Efficient Assessment Method Research Articles

Measuring road space consumption by transport modes: Toward a standard spatial efficiency assessment method and an application to the development scenarios of Rajkot City, India

The space “consumed” by various urban passenger transport modes varies greatly depending on the size and the speed of vehicles. Past studies have shown that public transport (PT) and non-motorized transport (NMT) can be up to 20 times more space-efficient compared to a typical car. This optimal use of space is of relevance in an urban context where space is often a constrained resource. Yet space used by vehicles is rarely assessed in the practice of transport planning. There exists no standard method for quantifying the use of space in complex urban settings. This study proposes an approach based on the space-time concept for quantifying and comparing the dynamic (on-road) and still (parking) space used by different transport modes for a specific road network. Transport planning scenarios developed in the Low-carbon Comprehensive Mobility Plan (LCMP) prepared for the city of Rajkot are used to demonstrate the method. The indicators show that significantly less space is used by transport in a scenario that promotes higher use of PT and NMT in comparison to a business-as-usual scenario based on traffic projections for private motorized vehicles. These results provide evidence that could contribute to alleviating chronic congestion expected from car- and motorcycle-based transport development only. Overall, this research describes an assessment framework for low-carbon transport development that would include spatial efficiency concerns.

An efficient method for network security situation assessment

Network security situational assessment, the core task of network security situational awareness, can obtain security situation by comprehensively analyzing various factors that affect network status. Thus, network security situational assessment can provide accurate security state evaluation and security trend prediction for users. Although plenty of network security situational assessment methods have been proposed, there are still many problems to solve. First, because of high dimensionality of input data, computational complexity in model construction could be very high. Moreover, most of the existing schemes trade computational overhead for accuracy. Second, due to the lack of centralized standard, the weights of indicators are usually determined empirically or by subjective opinions of domain expert. To solve the above problems, we propose a novel network security situation assessment method based on stack autoencoding network and back propagation neural network. In stack autoencoding network and back propagation neural network, to reduce the data storage overhead and improve computational efficiency, we use stack autoencoding network to reduce the dimensions of the indicator data. And the low-dimensional data output by hidden layer of stack autoencoding network will be the input data of the error back propagation neural network. Then, the back propagation neural network algorithm is adopted to perform network security situation assessment. Finally, extensive experiments are conducted to verify the effectiveness of the proposed method.

Methods for Evaluating the Effectiveness of Gas Vortex Stabilization in Plasma Torches for Metal Cutting

The well-known recommendations for the design of gas-vortex stabilization systems in metal-cutting plasma torches are considered. Various designs of such systems used in the series PMVR plasma torches developed by the authors are presented. It is noted that the method of efficiency assessment developed by the authors should be based on the calculation of the uniformity distribution of the gas flow velocity. The velocities are calculated in the control sections of the gas-air path in the plasma torch. Various simplified and precise estimation methods are proposed. The velocity distribution in control sections for various modifications of plasma torches are presented. Calculations are made based on the “cold” model of gas flow and its heating by a plasma arc. Recommendations are made on the choice of parameters for evaluating the effectiveness of gas-vortex stabilization in plasma torches. The advantages of the new modernized plasma torches, including those using narrow-jet plasma technology, in terms of the gas-vortex stabilization efficiency are demonstrated. The necessity of using several criteria for evaluating the effectiveness of plasma torches design is noted.

Comprehensive evaluation of NAODESHENG by combining UPLC quantitative fingerprint and antioxidant activity

The screening of marker compound is of great significance to the quality control of traditional Chinese medicine (TCM). One approach which combines fingerprint and biological evaluation has developed rapidly. Multi-wavelength fusion fingerprints and antioxidant activity screening are integrated in this study to evaluate the quality of NAODESHENG. Characteristic multiwavelength fusion fingerprints of 14 batches of samples were generated at five different wavelengths and evaluated by quantitative fingerprinting with ultra-performance liquid chromatography (UPLC). In the quantitative fingerprinting method, 21 components in NAODESHENG were qualitatively and quantitatively analyzed by external standard method. The antioxidant activities of these 21 components was determined by pre-column antioxidant activity test. Multivariate statistical methods such as hierarchical clustering analysis and principal component analysis(PCA) was used to reduce the dimensions and variables from a large number of original data to screening marker compound with bioactivity. Based on the above results, it is suggested that 3'-Methoxy Puerarin and 11 other components should be used as the quality marker of NAODESHENG. This study demonstrates the feasibility of multi-wavelength fusion fingerprinting combined with antioxidant activity analysis, which associates quality control with bioactivity, providing a reliable and efficient method for quantitative assessment of TCM quality consistency.

