Traditional Evaluation Model Research Articles

Multiscale Persistent Functions for Biomolecular Structure Characterization.

In this paper, we introduce multiscale persistent functions for biomolecular structure characterization. The essential idea is to combine our multiscale rigidity functions (MRFs) with persistent homology analysis, so as to construct a series of multiscale persistent functions, particularly multiscale persistent entropies, for structure characterization. To clarify the fundamental idea of our method, the multiscale persistent entropy (MPE) model is discussed in great detail. Mathematically, unlike the previous persistent entropy (Chintakunta et al. in Pattern Recognit 48(2):391-401, 2015; Merelli et al. in Entropy 17(10):6872-6892, 2015; Rucco et al. in: Proceedings of ECCS 2014, Springer, pp 117-128, 2016), a special resolution parameter is incorporated into our model. Various scales can be achieved by tuning its value. Physically, our MPE can be used in conformational entropy evaluation. More specifically, it is found that our method incorporates in it a natural classification scheme. This is achieved through a density filtration of an MRF built from angular distributions. To further validate our model, a systematical comparison with the traditional entropy evaluation model is done. It is found that our model is able to preserve the intrinsic topological features of biomolecular data much better than traditional approaches, particularly for resolutions in the intermediate range. Moreover, by comparing with traditional entropies from various grid sizes, bond angle-based methods and a persistent homology-based support vector machine method (Cang et al. in Mol Based Math Biol 3:140-162, 2015), we find that our MPE method gives the best results in terms of average true positive rate in a classic protein structure classification test. More interestingly, all-alpha and all-beta protein classes can be clearly separated from each other with zero error only in our model. Finally, a special protein structure index (PSI) is proposed, for the first time, to describe the "regularity" of protein structures. Basically, a protein structure is deemed as regular if it has a consistent and orderly configuration. Our PSI model is tested on a database of 110 proteins; we find that structures with larger portions of loops and intrinsically disorder regions are always associated with larger PSI, meaning an irregular configuration, while proteins with larger portions of secondary structures, i.e., alpha-helix or beta-sheet, have smaller PSI. Essentially, PSI can be used to describe the "regularity" information in any systems.

DEA cross-efficiency evaluation and ranking method based on interval data

Data envelopment analysis (DEA) is an important method of efficiency evaluation. Cross-efficiency evaluation is one of the main aspects of research in the field of DEA that has been applied in various fields. In the traditional cross-efficiency evaluation model, the variable data of decision-making units is exact. Dynamic information is frequently unable to reflect the whole characteristic when determining the exact data. In this study, we select interval data to represent the dynamic information of some variables in the evaluation process. We then build a solution method based on interval efficiency and DEA cross-efficiency. This method retains the reflection of interval data on uncertain variable properties. Finally, the stochastic multi-criteria acceptability analysis 2 (SMAA2) is introduced to solve the whole sequence problem of interval efficiency. We present a case study from a set of 19 reservoir dams suffered from Wenchuan earthquake in Luojiang County, Sichuan Province to demonstrate the applicability of the proposed model.

Rating Credits of Online Merchants Using Negative Ranks

Electronic commerce has become increasingly popular. Although it brings significant convenience to people's lives, a purchaser often hesitates to provide a negative rating to a merchant (or commodity) after a bad online shopping experience because his sensitive information (e.g., address, telephone number, and email address) would be available to the merchant. This makes the purchaser uncomfortable and even unsafe, and the purchaser tends to contribute better but untrue ratings. Hence, the privacy of the purchaser's score is vitally important to the development of electronic commerce. In this study, we apply for the first time an artificial immune technique (i.e., the negative survey) to rate the credits of online merchants, and we propose a new credit rating model, called a negative rating model, that could preserve the privacy of the purchaser's score with low additional computational cost. Moreover, the results obtained from our credit rating model exhibited a high correlation with those from the traditional evaluation model. Therefore, the proposed model has promising application prospects.

