The distinct problems of physical inconsistency and of multivariate bias potentially involved in the statistical adjustment of climate simulations

Bias adjustment of numerical climate model simulations involves several technical and epistemological arguments wherein the notion of physical inconsistency is often referred to, either for rejecting the legitimacy of bias adjustment in general or for justifying the necessity of sophisticated multivariate techniques. However, this notion is often mishandled, in part because the literature generally proceeds without defining it. In this context, the central objective of this study is to clarify and illustrate the distinction between physical inconsistency and multivariate bias, by investigating the effect of bias adjustment on two different kinds of inter-variable relationships, namely a physical constraint expected to hold at every step of a time series and statistical properties that emerge with potential bias over a climatic time scale. The study involves the application of 18 alternative bias adjustment techniques on 10 climate simulations and over 12 sites across North America. Adjusted variables are temperature, pressure, relative humidity and specific humidity, linked by a thermodynamic constraint. The analysis suggests on the one hand that a clear instance of potential physical inconsistency can be avoided with either a univariate or a multivariate technique, if and only if the bias adjustment strategy explicitly considers the physical constraint to be preserved. On the other hand, it also suggests that sophisticated multivariate techniques alone aren’t complete adjustment strategies in presence of a physical constraint, as they cannot replace its explicit consideration. As a supplementary objective, this study relates common optional adjustment procedures with likely effects on diverse basic statistical properties, as an effort to guide climate information users in the determination of adequate bias adjustment strategies for their research purposes.

Managing consistency and consensus measures and adjustment strategies in group decision making with probabilistic linguistic preference relations

The use of probabilistic linguistic preference relations (PLPRs) in pairwise comparisons enhances the flexibility of quantitative decision making. To promote the application of probabilistic linguistic term sets (PLTSs) and PLPRs, this paper introduces the consistency and consensus measures and adjustment strategies to guarantee the rationality of preference information utilized in the group decision making process. First of all, a novel entropy-based similarity measure is developed with PLTSs. Hereafter an improved consistency measure is defined on the basis of the proposed similarity measure, and a convergent algorithm is constructed to deal with the consistency improving process. Furthermore, a similarity-based consensus measure is developed in a given PLPR, and the consensus reaching process is presented to deal with the unacceptable consensus degree. The proposed consistency improving and consensus reaching processes follow a principle of minimum information loss, called a local adjustment strategy. In particular, the presented methods not only overcome the deficiencies in existing studies but also enhance the interpretation and reduce the complexity of the group decision making process. Finally, the proposed consistency measure and improving process, as well as consensus measure and reaching process are verified through a numerical example for the medical plan selection issue. The result and in-depth comparison analysis validate the feasibility and effectiveness of the proposed methods.

Rice Disease Recognition Using Effective Deep Neural Networks

Rice is the most important grain in Thailand for both consuming and exporting. One of the critical problems in rice cultivation is rice diseases, which affects directly to the yield. Early disease recognition is handled by a human, which is difficult to achieve high accuracy and the performance depends on the farmer’s experience. To overcome this problem, we did three folds of contributions. First, an infield rice diseases image dataset, named K5RD, was created. Second, a number of additional techniques to enhance the classification scores including data augmentations and learning rate adjustment strategies were carefully surveyed. Third, a set of selective deep learning models including ResNets and DenseNets were applied to classify such rice diseases. The experimental results reveal that the proposed framework can achieve high performance, which its F1 score is higher than 98% on average, and has the potential to be implemented as a practical system to provide to Thai farmers in the future.

Lived experiences of the adjustment of older employees to re-employment in Singapore: A Bourdieusian perspective

The Singapore government promulgated the Retirement and Re-employment Act in 2012 to promote extending working life. This article offers insight into the utility of Bourdieu’s conceptual framework of habitus, field and capital in exploring how older employees in Singapore adjust to re-employment. Semi-structured in-depth interviews were conducted with 10 re-employed older persons consisting of four women and six men. The thematic analysis of the data indicated that a series of adjustment strategies underpinned by the realism-, positivity-, productivity- and proactivity-oriented habitus synergized to empower research participants to navigate through the field of re-employment. The article proposes that in the Singapore context policy makers and employers need to take a habitus-sensitive approach to re-employed older persons, developing a habitus-friendly field of re-employment.

Adjustment Strategies of Older Adults Transitioning Into an Assisted Living Facility: Implications for RT Practice

Transitions into an assisted living facility (ALF) may have major impacts on the well-being of older adults, both positively and negatively. The purpose of this study was to explore strategies that older adults are implementing to maintain or improve their well-being during their transition into an ALF. A grounded theory, descriptive approach employed 14 individual, in-person interviews at an ALF in the rural, southeastern U.S. Eight central findings emerged as adjustment strategies used by older adults, catorgizied as active and passive strategies. The five active strategies were identified as importance of health promoting activities (subthemes: promoting physical health and promoting mental health), connections to the outside world (subthemes: community integration outings and community visitors), placing possessions, finding a new routine, and engaging in spiritual practices. Three passive strategies were identified: peer support, staff support, and prior familiarity with the ALF. Implications for recreational therapists working with older adults in ALFs are detailed and future research recommendations are provided.

Dynamics of bilateral control system with state feedback for price adjustment strategy

The price fluctuation of commodities affects their demand, and it strongly influences the development of industry and the stability of the international economy. A price-output model with two price-dependent impulses is presented in this paper to describe their mutual restrictions and the price adjustment strategies. The equilibria and dynamic properties of the impulsive-free price-output model are qualitatively analyzed, and the results show the hazard of free price fluctuation. For the price-output model with two price-dependent impulses, conditions for the existence of the order-2 periodic solution are obtained, and the orbital asymptotic stability is proved. Those results reveal the positive role of price adjustment strategies. Finally, some numerical simulations are carried out to verify the theoretical results.