Machine Learning Accelerates Parameter Optimization and Uncertainty Assessment of a Land Surface Model

AbstractThe performance of land surface models (LSMs) significantly affects the understanding of atmospheric and related processes. Many of the LSMs' soil and vegetation parameters were highly uncertain so that it is crucially important to efficiently optimize them. Here I present a globally applicable and computationally efficient method for parameter optimization and uncertainty assessment of the LSM by combining Markov Chain Monte Carlo (MCMC) with machine learning. First, I performed the long‐term (decadal‐scale) ensemble simulation of the LSM, in which each ensemble member has different parameters' values, and calculated the gap between simulation and observation, or the cost function, for each ensemble member. Second, I developed the statistical machine learning‐based surrogate model, which is computationally cheap but accurately mimics the relationship between parameters and the cost function, by applying the Gaussian process regression to learn the model simulation. Third, I applied MCMC by repeatedly evaluating the surrogate model to get the posterior probabilistic distribution of parameters. Using satellite passive microwave brightness temperature observations, both synthetic and real‐data experiments in the Sahel region of west Africa were performed to optimize unknown soil and vegetation parameters of the LSM. The primary findings are (1) the proposed method is 50,000 times as fast as the direct application of MCMC to the full LSM; (2) the skill of the LSM to simulate both soil moisture and vegetation dynamics can be improved; and (3) I successfully quantify the characteristics of equifinality by obtaining the full nonparametric probabilistic distribution of parameters.

О необходимости применения современных инструментов менеджмента как основы повышения эффективности деятельности учреждений культуры

The present research featured official methods of efficiency assessment of cultural institutions. The existing system focuses on quantitative assessment and does not take into account the delayed social and economic effects associated with the quality of human capital. Therefore, the current system of indicators requires expansion. Cultural institutions acquire state or municipal support based on their compliance to efficiency criteria. The author analyzed the financial support provided for implementation of priority national projects. The amount of funds for the development of the cultural sphere appeared to be one of the smallest. The current global uncertainty and new challenges caused the budget funding focus to shift. Taking into consideration the growing variability of external environment, cultural institutions can become efficient only by using modern management tools. The author studied official approaches to assessing the efficiency of cultural institutions. The research objective was to justify the need to use modern management tools in order to increase the efficiency of cultural institutions. The study was based on the institutional approach, as well as the methods of analysis, synthesis, and comparison. The paper introduces some practical recommendations for the use of modern management tools and the application of national standards. The results can be of some interest to top management of cultural institutions. The author proposes systemic and process approaches for implementation of creative projects. She believes that PDCA methodology, benchmark and GAP analyses, and the method of key performance indicators will develop the dynamic capabilities of cultural institutions and increase their strategic flexibility in conditions of high external variability.

Fitness-Tracker Assisted Frailty-Assessment Before Transcatheter Aortic Valve Implantation: Proof-of-Concept Study