A New Analytical Model to Study the Ionospheric Effects on VHF/UHF Wideband SAR Imaging

With a view to detecting foliage-obscured/ground-obscured targets on a global scale, low frequency (i.e., very high frequency (VHF)/ultrahigh frequency (UHF) band) and wide bandwidth is a trend in future spaceborne synthetic aperture radar (SAR) system design. However, due to the dispersion of ionosphere, VHF/UHF wide bandwidth SAR signals inevitably experience adverse effects. In contrast to narrow bandwidth SAR at VHF/UHF, quadratic and cubic ionospheric phase errors will introduce noticeable effects on future wide-bandwidth SAR systems. Traditional evaluation models based on Taylor series expansion may become inaccurate when an extremely wide bandwidth is considered. With a focus on this this issue, first, the shortcoming of Taylor series expansion of ionospheric phase errors is briefly discussed in this paper. Then, a new analytical model based on Legendre orthogonal polynomials is developed, which is expected to be widely applicable, especially for low-frequency and wide-bandwidth SAR systems. Finally, compared with previous models based on Taylor series expansion, numerical simulations and evaluations show the superiority of the new model.

Cost-sensitive boosted tree for loan evaluation in peer-to-peer lending

Abstract Loan evaluation is an effective tool for credit risk assessment in the peer-to-peer (P2P) lending market. However, most of the traditional loan evaluation models assume a balanced misclassification cost, which is far from business reality and leaves opportunities for investigating the cost-sensitive modelling approaches. Moreover, few existing studies consider the special characteristics of P2P lending. In this paper, we propose a cost-sensitive boosted tree loan evaluation model by incorporating cost-sensitive learning and extreme gradient boosting (XGBoost) to enhance the capability of discriminating potential default borrowers. Therefore, a portfolio allocation model that converts the portfolio optimization problem into an integer linear programming is proposed as a decision support system for unprofessional lenders. Unlike existing studies, which mainly evaluate the model through accuracy-based metrics, this study measures the expected profitability based on the annualized rate of return (ARR) and proposes a new metric (ARR curve) reflecting the ARR over different rejection rates. Two real-world P2P lending datasets are examined, and explanatory data analysis shows that explanatory variables differ in predicting the probability of default and profitability. Experimental results reveal that the area under the ARR curve is not a considerable metric in evaluating models from a profit perspective. Conventional cost-insensitive models may even lead to negative returns, whereas the proposed loan evaluation and portfolio allocation model are the best performing methods over the two datasets in terms of profitability.

Imaging quality evaluation method of pixel coupled electro-optical imaging system

With advancements in high-resolution imaging optical fiber bundle fabrication technology, traditional photoelectric imaging system have become “flexible” with greatly reduced volume and weight. However, traditional image quality evaluation models are limited by the coupling discrete sampling effect of fiber-optic image bundles and charge-coupled device (CCD) pixels. This limitation substantially complicates the design, optimization, assembly, and evaluation image quality of the coupled discrete sampling imaging system. Based on the transfer process of grayscale cosine distribution optical signal in the fiber-optic image bundle and CCD, a mathematical model of coupled modulation transfer function (coupled-MTF) is established. This model can be used as a basis for following studies on the convergence and periodically oscillating characteristics of the function. We also propose the concept of the average coupled-MTF, which is consistent with the definition of traditional MTF. Based on this concept, the relationships among core distance, core layer radius, and average coupled-MTF are investigated.Results show that the coupled-MTF oscillation converges to a fixed value when the deviation between a spatial frequency of input signal and Nyquist frequency is 1% and when the total number of pixels in the coupled system is more than 1000. The minimal frequency deviation corresponds to the slow velocity of the oscillational convergent. The oscillation amplitude of coupled-MTF differs in tangential and sagittal directions in a manner related to the corresponding pixel coupling error. The coupled-MTF periodically oscillates with the alignment error between the coupled pixel. One cycle is equivalent to the diameter of fiber cladding. The observation from the simulations further reveal that the distance between adjacent fiber cores and the dimension of core layer are directly related to the system imaging quality and the signal-to-noise ratio. Moreover, the average coupled-MTF can be used to quantitatively describe the function of related parameters and the imaging quality of the system.

SHALE RESERVOIR CONDUCTIVE MECHANISM SIMULATION BASED ON PERCOLATION NETWORK

AbstractThe shale gas reservoir storage space mainly includes micro pores and cracks of micron and nano scale. Owing to the complex pore network, as well as high content of kerogen and clay minerals in shale matrix and existence of conductive minerals, especially pyrite, the shale reservoir conductive mechanism is quite different from that of conventional reservoir, and the I‐Sw curve obtained by core electricity experiment is non‐linear which makes traditional evaluation models such as Archie's law not suitable. Aiming at these issues, according to actual core experiment and CT scan data, a three dimensional percolation network is established with randomized algorithm and the node voltage and current are calculated through over‐relaxation iteration algorithm. With this network, the reasons for non‐Archie property and the influence factors of shale reservoir are analyzed. Simulation results show that pore structure, shape and size, mineral composition and formation water resistivity have different effects on the reservoir resistivity. By changing the setting value, single‐correlation between the reservoir resistivity and these factors can be built, and percolation correction model is also developed to calculate shale reservoir water saturation. The method has achieved a good effect in a certain shale gas field in Sichuan, China, which presents a good application prospect and provides a new thought on solving complex problems in shale gas field exploration and development with network simulation methods.

