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In this study, the Weibull distribution with various numerical estimation methods is utilized for the assessment of wind energy potential in Mersing and Port Dickson, Malaysia, by considering different monsoon seasons, i.e., northeast and southwest monsoons. This assessment is conducted based on hourly wind speed data obtained from the Malaysian Meteorological Department and the Department of Environment, Malaysia. A total of 28 numerical estimation methods are presented, and their performances are first investigated through a Monte Carlo simulation. The results of the Monte Carlo simulation indicate that no particular method outperforms all other methods. In different settings, i.e., different sample sizes and shape parameters, certain methods are more efficient than others in estimating the Weibull parameters. Based on the simulation results, 24 out of 28 numerical estimation methods are utilized for wind energy potential assessment in Mersing and Port Dickson. The performance efficiency of all the considered methods is evaluated using an integrated approach comprising four goodness of fit criteria, the modified Kolmogorov − Smirnov, modified Anderson − Darling, modified Cramér–von Mises, and power density error. Using this integrated approach allow us to obtain a single-value goodness of fit measure known as the global score to determine the best method. Based on the best fitted Weibull model, the wind characteristics in both sites are investigated. The wind characteristics during northeast monsoon is found to be favorable for wind energy generation in Mersing with the northeast (0 − 40°) as the prominent wind direction. However, small-scale wind energy is the best option for wind energy development in Mersing. On the other hand, the Port Dickson site demonstrates poor wind characteristics, indicating that this area is not favorable for wind energy development. [ABSTRACT FROM AUTHOR]

• Mg II index was implemented in IRI-2016 to assess foF2 but results do not provide a clear improvement of the model performance. • IRI-Plas with Mg II option to assess foF2 provides a slightly better performance than IRI-2016. To assess upper atmosphere parameters, current models use different variables to account for solar activity levels. Studies that evaluate the most recent solar cycles have shown that when dealing with the ionospheric F2 layer, and in particular with foF2, the Mg II index is a better choice than other solar activity proxies to account for solar EUV variation. The International Reference Ionosphere, version 2016 (IRI-2016), a model widely used by the scientific community, uses the Ionosonde Global (IG) index to assess foF2. A most recent and expanded version, IRI-Plas, allows selecting a solar activity proxy among 7 options including IG and Mg II. In the present work, the performance of IRI considering Mg II to assess foF2 is analyzed, comparing three modeling cases: IRI-2016 with its default solar activity index (IG), IRI-2016 with Mg II instead of IG, and IRI-Plas choosing Mg II as the solar proxy option. This model comparison was evaluated in terms of their agreement with measured foF2 data from four stations located in Japan (Northern Hemisphere), and four in Australia (Southern Hemisphere). Monthly medians for the 24 h, along two periods of three years were considered: 2000–2002 and 2008–2010, which correspond to epochs of maximum and minimum solar activity levels, respectively. Based on goodness-of-fit statistics, our results show that in the case of IRI-2016, the Mg II implementation does not reveal a significant improvement for foF2 assessment, and the IRI-Plas performance with the Mg II option is only slightly better than the other two options. Dispersion diagrams between measured and modeled foF2 also evince a similar performance between the three models. All models show the same over- and underestimation patterns, except in the nighttime case during the minimum activity level period for both Australian and Japanese stations where IRI-Plas outperforms the other two model options. The comparable performances of the three options might be attributed to a stronger variation in the evaluated periods which could be related to seasonal changes rather than to solar EUV proxies. Future studies considering time series over several years, covering at least a complete solar activity cycle, are required to determine stronger model performance differences. [ABSTRACT FROM AUTHOR]

Despite an increase in prevalence of complex chronic conditions and dementia, long‐term care services are being continuously pushed out of institutional settings and into the home and community. The majority of people living with dementia in Canada and the United States (U.S.) live at home with support provided by family, friends or other unpaid caregivers. Ten dementia care policy programs and service delivery models across five different North American jurisdictions in Canada and the U.S. are compared deductively using a comparative policy framework originally developed by Richard Rose. One aim of this research was to understand how different jurisdictions have worked to reduce the fragmentation of dementia care. Another aim is to assess, relying on the theory of smart policy layering, the extent to which these policy efforts 'patch' health system structures or add to system redundancies. We find that these programs were introduced in a manner that did not fully consider how to patch current programs and services and thus risk creating further system redundancies. The implementation of these policy programs may have led to policy layers, and potentially to tension among different policies and unintended consequences. One approach to reducing these negative impacts is to implement evaluative efforts that assess 'goodness of fit'. The degree to which these programs have embedded these efforts into an existing policy infrastructure successfully is low, with the possible exception of one program in NY. [ABSTRACT FROM AUTHOR]

Reference evapotranspiration (ET0) is amajor component of the hydrological cycle. Its use is essential both for the hydrological rainfall-runoff assessment models and determination of water requirements in agricultural and forest ecosystems. This study investigates the performance of 24 differentmethods, which produce ET0 or potential evapotranspiration estimates above a grass-covered ground in a Mediterranean forest environment in Greece and compares the derived resultswith those of the presumed most accurate and scientifically acceptable Penman-Monteith method (ETP-M). Their performance was evaluated on a daily basis for a period of 17 years, using 17 different statistical parameters of goodness of fit. The results showed that some empirical methods could serve as suitable alternatives. More specifically, Copais (ETCOP), Hargreaves original (ETHAR), and Valiantzas2 (ETVA2) methods, exhibited very good values of the model efficiency index, EF (0.934, 0.932, and 0.917, respectively) and the index of agreement, d (0.984, 0.982, and 0.977, respectively). Additionally, the differences of the estimatedmean daily value against the respective ETP-M value (rt index) for all methods had a range of -27.8% (Penman - ETPEN) to +59.5% (Romanenko - ETROM), while Copais (ETCOP), Hargreaves-Samani modified1 (ETHS1), and STU (ETSTU) yielded the best values (-0.06%, +0.06%, and 0.22%, respectively). [ABSTRACT FROM AUTHOR]

This study introduces a new estimation approach that could be used in calculating the Weibull parameters for the estimation of wind power. This new approach, called the method of multi-objective moments (MUOM), proposes minimization of the squared deviances between the first three population moments and corresponding sample moments. In the proposed MUOM, the third moment, which is used in the formula of wind power, is a key function since it provides a significant contribution to the correct prediction of wind energy. In order to demonstrate the performance of the proposed MUOM, it is compared with the well-known estimation methods such as the maximum likelihood, modified maximum likelihood, moment and energy pattern factor. In comparative analysis, the performance of the considered methods is evaluated on the actual wind speed data measured different time periods according to various goodness of fit criteria. The obtained results indicate that the MUOM definitely provides more accurate estimates than other well-known methods in estimating wind power based on the Weibull distribution. Thus, the MUOM can be used as an improved method in estimating wind power. [ABSTRACT FROM AUTHOR]