•An importance measure is proposed to guide maintenance for repairable systems.•A method based on multi-valued decision diagram is developed to evaluate the measure.•The computational procedure and ...properties of the proposed measure are illustrated.•A case study is utilized to illustrate the applicability of the measure.
To enhance system performance, corrective maintenance for failed components and preventive maintenance (PM) for operating components can be performed simultaneously on repairable systems. Due to limited budget, it is typically not practical to perform PM for all the operating system components. Moreover, different selections of components for PM can lead to significant differences in system performance improvements. This paper proposes an extended joint integrated importance measure (JIIM) to effectively guide the selection of PM components, aiming to maximize gains of the system performance. A multi-valued decision diagram (MDD) based method is then developed to evaluate the proposed JIIM for general repairable systems. The computational procedure of MDD and some properties of JIIM are illustrated with a numerical example of a system containing three components. A realistic application to the performance analysis of an aircraft warning system verifies the proposed method.
•A new method for design concept evaluation of smart PSS is proposed.•A new topic of smart PSS sustainability in design stage is tackled.•The new method reduces designers’ burden of pairwise ...comparisons in decision-making.•The method considers objective criteria weights though intercriteria correlation.•The method can flexibly manipulate imprecise and vague decision-making information.
Intelligent products and services are integrated into Smart product-service systems (PSS) through information and communication technology (ICT). Various feasible Smart PSS designs are usually created in the design stage, and the design concept selection directly affects the delivery performance of the Smart PSS. However, existing methods often require more comparisons, omit criteria objective weights, and consider less about the impact of information subjectivity and impreciseness on the Smart PSS design concept selection. To solve the problems, a new integrated method is proposed, which integrates both subjective and objective weights to improve the accuracy of evaluation. Firstly, for criteria weighting, the proposed approach integrates the merits of the Best Worst Method (BWM) in reducing the burden of pair-wise comparisons when determining the subjective weights, and the strengths of the Criteria Importance Though Inter-criteria Correlation (CRITIC) method in considering the correlation and contrast between all criteria when determining the objective weights. Then, Rough Set Theory is used to flexibly deal with the decision-making vagueness without much prior information. Finally, a case study of a smart washing machine is adopted to validate the effectiveness of the proposed method.
Recent reform efforts have pushed toward a better understanding of the distinction between exploratory and confirmatory research, and appropriate use of each. As some utilize more exploratory tools, ...it may be tempting to employ multiple linear regression models. In this paper, we advocate for the use of random forest (RF) models. RF is able to obtain better predictive performance than traditional regression, while also inherently protecting against overfitting as well as detecting nonlinear effects and interactions among predictors. Given the advantages of RF compared to other statistical procedures, it is a tool commonly used within a plethora of industries, including stock trading, banking, pharmaceuticals, and patient healthcare planning. However, we find RF is used within the field of psychology comparatively less frequently. In the current paper, we advocate for RF as an important statistical tool within the context of behavioral and psychological research. In hopes of increasing the use of RF in the field of psychology, we provide information pertaining to the limitations one might confront in using RF and how to overcome such limitations. Moreover, we discuss various methods for how to optimally utilize RF with psychological data, such as nonparametric modeling, interaction and nonlinearity detection, variable selection, prediction and classification modeling, and assessing parameters of Monte Carlo simulations. Throughout, we illustrate the use of RF with visualization strategies, aimed to make RF models more comprehensible and intuitive.
Buckwheat is a biochemical enriched pseudo-cereal crop. The field experiment was conducted to identify superior of Buckwheat in the Namsai region of the eastern Himalayas. The distinct phenotype of ...Kuttu, Jheem, Jarain, Demchi, Wakha Yendem and Gruching local varieties were cultivated in randomized complete block design (RCBD) with four replications in the instructional farm in the October 2021. The manual weeding and thinning intercultural operations were conducted in the field. The growth parameters yield and correlation coefficient and bio-metabolism were studied in the plant. The primary data was obtained in vegetative growth and reproductive growth in the plant. The values of plant heights; 68.00 (T6-Kuttu), 65.50 (T4-Jheem), 64.23 (T3-Gruching) followed by 62.50 (T5-Demchi), 55.50 (T2-Jarain) and 57.50 (T1-Wakha Yendem) were observed at harvest (cm). The mean values of grain yields (plot/m2); 5.65 (T6-Kuttu), 4.20 (T5-Jarain), 4.13 (T3-Gruching) followed by 2.78 (T1-Wakha Yendem), 3.68 (T2-Demchi) and 3.53 (T4- Jheem) were obtained. The plant height at harvest positively contributes in growth and development induction of seed per cluster, 1000 gm seed weight, grain yield and straw yield. The 1000 gm seed weight was positively involves in phenotypic growth of plant height at harvest, nodes per plant, petiole length, seeds per cluster, 1000 gm seed weight, grain yield and straw yield. The plant morphogenesis is regulated with flavonoid biosynthetic pathway and biochemical productions are facilitated through rutin biosynthetic pathway. The crop has potential to exhibit companion production and biochemical enriched property. The crop replenishes food production, value-addition products, supply chain, socio-economic aspects and sustainable development goals in the country.
•Primary Introduction and Distribution of Local Buckwheat Cultivars.•Biometric analysis and Correlation Coefficients in Local Buckwheat Cultivars.•Economic importance of Morphological Portion of Buckwheat.•Gene Regulations in Phenological growth and Biochemical synthesis in Buckwheat.
