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Blockchain is an emerging technology that is increasingly being applied in both industrial and academic contexts. Cryptocurrency is a major application of blockchain in the financial sector, but the technology is expected to disrupt other industries. In fact, it has influenced many businesses and reshaped private and public sector activities. Therefore, there is growing interest in blockchain-based solutions, and applications have evolved in finance, insurance, logistics, government, education, and healthcare. Applications built on blockchains benefit from fair access, transparency, and immutability; these properties have attracted business owners and practitioners to explore blockchain opportunities beyond cryptocurrency, motivating them to investigate how they can benefit from the technology and also to evaluate its compatibility with their strategic orientation. Suitability evaluation (or applicability evaluation) has always been a crucial step for the successful adaptation of any innovative technology, including blockchain. Hence, this paper investigates how the current literature has addressed blockchain suitability evaluation for business cases beyond cryptocurrency. A scoping review is presented that examines the evaluation models and frameworks that have been developed to assist decision-makers regarding blockchain adoption. The results indicate that blockchain evaluation methodologies have utilized varied approaches and serve diverse objectives, which are applicable for different technology adoption stages. Through this scoping review, blockchain evaluation initiatives are classified into five categories, and a critical analysis is offered of the evaluation models under each category. As such, this scoping review overviews existing methodologies for blockchain evaluation approaches with a focus on context, identified assessments factors, assessment process, and evaluation dimensions.

Multisource meteorological precipitation products are an important way to make up for a lack of observation sites or a lack of precipitation data in areas with a complex topography. They have important value for local industrial, agricultural, and ecological water use calculations, as well as for water resource evaluation and management. The Yunnan-Kweichow Plateau is located in southwest China and has a relatively backward economy and few meteorological stations. At the same time, the terrain is dominated by mountain valleys, precipitation is greatly affected by the terrain, and meteorological data are lacking, making the calculation of local water resources difficult. In this study, the applicability of the 3-hourly merged high-quality/IR estimates (3B42) of the Tropical Rainfall Measuring Mission (TRMM), China Meteorological Forcing Dataset (CMFD), and China Meteorological Assimilation Driving Datasets (CMADS) in the Yunnan-Kweichow Plateau was analyzed using multiple evaluation indicators of different temporal scales and precipitation intensity levels as well as the spatial distribution of the indicators based on measured daily precipitation data from 59 national meteorological basic stations in the study area in 2008–2018. The results showed that (1) the three products had performed well and could be applied to the calculation of local water resources with CMFD performing the best; (2) the performance of precipitation products was slightly worse on the daily scale, and the overall performance of the yearly, quarterly, and monthly scales was better; (3) good results were achieved in most regions, but there were also some regions with prominent overestimation and underestimation; (4) the three precipitation products had the highest probabilities of detection and the lowest false alarm rates for no rain and light rain, and the probability of detection gradually decreased with an increase in the precipitation intensity; and (5) the mean absolute error of precipitation products in rainy months is large, so the accuracy of products in the calculation of heavy rain and flood will be limited.

Separating productive green water from non-productive green water could determine the potential for improving green water use through water-to-vapor conversion and the optimization of green water resource management. This study selected three typical planted forests of Robinia pseudoacacia, Platycladus orientalis, and Pinus tabulaeformis in the Nanxiaohegou sub-basin, a typical small sub-basin located in the gully region of the Loess Plateau. A combination of field monitoring, hydrological models, and statistical tests was used to obtain the crop coefficient and to differentiate productive green water from non-productive green water, based on the hydrological, climatic, and ecological processes in the basin. The results demonstrated that the complementary relationship areal evapotranspiration (CRAE) model was the most effective complementary relationship-based model for the simulation. Based on the calibrated parameters, it could be used for the simulation of green water flux of different vegetation types in the studied region. In the Nanxiaohegou sub-basin, the amounts of productive green water, non-productive green water, and total green water flux of R. pseudoacacia were the highest among all three types of vegetation, followed by those of P. orientalis and P. tabulaeformis forests during the growing seasons between 2015 and 2017.

