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Evaluating war-induced damage to agricultural land in the Gaza Strip since October 2023 using PlanetScope and SkySat imagery

The ongoing 2023 Israel-Hamas War has severe and far-reaching consequences for the people, economy, food security, and environment. The immediate impacts of damage and destruction to cities and farms are apparent in widespread reporting and first-hand accounts from within the Gaza Strip. However, there is a lack of comprehensive assessment of the war's impacts on key Gazan agricultural land that a

Space-time Correlation Field--A new method for analyzing one dimensional unsaturated flow

This work presents a statistical approach for estimating and analyzing the downward transport pattern and distribution of soil water by the use of pattern analysis of space-time correlation structures. This approach, called the Space-time Correlation Field, is mainly based on the analyses of correlation functions simultaneously in the space and time domain. The overall purpose of this work is to d

Wastewater treatment and reuse through natural treatment systems

Two successful samples of land treatment systems are introduced in the paper. A rapid infiltration system of the area 11.3 hectares with treatment capacity of 10,000 m3/day was constructed in Pingdu city of Shandong province. The removal of COD reached 87.5% while 89.4 for suspended solids and 64.4 % for NH3-N. In fact, the treated water already achieved the criteria of the secondary treatment eve

The Effect of Measurement Errors on the Performance of Variable Sample Size and Sampling Interval X¯ Control Chart

The effect of measurement errors on adaptive and non-adaptive control charts has been occasionally considered by researchers throughout the years. However, that effect on the variable sample size and sampling interval (VSSI) X¯ control charts has not so far been investigated. In this paper, we evaluate the effect of measurement errors on the VSSI X¯ control charts. After a model development, the e

Monitoring the multivariate coefficient of variation in presence of autocorrelation with variable parameters control charts

The coefficient of variation is a very important process parameter in many processes. A few control charts have been considered so far for monitoring its multivariate counterpart, i.e., the multivariate coefficient of variation (MCV). In addition, autocorrelation is very likely to occur in processes with high sampling frequency. Hence, designing suitable control charts and investigating the effect

An adaptive max-type multivariate control chart by considering measurement errors and autocorrelation

The combined effect of two real-world-occurring phenomena: ‘measurement errors’ and ‘autocorrelation between observations’ has rarely been investigated. In this paper, it will be investigated for the first time on ‘adaptive’ and/or ’simultaneous monitoring’ charts and also for the first time by using the multivariate linearly covariate measurement errors and VARMA (vector mixed autoregressive and

Performance of the variable parameters X control chart in presence of measurement errors

In this article, we investigate the effect of measurement errors on the performance of the VP (Variable Parameters) X control chart. After introducing the VP scheme for the X chart with measurement errors, we evaluate the chart performance by using the average time to signal criterion, and we investigate the effect of measurement errors on the chart’s performance through extensive numerical studie

A multivariate adaptive control chart for simultaneously monitoring of the process parameters

There have been some advances in multivariate control charts in recent years. This paper presents a new simultaneous scheme for monitoring both the mean and variability of a multivariate normal process in a single chart, which is developed by improving and modifying another recently proposed scheme. We not only propose a new control scheme but also make it adaptive by varying all control chart par

A variable parameters multivariate control chart for simultaneous monitoring of the process mean and variability with measurement errors

Evaluating the effect of measurement errors on either adaptive or simultaneous control charts has been a topic of interest for the researchers in the recent years. Nevertheless, the effect of measurement errors on both adaptive and simultaneous monitoring control charts has not been considered yet. In this paper, through extensive numerical studies, we evaluate the effect of measurement errors on

New Machine-Learning Control Charts for Simultaneous Monitoring of Multivariate Normal Process Parameters with Detection and Identification

Simultaneous monitoring of the process parameters in a multivariate normal process has caught researchers’ attention during the last two decades. However, only statistical control charts have been developed so far for this purpose. On the other hand, machine-learning (ML) techniques have rarely been developed to be used in control charts. In this paper, three ML control charts are proposed using t

An adaptive variable-parameters scheme for the simultaneous monitoring of the mean and variability of an autocorrelated multivariate normal process

Due to advances in technology, sampling procedures and short lag times between successive sampling, autocorrelation among the measured data has become common in most applications. Neglecting autocorrelation leads to a poor false alarm performance. In the current paper, the effect of the autocorrelation on the performance of a variable-parameters multivariate single control chart is investigated in

Variable parameters memory-type control charts for simultaneous monitoring of the mean and variability of multivariate multiple linear regression profiles

Variable parameters (VP) schemes are the most effective adaptive schemes in increasing control charts' sensitivity to detect small to moderate shift sizes. In this paper, we develop four VP adaptive memory-type control charts to monitor multivariate multiple linear regression profiles. All the proposed control charts are single-chart (single-statistic) control charts, two use a Max operator and tw

Evaluating the effect of measurement errors on the performance of the variable sampling intervals Hotelling's T2 control charts

The effect of measurement errors on the performance of multivariate adaptive control charts has not been considered yet. In this article, we investigate the effect of measurement errors on the performance of the variable sampling intervals (VSI) Hotelling's T2 control chart in the case of known parameters. A linearly covariate error model is used as the measurement error function. In order to meas

Developing a partial backlogging deteriorating inventory model with selling price dependant demand rate and cycle length dependant selling price

In this paper, we develop an inventory model with price dependant demand rate, under time value of money and inflation, finite time horizon, exponential backlogging rate and exponential deterioration rate with the objective of maximizing the present worth of the total system profit. Using a dynamic programming based solution algorithm, we are able to find the optimal sequence of the cycles and als

A new adaptive control chart for the simultaneous monitoring of the mean and variability of multivariate normal processes

This paper considers adaptive schemes for the simultaneous monitoring of the mean and variability of a multivariate normal quality characteristic. At first, we extend an already existing bivariate non-adaptive simultaneous control chart to a multivariate one. Then, we develop several adaptive schemes, which will cover both previously bivariate and newly multivariate charts. After having designed a

A new development of an adaptive X − R control chart under a fuzzy environment

It is proved that adaptive control charts have better performance than classical control charts due to adaptability of some or all of their parameters to the previous process information. Fuzzy classical control charts have been occasionally considered by many researchers in the last two decades; however, fuzzy adaptive control charts have not been investigated. In this paper, we introduce a new a