Integrated Evaluation Criterion Research Articles

Label-Free Single Cell Viability Assay Using Laser Interference Microscopy.

Laser interference microscopy (LIM) is a promising label-free method for single-cell research applicable to cell viability assessment in the studies of mammalian cells. This paper describes the development of a sensitive and reproducible method for assessing cell viability using LIM. The method, based on associated signal processing techniques, has been developed as a result of real-time investigation in phase thickness fluctuations of viable and non-viable MCF-7 cells, reflecting the presence and absence of their metabolic activity. As evinced by the values of the variable vc, this variable determines the viability of a cell only in the attached state (vc exceeds 20 nm2 for viable attached cells). The critical value of the power spectrum slope βc of the phase thickness fluctuations equals 1.00 for attached MCF-7 cells and 0.71 for suspended cells. The slope of the phase fluctuations' power spectrum for MCF-7 cells was determined to exceed the threshold value of βc for a living cell, otherwise the cell is dead. The results evince the power spectrum slope as the most appropriate indicator of cell viability, while the integrated evaluation criterion (vc and βc values) can be used to assay the viability of attached cells.

Integrated Evaluation Criteria of Economic Benefit and Energy Value Efficiency of Micro Grid

An evaluation criterion of micro grid is proposed from the perspective of economy, energy conservation and emission reduction. The heterogeneous energy such as cold, heat and electricity based on the micro grid taking combined cooling heating and power as the core was evaluated based on the energy value through the cascade utilization of energy, and the micro-grid optimization model including the micro-turbine, waste heat boiler, lithium bromide absorption chiller, fan and photovoltaic was established. As compared with the model of cost optimization only, its integrated optimization index increased by 11.547% and the efficiency of exergy increased by 14.651%.

Improving deep forest by ensemble pruning based on feature vectorization and quantum walks

Recently, a deep learning model, the deep forest (DF), was designed as an alternative to deep neural networks. Each cascade layer of the DF contains a set of random forests (RFs) with a large number of decision trees, some of which are of high redundancy and poor performance. To avoid the negative impacts of such decision trees, this paper proposes to optimize RFs in each cascade layer of the DF so as to realize a pruned deep forest (PDF) with higher performance and smaller ensemble size. In this paper, a new ordering-based ensemble pruning method is proposed based on feature vectorization and quantum walks. This method simultaneously considers the accuracy and the diversity of base classifiers, and it provides an integrated evaluation criterion for ordering base classifiers in the ensemble system. The effectiveness of the proposed method is verified by experiments and discussions.

Integrated Mechanical-Economic–Environmental Quality of Performance for Natural Fibers for Polymeric-Based Composite Materials

ABSTRACTIn this work, a proposed evaluation tool for the performance of the available natural fibers based on integrated technical, economic, and environmental stand points is demonstrated. A novel Cost Per Waste-Volume Ratio (CPWVR) eco-friendly indicator for natural fibers is introduced here for the first time. Various natural fiber types were evaluated regarding the suggested integrated evaluation criteria simultaneously to capture the quality of fiber performance for producing biomaterials. Better evaluations of natural fibers regarding wide range of criteria will lead to better decisions regarding fibers’ qualities as well as their selections for industrial applications and enhance achieving better performance. Such evaluations should consider economic, physical, mechanical, and environmental characteristics as well as technical ones. New potential fiber types can be discovered and utilized in future cleaner production through keen evaluation criteria.

A development of integrated evaluation criteria model for measurement of career success of Korean office worker

A development of integrated evaluation criteria model for measurement of career success of Korean office worker

Customer credit scoring using a hybrid data mining approach

Purpose A crucial decision in financial services is how to classify credit or loan applicants into good and bad applicants. The purpose of this paper is to propose a four-stage hybrid data mining approach to support the decision-making process. Design/methodology/approach The approach is inspired by the bagging ensemble learning method and proposes a new voting method, namely two-level majority voting in the last stage. First some training subsets are generated. Then some different base classifiers are tuned and afterward some ensemble methods are applied to strengthen tuned classifiers. Finally, two-level majority voting schemes help the approach to achieve more accuracy. Findings A comparison of results shows the proposed model outperforms powerful single classifiers such as multilayer perceptron (MLP), support vector machine, logistic regression (LR). In addition, it is more accurate than ensemble learning methods such as bagging-LR or rotation forest (RF)-MLP. The model outperforms single classifiers in terms of type I and II errors; it is close to some ensemble approaches such as bagging-LR and RF-MLP but fails to outperform them in terms of type I and II errors. Moreover, majority voting in the final stage provides more reliable results. Practical implications The study concludes the approach would be beneficial for banks, credit card companies and other credit provider organisations. Originality/value A novel four stages hybrid approach inspired by bagging ensemble method proposed. Moreover the two-level majority voting in two different schemes in the last stage provides more accuracy. An integrated evaluation criterion for classification errors provides an enhanced insight for error comparisons.

