectively).

Results

Two way ANOVA main effects indicated a significant difference in jump height after the PAP protocol (F[3, 11]?=?14.99, P?<?0.001, partial η2?=?0.577). Analysis also indicated a significant difference in CMJ performance across conditions, with caffeine eliciting a greater response (F[1, 11]?=?10.12, P?=?0.009, partial η2?=?0.479). CMJ height was increased at T1, T3 and T5 in caffeine condition (5.07%, 5.75% and 5.40%, respectively; P?<?0.01) compared to baseline. In the placebo condition, jump performance was increased at T3 (4.94%; P?<?0.01) only. Jump height was higher in caffeine condition on T1, T3 and T5 (P?<?0.05) but not on baseline (P?>?0.05) compared to placebo.

Conclusions

The results of this study suggest that acute plyometric and sled towing stimuli enhances jump performance and that this potentiation is augmented by caffeine ingestion in male soccer players.

     

Monitoring deforestation and forest degradation using multi-temporal fraction images derived from Landsat sensor data in the Brazilian Amazon

Deforestation is the replacement of forest by other land use while degradation is a reduction of long-term canopy cover and/or forest stock. Forest degradation in the Brazilian Amazon is mainly due to selective logging of intact/un-managed forests and to uncontrolled fires. The deforestation contribution to carbon emission is already known but determining the contribution of forest degradation remains a challenge. Discrimination of logging from fires, both of which produce different levels of forest damage, is important for the UNFCCC (United Nations Framework Convention on Climate Change) REDD+ (Reducing Emissions from Deforestation and Forest Degradation) program. This work presents a semi-automated procedure for monitoring deforestation and forest degradation in the Brazilian Amazon using fraction images derived from Linear Spectral Mixing Model (LSMM). Part of a Landsat Thematic Mapper (TM) scene (path/row 226/068) covering part of Mato Grosso State in the Brazilian Amazon, was selected to develop the proposed method. First, the approach consisted of mapping deforested areas and mapping forest degraded by fires using image segmentation. Next, degraded areas due to selective logging activities were mapped using a pixel-based classifier. The results showed that the vegetation, soil, and shade fraction images allowed deforested areas to be mapped and monitored and to separate degraded forest areas caused by selective logging and by fires. The comparison of Landsat Operational Land Imager (OLI) and RapidEye results for the year 2013 showed an overall accuracy of 94%. We concluded that spatial resolution plays an important role for mapping selective logging features due to their characteristics. Therefore, when compared to Landsat data, the current availability of higher spatial and temporal resolution data, such as provided by Sentinel-2, is expected to improve the assessment of deforestation and forest degradation, especially caused by selective logging. This will facilitate the implementation of actions for forest protection.