Domestic camels (Camelus bactrianus, the Bactrian camel; and Camelus dromedarius, the dromedary) are pseudo-ruminant herbivores kept as livestock in rural, inhospitable regions (cold deserts and dry ...steppes of Asia, arid to semi-arid regions of Africa, western and central Asia). Their close contact with humans makes them a potential reservoir for zoonotic parasite infections, as has been suggested for human balantidiasis. However, there is confusion about the ciliate species that infects camels: Infundibulorium cameli was originally described in dromedaries, but this name has almost never been used and most authors identified their findings as Balantioides coli and, to a lesser extent, Buxtonella sulcata, a cattle ciliate. To clarify the taxonomic status of the parasite and the corresponding zoonotic significance for camels, we performed morphological characterization of cysts and genetic analysis (SSU-rDNA and ITS markers) of B. coli-like isolates from Bactrian camels from Bulgaria and from dromedaries from Spain and the United Arab Emirates. Our results indicate that the camel ciliate is not B. coli, nor is it B. sulcata, but is a different species that should be placed in the same genus as the latter. Thus, camels are not a reservoir for human balantidiasis. Although the correct genus name would be Infundibulorium according to the principle of priority, this would lead to confusion since this name has almost fallen into disuse since its initial description, but Buxtonella is almost universally used by researchers and veterinarians for the cattle ciliate. We therefore propose to apply the reversal of precedence and use Buxtonella as the valid genus name. Consequently, we propose Buxtonella cameli n.comb. as the name for the camel ciliate.
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•The morphology of camel pycnotrichid ciliate cysts is described.•SSU rDNA and ITS sequences of camel pycnotrichid ciliates were obtained.•Camels (Camelus bactrianus, C. dromedarius) are not reservoirs of human balantidiasis.•Infundibulorium cameli and Buxtonella sulcata are different but congeneric species.•A reversal of precedence is proposed to keep Buxtonella as the valid genus name.
Adaptive importance sampling is a class of techniques for finding good proposal distributions for importance sampling. Often the proposal distributions are standard probability distributions whose ...parameters are adapted based on the mismatch between the current proposal and a target distribution. In this work, we present an implicit adaptive importance sampling method that applies to complicated distributions which are not available in closed form. The method iteratively matches the moments of a set of Monte Carlo draws to weighted moments based on importance weights. We apply the method to Bayesian leave-one-out cross-validation and show that it performs better than many existing parametric adaptive importance sampling methods while being computationally inexpensive.
Abstract
Background
Random forest based variable importance measures have become popular tools for assessing the contributions of the predictor variables in a fitted random forest. In this article we ...reconsider a frequently used variable importance measure, the Conditional Permutation Importance (CPI). We argue and illustrate that the CPI corresponds to a more partial quantification of variable importance and suggest several improvements in its methodology and implementation that enhance its practical value. In addition, we introduce the threshold value in the CPI algorithm as a parameter that can make the CPI more partial or more marginal.
Results
By means of extensive simulations, where the original version of the CPI is used as the reference, we examine the impact of the proposed methodological improvements. The simulation results show how the improved CPI methodology increases the interpretability and stability of the computations. In addition, the newly proposed implementation decreases the computation times drastically and is more widely applicable. The improved CPI algorithm is made freely available as an add-on package to the open-source software R.
Conclusion
The proposed methodology and implementation of the CPI is computationally faster and leads to more stable results. It has a beneficial impact on practical research by making random forest analyses more interpretable.
Abstract
Particle filters may suffer from degeneracy of the particle weights. For the simplest “bootstrap” filter, it is known that avoiding degeneracy in large systems requires that the ensemble ...size must increase exponentially with the variance of the observation log-likelihood. The present article shows first that a similar result applies to particle filters using sequential importance sampling and the optimal proposal distribution and, second, that the optimal proposal yields minimal degeneracy when compared to any other proposal distribution that depends only on the previous state and the most recent observations. Thus, the optimal proposal provides performance bounds for filters using sequential importance sampling and any such proposal. An example with independent and identically distributed degrees of freedom illustrates both the need for exponentially large ensemble size with the optimal proposal as the system dimension increases and the potentially dramatic advantages of the optimal proposal relative to simpler proposals. Those advantages depend crucially on the magnitude of the system noise.
This study is a methodological evaluation of studies on importance and performance measurement, and importance–performance analysis (IPA) which has gained widespread acceptance in the hospitality and ...tourism research. A synthesis of IPA literature on conceptual and measurement issues is presented with a view to identifying and mitigating potential validity concerns.
•A model based on random forests for short term load forecast is proposed.•An expert feature selection is added to refine inputs.•Special attention is paid to customers behavior, load profile and ...special holidays.•The model is flexible and able to handle complex load signal.•A technical comparison is performed to assess the forecast accuracy.
The electrical load forecast is getting more and more important in recent years due to the electricity market deregulation and integration of renewable resources. To overcome the incoming challenges and ensure accurate power prediction for different time horizons, sophisticated intelligent methods are elaborated. Utilization of intelligent forecast algorithms is among main characteristics of smart grids, and is an efficient tool to face uncertainty. Several crucial tasks of power operators such as load dispatch rely on the short term forecast, thus it should be as accurate as possible. To this end, this paper proposes a short term load predictor, able to forecast the next 24h of load. Using random forest, characterized by immunity to parameter variations and internal cross validation, the model is constructed following an online learning process. The inputs are refined by expert feature selection using a set of if–then rules, in order to include the own user specifications about the country weather or market, and to generalize the forecast ability. The proposed approach is tested through a real historical set from the Tunisian Power Company, and the simulation shows accurate and satisfactory results for one day in advance, with an average error exceeding rarely 2.3%. The model is validated for regular working days and weekends, and special attention is paid to moving holidays, following non Gregorian calendar.
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