this experiment was conducted to study the effect of plastic mulch on the growth and some physiological characteristics of two strawberry cultivars (paros and queen elisa) under drought stress. a factorial experiment was performed based on randomized complete block design with four treatments, including mulch, without mulch, normal irrigation (control) and deficit irrigation (-10 bar) with thre...

A model of consumer behavior has been formulated by using an additive utility function and the hedonic pricing approach, in a virtual market. Since, there is a time lag between ordering and purchasing products (goods and services) online and receiving them, it means the consumer makes decision under uncertainty. The level of satisfaction with products with distinctive characteristics is describ...

Let us say that we want to analyze the total sum of a certain kind of result in a series of repeated independent random experiments each of which has a well-defined expected value and finite variance. In other words, a certain kind of result (e.g. whether the experiment is a “success”) has some probability to be produced in each experiment. We would like to repeat the experiment many times inde...

This paper discusses a set of necessary conditions for continuous time Markov decision processes with criterion of expected discounted total rewards, where the state space is countable, the reward rate function is extended real-valued and the discount rate is any real number. Under necessary conditions that the model is well defined, the state space is partitioned into three subsets, on which t...

Let us consider a case where all of the elements in some continuous slices are missing in tensor data. In this case, the nuclear-norm and total variation regularization methods usually fail to recover the missing elements. The key problem is capturing some delay/shift-invariant structure. In this study, we consider a low-rank model in an embedded space of a tensor. For this purpose, we extend a...

Most distance metric learning (DML) approaches focus on learning a Mahalanobis metric for measuring distances between examples. However, for particular feature representations, e.g., histogram features like BOW and SPM, Mahalanobis metric could not model the correlations between these features well. In this work, we define a nonMahalanobis distance for histogram features, via Expected Hitting T...