BackgroundWhile transcatheter aortic valve replacement (TAVR) has revolutionized the treatment of aortic valve stenosis, wearable health-monitoring devices are gradually transforming digital patient care.ObjectiveThe aim of this study was to develop a simple, efficient, and economical method for preprocedural frailty assessment based on parameters measured by a wearable health-monitoring device.MethodsIn this prospective study, we analyzed data of 50 consecutive patients with mean (SD) age of 77.5 (5.1) years and a median (IQR) European system for cardiac operative risk evaluation (EuroSCORE) II of 3.3 (4.1) undergoing either transfemoral or transapical TAVR between 2017 and 2018. Every patient was fitted with a wrist-worn health-monitoring device (Garmin Vivosmart 3) for 1 week prior to the procedure. Twenty different parameters were measured, and threshold levels for the 3 most predictive categories (ie, step count, heart rate, and preprocedural stress) were calculated. Patients were assigned 1 point per category for exceeding the cut-off value and were then classified into 4 stages (no, borderline, moderate, and severe frailty). Furthermore, the FItness-tracker assisted Frailty-Assessment Score (FIFA score) was compared with the scores of the preprocedural gait speed category derived from the 6-minute walk test (GSC-6MWT) and the Edmonton Frail Scale classification (EFS-C). The primary study endpoint was hospital mortality.ResultsThe overall preprocedural stress level (P=.02), minutes of high stress per day (P=.02), minutes of rest per day (P=.045), and daily heart rate maximum (P=.048) as single parameters were the strongest predictors of hospital mortality. When comparing the different frailty scores, the FIFA score demonstrated the greatest predictive power for hospital mortality (FIFA area under the curve [AUC] 0.844, CI 0.656-1.000; P=.048; GSC-6MWT AUC 0.671, CI 0.487-0.855; P=.42; EFS-C AUC 0.636, CI 0.254-1.000; P=.44).ConclusionsThis proof-of-concept study demonstrates the strong predictive performance of the FIFA score compared to that of the conventional frailty assessments.

Efficient reliability assessment method for bridges based on Markov Chain Monte Carlo (MCMC) with Metropolis-Hasting Algorithm (MHA)

Reliability assessment plays a vital roles in bridge health monitoring (BHM) technique. The analysis results of inspection data and monitoring data, such as numerical data, image data and video data, are not well due to there is no efficient reliability assessment method. This paper analysed the applied effect of Markov Chain Monte Carlo (MCMC) simulation method. The subset simulation method is used to analyse small failure probability events. Furthermore, the reliability assessment process based on Markov Chain Monte Carlo (MCMC) simulation method with Metropolis-Hasting Algorithm (MHA) is proposed. The advantage of this method is to improve the application efficiency and accuracy of reliability assessment based on BHM data.

Energy efficiency assessment and resource optimization using novel DEA model: evidence from complex chemical processes

Energy efficiency assessment and resource allocation optimization are conducive to improve the production and reduce carbon emissions in complex chemical processes. And the traditional energy efficiency assessment method based on data envelopment analysis (DEA) does not distinguish the effective decision-making units (DMUs) better. Therefore, this paper proposed a novel DEA method combining the cosine similarity (CS) (DEA-CS) to estimate the energy efficiency and optimize the resource of complex chemical plants. The ineffective and effective DMUs can be obtained by the DEA. Then, the CS can further distinguish the effective DMUs to obtain the optimal DMU, which makes the DEA model have the better discriminating ability. Moreover, through the input and output of the optimal DMU, the resource of ineffective DMUs can be optimized. Finally, the proposed model is used in energy efficiency assessment and resource optimization of ethylene and purified terephthalic acid (PTA) production plants in complex chemical processes. The experiments show that the energy-saving potential of ethylene and PTA production plants is improved by about 13.61% and 1.22%, respectively. Meanwhile, the average carbon emission–saving potential of the ethylene production plants is reduced by 12.58%, approximately.

Valuation of Water Resource Green Efficiency Based on SBM–TOBIT Panel Model: Case Study from Henan Province, China

With progress in China’s industrialization and urbanization, the contradiction of social and economic development with water resource supply–demand and water environmental pollution becomes increasingly prominent. To cope with the dual constraints of resource shortage and environmental regulations, the concept of water resource green efficiency that considers economic, environmental, and ecological factors is highly involved to promote sustainable economic development. The theoretical and practice circle devote to scientific green efficiency assessment of water resources and effective recognition of relevant influencing factors. However, to an extent they neglect social benefits brought by sustainable development and possible influences of industrial restructuring on green efficiency. They also lack concern on green efficiency of water resources in inland arid areas. To offset the disadvantages of existing studies, the philosophy of sustainable development was integrated into the input–output assessment system of green efficiency of water resources, and an assessment model was constructed using the SBM–Tobit (slack-based measure and Tobit) method. Moreover, a case study based on Henan Province, China was carried out. The green efficiencies of water resources in 18 cities of Henan Province during 2011–2018 were calculated. The operation mechanism of relevant influencing factors was discussed, and the methods to improve green efficiency of water resources were determined. Results reveal that the sustainable green efficiency of water resources in Henan Province increased in fluctuation during 2011–2018. The mean green efficiency increased from 0.425 in 2011 to 0.498 in 2018. At present, green efficiency of water resources in Henan Province remains at a low level, with a mean of 0.504. Reducing water consumption intensity and increasing investment to water environmental pollution technologies can promote green efficiency of water resources significantly. Conclusions provide a new method for scientific measurement and green efficiency assessment of water resources in inland arid areas.