Standard applicability is the ability of a standard to be suitable for the prescriptive purpose under specified conditions. There is no mature applicability-evaluation index system of standards worldwide at present. We aim to construct the index system for evaluating the applicability of forensic science standard. The index system of applicability evaluation is proposed using a statistical analysis on the applicability of forensic science standards in China. We summarize the major problems and reasons in developing and revising the national and industry standards in China. Based on these, we put forward measures to improve standards' applicability, provide policy support for rectifying the standards, and lay the theoretical foundation for the construction, adjustment, and optimization of the forensic science standard system.

Global Satellite Mapping of Precipitation (GSMaP), Climate Hazards Group InfraRed Preconception with Station data (CHIRPS), Tropical Rain Measurement Mission Multisatellite Precipitation Analysis (TRMM 3B42 V7) and Rainfall Estimation from Soil Moisture Observations (SM2RAIN) are satellite precipitation products with high applicability, but their applicability in hydrological research in arid mountainous areas is not clear. Based on precipitation and runoff data, this study evaluated the applicability of each product to hydrological research in a typical mountainous basin (the Qaraqash River basin) in an arid region by using two methods: a statistical index and a hydrological model (Soil and Water Assessment Tool, SWAT). Simulation results were evaluated by Nash efficiency coefficient (NS), relative error (PBIAS) and determination coefficient (R2). The results show that: (1) The spatial distributions of precipitation estimated by these four products in the Qaraqash River basin are significantly different, and the multi-year average annual precipitation of GSMaP is 97.11 mm, which is the closest to the weather station interpolation results. (2) On the annual and monthly scales, GSMaP has the highest correlation (R ≥ 0.82) with the observed precipitation and the smallest relative error (BIAS < 6%). On the seasonal scale, the inversion accuracy of GSMaP in spring, summer and autumn is significantly higher than other products. In winter, all four sets of products perform poorly in estimating the actual precipitation. (3) Monthly runoff simulations based on SM2RAIN and GSMaP show good fitting (R2 > 0.6). In daily runoff simulation, GSMaP has the greatest ability to reproduce runoff changes. The study provides a reference for the optimization of precipitation image data and hydrological simulation in data-scarce areas.

Reactive distillation (RD) is a great process intensification concept applicable to equilibrium limited reaction systems, but how can anyone decide quickly if RD is indeed worth applying? To answer this question, this study proposes a mapping method for checking the applicability of reactive distillation (RD). The initial development is for one of the most relevant subset of quaternary reversible reactions (A + B ⇄ C + D, with boiling points Tb,C

It is not yet clear whether there is any difference in using remote sensing data of different spatial resolutions and filtering methods to improve the above-ground biomass (AGB) estimation accuracy of alpine meadow grassland. In this study, field measurements of AGB and spectral data at Sangke Town, Gansu Province, China, in three years (2013–2015) are combined to construct AGB estimation models of alpine meadow grassland based on these different remotely-sensed NDVI data: MODIS, HJ-1B CCD of China and Landsat 8 OLI (denoted as NDVIMOD, NDVICCD and NDVIOLI, respectively). This study aims to investigate the estimation errors of AGB from the three satellite sensors, to examine the influence of different filtering methods on MODIS NDVI for the estimation accuracy of AGB and to evaluate the feasibility of large-scale models applied to a small area. The results showed that: (1) filtering the MODIS NDVI using the Savitzky–Golay (SG), logistic and Gaussian approaches can reduce the AGB estimation error; in particular, the SG method performs the best, with the smallest errors at both the sample plot scale (250 m × 250 m) and the entire study area (33.9% and 34.9%, respectively); (2) the optimum estimation model of grassland AGB in the study area is the exponential model based on NDVIOLI, with estimation errors of 29.1% and 30.7% at the sample plot and the study area scales, respectively; and (3) the estimation errors of grassland AGB models previously constructed at different spatial scales (the Tibetan Plateau, Gannan Prefecture and Xiahe County) are higher than those directly constructed based on the small area of this study by 11.9%–36.4% and 5.3%–29.6% at the sample plot and study area scales, respectively. This study presents an improved monitoring algorithm of alpine natural grassland AGB estimation and provides a clear direction for future improvement of the grassland AGB estimation and grassland productivity from remote sensing technology.