Simulation study on the thermal performance of vertical U-tube heat exchangers for ground source heat pump system

The Vertical U-tube ground source heat exchanger (GSHE) is a significant component of the ground source heat pump (GSHP) system. This paper investigates the effect of Reynolds number, tube diameter and tube-connection configurations on the thermal and pressure performance of vertical U-tube GSHEs numerically. The simulation study was verified by ground thermal response experimental test. Meanwhile, the dimensionless evaluation criterion and the integrated evaluation criterion were adopted to analyze the thermal and pressure performance of GSHEs. The results show that the integrated evaluation factor was 5.11, 11.55, and 13.25 for Re = 100, Re = 1000, Re = 1600, respectively. The integrated evaluation factor was 11.48, 11.55 and 12.14 for different tube external diameters of DN25, DN32 and DN40. Therefore, better integrated performance can be obtained by increasing Reynolds number and U-tube diameter under laminar flow condition. Furthermore, parallel U-tubes GSHEs can ensure higher heat flux and lower pressure drop.

A novel operation strategy for CCHP systems based on minimum distance

Abstract A novel operation strategy based on minimum distance was proposed. Also, an integrated evaluation criterion which can reflect the matching performance between the CCHP (combined cooling, heating and power) system and the building was presented. A hospital in Shanghai was used to evaluate the CCHP system with the proposed strategy using the proposed evaluation criterion. The proposed operation strategy was compared with FEL (following the electric load), FTL (following the thermal load) and FHL (following hybrid electric-thermal load) strategies. The results show that the matching performance evaluation criterion is reasonable and integrated. The system with a better matching performance would be fully used and maintain high efficiency. Compared with FEL, FTL and FHL strategies, the proposed operation strategy is flexible and adaptable, which can lead to a better matching performance for a CCHP system. In the case study, the optimized power generation unit capacity and weightings of the optimized operation strategy are 900 kW and w1,above equals to 0.4, w1,below equals to 0.1, respectively.

Analysis and Evaluation of ELT Smartphone Applications

The number of smartphone users has been sharply increasing every year and mobile learning content providers have released numerous educational smartphone applications (apps) including those for English language teaching (ELT) in a very short time. Though, integrated evaluation criteria for mobile-assisted language learning (MALL) content has been non-existent. In this research, the trends of ELT apps were summarized by examining a hundred ELT apps. Also, five representative apps among these were thoroughly analyzed and carefully evaluated according to a set of evaluation criteria. The results of the examination of the apps and an in-depth evaluation of five of the apps showed that existing ELT apps focused mostly on teaching vocabulary, that they should be more accessible to users of different smartphones, and that at least one or two activities should be contained in an ELT app to help learners recycle content. These implications not only report the current trends of ELT, apps but also provide a new direction for developing mobile learning content.

Adaptive nonlinear neuro-controller with an integrated evaluation algorithm for nonlinear active noise systems

An adaptive nonlinear neuro-controller with an integrated evaluation algorithm for nonlinear active noise control systems is proposed to attenuate the nonlinear and non-Gaussian noises. Inspired by the structure of the Hammerstein or Wiener model, the proposed controller is realized by the static nonlinear memory function mapping on the basis of a single neuron. A generalized filtered-X gradient descent algorithm based on an integrated evaluation criterion is developed to adaptively adjust the weights of the controller, where the weighted sum of Renyi's quadratic error entropy and the mean square error is applied as the integrated performance index, which improves the performance of the adaptive algorithm by introducing the information entropy. In addition, the convergence of the proposed approach is analyzed, and the computational complexity among different methods is investigated. The proposed scheme can effectively attenuate the nonlinear and non-Gaussian noises and has a relative simple structure and less learning parameters. The simulation results demonstrate the validity of the proposed method for attenuating the nonlinear and non-Gaussian noises.

Solving Truck Delivery Problems Using Integrated Evaluation Criteria Based on Neighborhood Degree and Evolutionary Algorithm

To solve a real-world truck delivery and dispatch problem (TDDP) that involves multiple mutually conflicting objectives, such as running and loading costs, a concept of neighborhood degree (ND) and an integrated evaluation criteria (IEC) of the solution based on ND are proposed. The IEC makes the weight setting easier than by using conventional methods. To find a high-quality solution to a TDDP in practical computational time, an evolutionary algorithm is proposed. It involves 3 components: (i) a simulated annealing (SA)-based method for finding an optimal or a suboptimal route for each vehicle; (ii) an evolutionary computation (EC)-based method for finding an optimal schedule for a group of vehicles; and (iii) threshold-based evolutionary operations, utilizing the ND concept. The TDDP viewed from real-world application is formulated and the proposed algorithm is implemented on a personal computer using C++. The proposed algorithm is evaluated in 2 experiments involving real-world data representative of the TDDP, and applied to food product delivery to a chain of 46 convenience stores in Saitama Prefecture. In the 2 experiments, our proposed algorithm resulted in a better schedule (with 80%-90% shorter computational time) than a schedule produced by an expert. By incorporating application-specific evaluation criteria, the proposed algorithm is applied to problems such as home-delivery of parcels or mail, and to problems of multidepot delivery and dispatch.