Calculation Model and Method of Target Damage Efficiency Assessment Based on Warhead Fragment Dispersion

There are many uncertain information and incompleteness factors on warhead fragments dispersion and the self-destructive factors of target damage. It is very difficult to scientifically give a target damage efficiency assessment calculation method of a proximity warhead fragments group. This article proposes a warhead fragments dispersion parameters’ measurement method using the intersection of two light-field cameras and a target damage efficiency assessment calculation method with a multiparameter correlation of warhead fragments dispersion under uncertain information. We research a correlation mechanism between warhead fragments parameters and target damage efficiency. Warhead fragments parameters are combined with the projectile burst location to establish a distribution density function under warhead fragments dispersion with uncertain information. The point trajectory rules of warhead fragments are utilized to set up the spatial position calculation model of warhead fragments hitting the 3-D surface of the target to give the calculation method of the target damage area caused by proximity warhead fragments. The damaged area combined with the damage characteristics of the target itself is used to establish a damage probability calculation model of warhead fragments dispersion to the target under the multi-intersection status of the projectile and target. Simulation analysis reveals the change rule of proximity warhead fragments parameters and target damage efficiency. Experimental results verified the calculation model of target damage efficiency of warhead fragments with uncertain information scientific. These research achievements can provide a scientific theory foundation for ammunition safety measurement, air defense campaign efficiency assessment, and smart ammunition damage efficiency assessment and have high scientific theory research value.

How to Use and Apply Assessment Tools in Medical Education?

Assessment in medical education usually gives the evidence that learning was carried out and the learning objectives were achieved. The assessment program is a measurement tool to evaluate the progress in knowledge, skills, behaviors, and the attitude of students. So, the planning for an effective assessment program should be based on instructional objectives, instructional activities, and efficient assessment methods. Thus, a well-designed assessment procedure should be characterized by validity and reliability. There are two methods for interpreting the results of students’ performance, norm-referenced and criterion-referenced; the first gives a relative ranking of students while the second describes learning tasks that students can and cannot perform. The information that gets from the assessment results should be used effectively to evaluate and revise the instructional course for more improvement. Therefore, the reporting of the assessment results to stakeholders should be clear, comprehensive, and understandable to prevent misinterpretation that may affect students and other stakeholders adversely.

Overwhelming role of hydrology-related variables and river types in driving diatom species distribution and community assemblage in streams in Cyprus

Mediterranean streams are naturally highly-stressed environments mainly due to wide seasonal and inter-annual fluctuations in water quantity. This natural pressure will be exacerbated by climate change and is a significant challenge when establishing efficient assessment methods. We studied environmental parameters (hydromorphology, hydrology, physical and chemical variables) and analysed 171 diatom samples from 65 stations in Cyprus (south-western part). Analyses revealed 290 taxa (273 identified to the species -or intraspecific- level) belonging to 65 genera. Even a tentative application of a Red-List approach underlined the overwhelming importance of hydrology-related variables and river types in determining species distribution and community ecological attributes in the water-stressed island of Cyprus. Somewhat unexpectedly, both species from threat categories of the diatom Red List for Central Europe (2018) and species one might predict would be included in such categories in a possible future Red List tailored for Cyprus occurred more frequently and were more relevant in assemblages from sites in intermittent streams. We found a majority of motile, medium- to small-sized, diatom species, including a small number of colony-forming species. We found several species known to be effective first colonizers (pioneer species) and, among these, there was a striking preponderance (80%) of Achnanthidium species, often with several species co-occurring, particularly at reference sites. A four-factor PERMANOVA found that all type (essentially hydrology-related) variables were significant, and there was also a significant effect of season. Agglomerative hierarchical cluster analysis revealed three end-groups, with groups being separated on ecohydro(geo)logical grounds (lentic/lotic), sediment grain size, discharge and pH. The reference sites were analysed in more detail to identify environmental determinants. 28% of the variation in diatom assemblage composition was explained by the measured variables, with those associated with stream type and hydrology explaining the greatest proportions (12 and 10%, respectively) whilst season accounted for the remainder. Our study emphasised a need for detailed investigations of ecological and distributional (including Red List status) traits of diatom species, and to acknowledge the importance of the hydrological peculiarities of Mediterranean streams, in particular the dramatic seasonal variability, when developing ecological assessment protocols for the region.