Optimization of Fuzzy Comprehensive Evaluation Model of Soil Heavy Metal Pollution Based on the Comprehensive Weight

In order to optimize the fuzzy comprehensive evaluation model, verify the soil pollution stage in tea Planting surface area of northeast Guizhou plateau mountain area. Using the principle of minimum relative information entropy and combined Pollutants exceed the standard ratio method and Double weight exceeds the standard weighting method to form the comprehensive weight for optimized the traditional fuzzy comprehensive evaluation model. Then this paper evaluated the soil pollution in the main planting areas of tea. The results showed that: The optimized fuzzy comprehensive evaluation model which integrated the soil heavy metal concentration and toxicity in the calculation of the weights of evaluation factor, the evaluation results is more scientific; the origin of tea soil cleaning rate up to 38.81%, still cleaning rate of 61.19%, so there is no soil polluted area, which proves that the soil environmental quality in the plant of tea is preference.

Governance of private label as a strategic asset: developing a brand valuation model

This paper aims at identifying which factors should be considered in the building of an economic evaluation model for the private label brand. In fact, some specific characteristics of private label, with respect to industrial brand, make unusable the consolidated models available. The results of the paper are the definition of some specific factors of private label, the assumptions about how these features impact on the traditional economic evaluation models and how these could be included in a model. Because of the complexity of the topic, the hypothesis is to build a model of synthesis, made of two parts: one part for a Financial-Based evaluation of Brand Equity, with the addition of some specific factors and indicators to the traditional formulas, while the other part is for a Consumer-based evaluation of Brand Equity, thanks to an index that summarizes the strength of private label brands from the consumer perspective. The private label economic evaluation has some relevant managerial implications on the retail system, on the vertical supply chain relationships and on the understanding of the strategic nature of this asset.

Study on clustering of micro-blog business enterprise users reputation based on web crawler

Micro-blog is a social tool of the new network era. It swept the world with its convenience of usage and real-time release of information. PageRank and Hits algorithms are the most widely used method in the evaluation of micro-blog's influence. But the two algorithms have the deficiency of poor performance and unrelated to specified keywords. We proposed a micro-blog enterprise users' reputation analysis model based on clustering network and improved PageRank algorithm. The model was simulated with the Sina micro-blog data acquired by a web crawler, and the model was compared with Hits and PageRank algorithm. The results show that the model has better convergence and its computational efficiency is superior to the traditional evaluation model based on PageRank or Hits algorithm.

Study on clustering of micro-blog business enterprise users reputation based on web crawler

Micro-blog is a social tool of the new network era. It swept the world with its convenience of usage and real-time release of information. PageRank and Hits algorithms are the most widely used method in the evaluation of micro-blog's influence. But the two algorithms have the deficiency of poor performance and unrelated to specified keywords. We proposed a micro-blog enterprise users' reputation analysis model based on clustering network and improved PageRank algorithm. The model was simulated with the Sina micro-blog data acquired by a web crawler, and the model was compared with Hits and PageRank algorithm. The results show that the model has better convergence and its computational efficiency is superior to the traditional evaluation model based on PageRank or Hits algorithm.

Patient and Family Engagement in Research in Era 3

Patient and Family Engagement in Research in Era 3

Better resource management: An improved resource and environmental efficiency evaluation approach that considers undesirable outputs

Evaluating resource and environmental efficiency is helpful to stakeholders when making iterative improvements to resource management policies, with regards to either their business activities or to societal management. Traditional evaluation models—which consider undesirable outputs in measuring environmental efficiency—are output-oriented, and so they only pursue the minimum undesirable outputs and the maximum desirable outputs, based on current inputs. The growing depletion of nonrenewable resources makes it difficult to acquire the resources essential to socioeconomic development. In such circumstances, better consideration of resource use (i.e., inputs) is required when considering both desirable and undesirable outputs. This study aims to develop an improved approach by which to evaluate resource and environmental efficiency, based on data envelopment analysis; in this approach, the evaluation of resource inputs into the objective function is introduced. On account of its improvements, the new model can measure not only resource and environmental efficiency, but also efficiencies with regards to resource inputs, undesirable outputs, and desirable outputs. The feasibility of the model is verified through its use in undertaking further empirical analyses of data from mainland China’s 31 provinces. The results of that analysis show the average resource and environmental efficiency value of China’s inefficient provinces to be only 0.65—a value that suggests that mainland China’s resource and environmental efficiency needs to be further improved.