With the reform of the power system, the retail electricity market in China has gradually been liberalized. The mechanism of freely selling electricity have been set up. To grab market share and increase profits, electricity retail companies have introduced a series of retail electricity price packages. To evaluate the applicability of these retail electricity price packages, an adaptive evaluation index system that takes into account the interests of both the power company and the users is first established. Furthermore, an integrated evaluation model that combines data envelopment analysis (DEA) and the cloud model is proposed. In this model, DEA is used to process quantitative indicators and the cloud model is employed to quantify qualitative problems. A case study of Tianjin is conducted to verify the effectiveness of the proposed evaluation system and model. The empirical study shows that qualitative indicators can also affect the applicability of the retail electricity price packages, and the applicability of the retail electricity price package was different in different seasons. Finally, several reliable suggestions on how to design retail electricity price packages are given based on the research. This study provides useful support for customers to choose the price package to increase the competitiveness of power selling companies and ultimately promote the reform of power selling.

Ova disertacija istražuje i definira metodologiju vrednovanja primjenjivosti normiranih modela predočavanja podataka u ugrađenim sustavima. Vrednovanje primjenjivosti zasnovano je kombinaciji ISO/IEC 9126 standarda za vrednovanje kvalitete programskog proizvoda i analitičkog hijerarhijskog procesa za dobivanje kvantitativnog oblika rezultata vrednovanja. Istražuje se izravna implementacija normiranog modela predočavanja podataka zasnovanog na SVG specifikaciji u ugrađeni sustav. Identificirani su problemi izravne implementacije odabranog normiranog modela u ugrađeni sustav. Dani su prijedlozi za rješenje identificiranih problema izravne implementacije normiranog modela predočavanja podataka. Razrađuje se prijedlog prilagodbe normiranog modela za prikladan rad u ugrađenim sustavima. Provedena su konkretna vrednovanja primjenjivosti koja pokazuju bolju primjenjivost prilagođene implementacije u odnosu na primjenjivost direktne implementacije normiranog modela predočavanja podataka. Za vrijeme ovog istraživanja također je razvijen program koji podržava definiranu metodologiju vrednovanja. This dissertation researches and defines a methodology of applicability evaluation of normalized data visualization models in embedded systems. The applicability evaluation is based on the combination of the ISO/IEC 9126 standard for the evaluation of software quality and the Analytical Hierarchy Process for obtaining of the evaluation results in the quantitative form. Direct implementation of SVG specification based normalized data visualization models into embedded system is researched. The problems of direct implementation of normalized data visualization models are identified. Different proposals for the solution of the identified problems of direct implementation of normalized data visualization models are given. Also a proposal of the customization of the normalized model for obtaining suitable functionality in embedded systems is presented. The concrete applicability evaluations are done, yielding better applicability results for the modified implementation in comparison to the direct implementation of normalized data visualization models. All results of the measurements and evaluations are commented and explained. During this research a program that supports defined methodology is developed.

Six types of runoff plots were set up and an experimental study was carried out to examine natural rate of soil and water loss in the granite gneiss region of northern Jiangsu Province in China. Through correlation analysis of runoff and soil loss during 364 rainfall events, a simplified and convenient mathematical formula suitable for calculating the rainfall erosivity factor (R) for the local region was established. Other factors of the universal soil loss equation (USLE model) were also determined. Relative error analysis of the soil loss of various plots calculated by the USLE model on the basis of the observed values showed that the relative error ranged from -3.5% to 9.9% and the confidence level was more than 90%. In addition, the relative error was 5.64% for the terraced field and 12.36% for the sloping field in the practical application. Thus, the confidence level was above 87.64%. These results provide a scientific basis for forecasting and monitoring soil and water loss, for comprehensive management of small watersheds, and for soil and water conservation planning in the region.