Energy Efficiency Evaluation Based on Data Envelopment Analysis: A Literature Review

The importance and urgency of energy efficiency in sustainable development are increasing. Accurate assessment of energy efficiency is of considerable significance and necessity. The data envelopment analysis (DEA) method has been widely used to study energy efficiency as a total factor efficiency assessment method. In order to summarize the latest research on DEA in the field of energy efficiency, this article first analyzes the overall situation of related literature published in 2011–2019. Subsequently, the definition, measurement and evaluation variables of energy efficiency are introduced. After that, this article reviews the current DEA model and its extension models and applications based on different scenarios. Finally, considering the shortcomings of the existing DEA model, possible future research topics are proposed.

Quantitative Method for Comparative Assessment of Particle Removal Efficiency of Fabric Masks as Alternatives to Standard Surgical Masks for PPE

In response to the COVID-19 pandemic, cloth masks are being used to control the spread of virus, but the efficacy of these loose-fitting masks is not well known. Here, tools and methods typically used to assess tight-fitting respirators were modified to quantify the efficacy of community-produced and commercially produced fabric masks as personal protective equipment. Two particle counters concurrently sample ambient air and air inside the masks; mask performance is evaluated by mean particle removal efficiency and statistical variability when worn as designed and with a nylon overlayer, to independently assess fit and material. Worn as designed, both commercial surgical masks and cloth masks had widely varying effectiveness (53%–75% and 28%–91% particle removal efficiency, respectively). Most surgical-style masks improved with the nylon overlayer, indicating poor fit. This rapid testing method uses widely available hardware, requires only a few calculations from collected data, and provides both a holistic and aspect-wise evaluation of mask performance.

EN Energy efficiency projects deployment for Ukrainian industry. Efficiency assessment method for energy exchange and the ratio of temperature change in heat exchangers

Energy efficiency projects deployment for Ukraine is one of the challenging task today. Ukrainian in­dustry faces very complex environment for project development as well as its deployment within organization nowadays. UA Policy struggle to keep place on the European market to have possibility not only be a part of global policy but to go forward and to bring benefits for macro and micro economy. Fresh breath by integration energy systems within project management into business model of organization let to move closer to hold under control energy efficiency projects realization and avoid financial risks. Environmental policy and energy policy play crucial role for Ukrainian transformation into European pla­yer. Presented proactive plan provides possibilities to deliver the intended economic and environmental benefits of the Ukrainian energy labelling and ecological design directives. These directives are in use or are under development process by increasing the rates of compliance with their energy efficiency requirements. To start from the energy efficiency development process investigation in order to have possibilities to make corrections on the stage of modeling and design can bring benefits and reduce costs for end users. To evaluate the efficiency of heat exchangers, there are over 40 different private integral energy efficiency criteria. Such a number makes the estimation of heat exchangers not always objective and sufficiently definite, which does not allow to algorithmize the task of determining the efficiency of heat exchangers. On the foundation of the system element representation for the heat exchange network, the concepts of energy potential and energy efficiency of energy exchange are proposed. The obtained equations allow us to determine the efficiency of energy exchange not only for an element of the heat exchange network, but also for a complex system as a whole with a minimum of information about the system