Impact of parameter fluctuations on the performance of ethanol precipitation in production of Re Du Ning Injections, based on HPLC fingerprints and principal component analysis

The present study was designed to determine the relationships between the performance of ethanol precipitation and seven process parameters in the ethanol precipitation process of Re Du Ning Injections, including concentrate density, concentrate temperature, ethanol content, flow rate and stir rate in the addition of ethanol, precipitation time, and precipitation temperature. Under the experimental and simulated production conditions, a series of precipitated resultants were prepared by changing these variables one by one, and then examined by HPLC fingerprint analyses. Different from the traditional evaluation model based on single or a few constituents, the fingerprint data of every parameter fluctuation test was processed with Principal Component Analysis (PCA) to comprehensively assess the performance of ethanol precipitation. Our results showed that concentrate density, ethanol content, and precipitation time were the most important parameters that influence the recovery of active compounds in precipitation resultants. The present study would provide some reference for pharmaceutical scientists engaged in research on pharmaceutical process optimization and help pharmaceutical enterprises adapt a scientific and reasonable cost-effective approach to ensure the batch-to-batch quality consistency of the final products.

Challenges in evaluating the EU’s lifelong learning policies

ABSTRACTSince the early 1990s, lifelong learning has become a major policy concern for the European Union, being seen as a means for enabling individuals to be more competitive in social and economic contexts that are continually changing. After a series of white papers and strategies in the field of lifelong learning, the EU launched the Lifelong Learning Programme in 2007, which dealt with the most pressing issues in the field. In light on the complexity of this programme, we need to ask ourselves if traditional evaluation models and approaches are appropriate for evaluating complex educational policies and programmes in the educational field. Thus, the stake of this article is to explore the challenges which arise when evaluating the EU’s lifelong learning policies and programmes in general, and the Lifelong Learning Programme 2007–2013 in particular, as well as to propose several new directions for overcoming these challenges.

Financial analysis and credit solvency evaluation of a selected enterprise case study of a company 'Aleva Novi Knezevac'

There is a large number of developed methods and indicators of financial analysis i.e. analysis of financial reports. Therefore, it was useful to develop a basic template indicator, that would include all the indicators together and that would have the same meaning for all of its users. However, the requirements of users of financial information determine the level and form of desired information. Today, the favorable characteristics of a company are primarily seen as its solvency. Solvency represents the degree of certainty in making predictions related to its survival and development, as well as a review of its quantitative and qualitative skills, primarily yielding abilities, but also material and financial capacities. Solvency, in the narrow sense of a word, represents a company's credit ability, and the ability to maintain current liquidity, while in the broader sense it represents a company's overall market position. In practice, there are two models of credit solvency evaluation: the traditional model of credit solvency evaluation, and the Altman's 'Z'-model (score). Since these two models differ, in this paper we performed credit solvency evaluation in the case of a joint stock company called 'Aleva' from Novi Kneževac, with the aim of comparing the results of credit solvency evaluation with the company's reliability.

A novel model for evaluating environmental governance performance based on trends analysis

The traditional static evaluation model of environmental governance performance usually leads to large deviations in the results owing to the limitations of the approach itself. This paper demonstrates the unified expression of the static model, and furthermore, proposes the trend analysis evaluation model taking the effect of status, the effect of accumulation, the effect of the given trend, as well as the effect of trend change into consideration simultaneously. A case study of the 15 largest cities in China shows that the novel approach could balance the trade-off between the short-term and long-term efforts on environmental governance issues, and is overall more objective and effective.