Economic efficiency of plastic recycling plant construction

Solving the problem of plastic pollution is a priority for all of mankind. A significant part of all plastic waste is recyclable and reusable. However, not every method of recycling and reusing plastic is cost-effective. The aim of the study is to justify the economic efficiency of the construction and operation of a plastic recycling plant in the city of Kazan (Russian Federation). When performing the calculations, the discounted method for efficiency assessment of investment projects was used. The method involves the calculation of several efficiency criteria: NPV, IRR, PBP, PI.The study justifies the economic efficiency of the plant construction project based on the calculated indexes: NPV (net present value of the project) is 182 million rubles, IRR is 41.6 %. As a result of risk modeling, it was found out that the greatest impact on the net present value of the project is made by an increase in the discount rate. Moreover, the project is highly resistant to a possible reduction in the price and volume of sales, growth in current and investment expenses. Putting the results into practice opens up potential for solving the complex task of saving natural resources, expanding the local raw material base for the production of building materials, and disposing waste having a long decomposition period, more specifically plastic waste.

An accurate and efficient method for occlusal tooth wear assessment using 3D digital dental models

Tooth or material wear in a dentition is a common finding that requires timely diagnosis for management and prevention of further loss or associated esthetic or functional impairment. Various qualitative and quantitative methods have been suggested to measure tooth or material wear, but they present with limitations, such as imprecision, subjectivity, or high complexity. Here we developed and assessed an efficient 3D superimposition method to accurately measure occlusal tooth wear on 3D digital dental models. For this purpose, teeth on plaster casts were manually grinded on their occlusal surfaces to simulate various degrees of tooth wear. The casts were scanned using a surface scanner. Grinded tooth crowns (T1) were segmented and compared to the original crowns (T0) using five 3D surface superimposition techniques and a gold standard technique (GS). GS measurements were obtained by using intact adjacent structures as superimposition references. The technique of choice (complete crown with 30% estimated overlap of meshes) showed the best reproducibility (maximum difference < 0.050 mm3) and excellent agreement with the GS technique (median difference: 0.032 mm3). The suggested 3D superimposition method offers a highly efficient and accurate tool for tooth wear assessment, which could be applicable to clinical conditions.

A Household Energy Efficiency Index Assessment Method Based on Non-Intrusive Load Monitoring Data

Various countries in the world are vigorously developing energy-saving industries and attaching importance to the improvement of household energy efficiency, but it is difficult to evaluate user power consumption characteristics due to insufficient information and large data granularity. It is, however, possible to evaluate the energy efficiency of household users via non-intrusive load monitoring (NILM). This paper explores the energy efficiency assessment of residential users and proposes a household energy efficiency assessment method based on NILM data. An energy efficiency assessment index of residents is provided by analyzing factors that affect residents’ energy efficiency. This index is clear, operable, and easy to obtain and quantify. Based on NILM information, clustering, and comprehensive evaluation, as well as combining the entropy weight method with the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), a user’s energy efficiency can be evaluated and analyzed. Some case studies are provided to verify the validity of the proposed method based on non-intrusive information, to analyze the characteristics and deficiencies of the user’s energy consumption, and to give corresponding energy recommendations.

Compositional kernel learning using tree-based genetic programming for Gaussian process regression

Although Gaussian process regression (GPR) is a powerful Bayesian nonparametric regression model for engineering problems, its predictive performance is highly dependent on a kernel for covariance function of GPR. However, choosing a proper kernel is still challenging even for experts. To choose proper kernel automatically, this study proposes a compositional kernel (CPK) learning using tree-based genetic programming (GEP). The optimal structure of the kernel is defined as a compositional representation based on sums and products of eight base-kernels. The CPK can be encoded as a tree-structure, so that tree-based GEP is employed to discover an optimal tree-structure of the CPK. To avoid overly complex solution in GEP, the proposed method introduced a dynamic maximum tree-depth technique. The novelty of the proposed method is to utilize more flexible and efficient learning capability to learn the relationship between input and output than existing methods. To evaluate the learning capability of the proposed method, seven test functions were firstly investigated with various noise levels, and its predictive accuracy was compared with existing methods. Reliability problems in both parallel and series systems were introduced to evaluate the performance of the proposed method for efficient reliability assessment. The results show that the proposed method generally outperforms or performs similarly to the best one among existing methods. In addition, it is also shown that proper kernel function can significantly improve the performance of GPR as the training data increases. Stated differently, the proposed method can learn the function of being fitted efficiently with less training samples than existing methods. In this context, the proposed method can make powerful and automatic predictive modeling based on GPR in engineering problems.