A Quantitative Risk Evaluation Model for Network Security Based on Body Temperature

These days, in allusion to the traditional network security risk evaluation model, which have certain limitations for real-time, accuracy, characterization. This paper proposed a quantitative risk evaluation model for network security based on body temperature (QREM-BT), which refers to the mechanism of biological immune system and the imbalance of immune system which can result in body temperature changes, firstly, through ther-contiguous bits nonconstant matching rate algorithm to improve the detection quality of detector and reduce missing rate or false detection rate. Then the dynamic evolution process of the detector was described in detail. And the mechanism of increased antibody concentration, which is made up of activating mature detector and cloning memory detector, is mainly used to assess network risk caused by various species of attacks. Based on these reasons, this paper not only established the equation of antibody concentration increase factor but also put forward the antibody concentration quantitative calculation model. Finally, because the mechanism of antibody concentration change is reasonable and effective, which can effectively reflect the network risk, thus body temperature evaluation model was established in this paper. The simulation results showed that, according to body temperature value, the proposed model has more effective, real time to assess network security risk.

Análisis de las Actitudes de la Educación Física en la E.S.O (Attitudinal analysis of Physical Education in Compulsory Secondary Education (E.S.O.))

Objetivo del trabajo: crear un programa de evaluación de las actitudes en Educación Física para la E.S.O. 1. Diseñar un modelo de evaluación de las Actitudes para Educación Física. 2. Crear instrumentos de recogida, análisis e interpretación de datos. 3. Validez de los objetivos. 4. Verificar la hipótesis. Hipótesis: «cuanta más información se disponga sobre un alumno, disminuyen las posibilidades de errar en su calificación». Metodología: se ha seguido un Diseño Longitudinal de Panel. Dos grupos de trabajo, 4º «F» y, 4º «G» de E.S.O., I. E. S. de Málaga «Universidad Laboral», curso 06/07. 4º F evaluado con el modelo tradicional de evaluación, 4º G con el experimental. En los dos grupos se recogieron variables actitudinales: las variables independientes se aplicaron al grupo experimental, y las dependientes al grupo control. Los resultados, se analizaron, para ver si la variable independiente, era la causante de la mejora en los resultados. Se ha empleado la observación directa, la recogida de datos, utilizando instrumentos: cuadernos de registros de 4º de E.S.O., hojas personales de actitudes por ámbitos de actuación, diario de observación del alumno, y grupo, y libro de texto para 4º de E.S.O.Conclusión: todo proceso de evaluación es complejo y en Educación Física más, por el volumen, la variedad, diversidad y la procedencia de la información, por diseñar instrumentos de recogida de datos, por individualizar el proceso, por estar el alumnado en movimiento. Los resultados afirman que la evaluación es eficaz, cuanta más información se tenga.Abstract: Objective of the work: to create a program of evaluation of the attitudes in Physical education for the E.S.O. 1. To design a model of evaluation of the Attitudes for Physical education. 2. To create instruments of collection, analysis and data processing. 3. Validity of the objectives. 4. To verify the hypothesis. The hypothesis: «whatever more information is arranged on a student, diminish the possibilities of being mistaken in its qualification». Methodology: diseño Longitudinal of Panel has been followed. Two work groups, 4º «F» and, 4º «G» of E.S.O., I. E. S. of Malaga «Labor University», course 06/07. 4º F evaluated with the traditional model of evaluation, 4º G with the experimental one. In both groups actitudinales variables took shelter: the independent variables were applied to the experimental group, and the employees to the group control. The results, were analyzed, to see if the independent variable, were the cause of the improvement in the results. The direct observation, the collection of data has been used, using instruments: notebooks of registries of 4º of E.S.O., personal leaves of attitudes by scopes of performance, record book of the student, and group, and text book for 4º of E.S.O. Conclusion: all process of evaluation is complex more and in Physical education, by the volume, the variety, diversity and the origin of the information, to design instruments of collection of data, to individualize the process, to be the pupils in movement. The results affirm that the evaluation is effective, to whatever more information is had.

An overlapping semantic community detection algorithm base on the ARTs multiple sampling models

Since the Semantic Social Network (SSN) is a new kind of complex networks, the traditional community detection algorithms require giving the number of the communities and could not detect the overlapping communities. To solve this problem, we propose improving multiple sampling models ARTs, consisting of ART, LART, ARTF and LARTF, sampling the textual information specific to node, link, node field, and link field correspondingly. The proposed ARTs models separate the semantic community detection into context sampling and communities detecting stage. After the context sampling, the quantized semantic coordinate is allocated to each sampling element, by which the cohesion for each sampling field can be established, avoiding the presetting of the number of communities. As the ARTs models are not easy to convergence, we explore the multiple sampling to accelerate the convergence, and the parameters of ARTs are analyzed by experimental analysis. In evaluation aspect, some traditional evaluation models are extended for semantic community measurement. Finally, efficiency of ARTs is verified by experiment.